Enumerating the impact of COVID-19 on cancer pathways: a robust evaluation of the NHS Digital Trusted Research Environment

The COVID-19 pandemic has been a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years.

During the first wave of the pandemic dramatic reductions were detected in the demand for, and supply of, cancer services which did not fully recover prior to the arrival of the COVID-19 second wave. These may contribute, to substantial excess mortality among people with cancer and multi-morbidity. It is a matter of great urgency to understand how the recovery of general practitioner, oncology and other hospital services might best mitigate these long-term excess mortality risks

The indirect impacts on the presentation, diagnosis, management and prognosis of cancer resulting from the response by governments and health services to the COVID-19 pandemic also need to be examined. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between regions), effects on different in- and out-patient services and treatments, and changes over time in response to mitigating actions (e.g. regional and national government advice), is urgently needed to inform government and NHS policy.

Under this Agreement, the University of Leeds and Leeds Teaching Hospitals NHS Foundation Trust (LTHT) will use the Secure Data Environment (SDE) service for England to enable analyses of linked, nationally collated healthcare datasets to enumerate the impact of COVID-19 on cancer pathways. The research questions will delineate the precise impact of the COVID-19 pandemic on cancer systems and cancer patients. This requires access to both historical data (pre-2020) and near real-time data on patients referred with (i) a suspicion of cancer and (ii) those diagnosed with and/or managed for cancer.

The specific aims are to examine the effects of COVID-19 on:

• Cancer referral (including those which lead to a cancer diagnosis and those where cancer is excluded);

• Cancer diagnosis (including date, tumour site, stage, grade, morphology and key molecular/genetic/ phenotype);

• Cancer treatment (including surgical procedures, chemotherapy/targeted therapy and radiotherapy);

• Clinical trial activity including recruitment to and active treatment within trials;

• Outcomes (including both hospital admission, survival, mortality and cause of death) and;

• COVID status (including COVID testing (Pillar 1&2) and results, acute hospitalisation and related direct COVID deaths in cancer patients).

• Rates of COVID infection, hospitalisation and death in discrete health care regions.

The processing of data for this study is a task of public interest. The University of Leeds and Leeds Teaching Hospitals NHS Trust are Data Controllers and process data under the legal basis of Article 6(1)(e) ‘processing is necessary for the performance of a task in the public interest and processes special category data under Article 9(2)(j) ‘processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes…’ as the data are required for research purposes in the public interest and judged subject to the appropriate safeguards.

This programme requires access to both historical data (pre 2020) and near real-time data on patients referred with

(i) a suspicion of cancer and

(ii) those diagnosed with and/or managed for cancer.

A comparison of activity from 2019 and 2020 will include patients diagnosed with cancer at any time before then. A maximum of 10 years data prior to 2020 will be worked on to enable cancer survival analyses at 1, 2, 5 and 10 year intervals. These are the standard research mortality statistics.

The work is organised into work packages (WPs) and led by representatives of DATA-CAN employed by either the University of Leeds or LTHT. Each work package is considered by the members of DATA-CAN’s Management group for scientific and clinical ratification. The Management group includes a Patient and Public Involvement and Engagement (PPIE) Lead. This group will give independent advice to the work package lead. Once finalised, the work package will be assigned to an approved individual with relevant expertise to undertake the work in the SDE.

PPIE involvement will be embedded throughout all activities, as this is a core way of working for DATA-CAN.

For instance, across DATA-CAN there has been PPIE representation in the selection and interview panels for the Chief Operating Officer, in every proposal or approach received from commercial organisations, in the development and uses of real-time data (for instance in the Covid-19 and cancer work), at all management groups and at all Steering Groups. DATA-CAN’s PPIE members have also undertaken in-depth work looking at the “value” of several large-scale organisations. To ensure PPIE members are supported and play a full and active part in all DATA-CAN activities, they are provided with in-depth training on “patient data” including 1:1 mentorship, 2-weekly data-drop-in sessions, a set of bespoke learning resources, plus direct access to the PPIE Lead for advice at any time.

In respect of DATA-CAN’s use of NHS England's SDE, some specific areas where patients will be represented by the PPIE group are in :

• The operational processes of running the SDE, including safeguards, controls audits and transparency.

• Reviewing any application to utilise the data in the SDE, including making sure that the application is clearly understandable and has clear potential for patient benefit.

• Reviewing or producing lay summaries of the activity of the SDE, including website content and external communications.

• Mapping out the optimal routes for dissemination for patient benefit, rather than just relying on publication in academic journals. This will include an up-front communications plan for different pieces of work, co-designed with the PPIE group, ensuring results are disseminated and promoted to a lay audience, encouraging them to use this information further.

• PPIE members have a real interest in impact, rather than just the “doing” of the research. They are mapping the “reach” of current PPIE group members, recognising many of them will also be involved with other local and national work, or with charities. DATA-CAN’s philosophy is to utilise those links/voices to ensure results are communicated out widely, ensuring a greater awareness and understanding of the work of the SDE.

• Working with the DATA-CAN Communications team, ensure the best use of social media to advertise the work of the SDE, the outcomes of any results, and the implications for the NHS and patients (current and future).

• Contributing to the production of a lay-accessible annual patient report, which will describe the work of the overall programme, including the activity and outputs of the SDE, with details of the benefits of the work which has been produced.

• Supporting the work of the use MY data patient movement, which operates independently from DATA-CAN. Their communication routes can be seen, through their Newsletter and other means, as another mechanism to communicate with a wider group.

• Lastly, the PPIE group will play a leading role in communications through media and third sector organisations by co-authoring lay summaries or case studies, by providing patient quotations in press releases, and potentially by engaging directly with the media.

A Scientific Steering Group (SSG) has been set up by DATA-CAN specifically for the SDE. All of the above elements of the PPIE group apply to this SSG. The SSG is chaired by the Scientific Director of DATA-CAN and has representation from the HRDUK research community, the National Disease Registration Service (formerly of PHE, now NHS England) and senior representation from UK-wide data research.

All purposes for which the data will be used will be reviewed and given favourable recommendation by the SSG.

The following work packages (WP) have been identified and ratified by the process described above:

WP 1 – Coordination (led by DATA-CAN):

This work package aims to identify relevant datasets and required dataset linkages across the UK; to coordinate applications for relevant research group access for work packages if not being conducted by DATA-CAN partners, and to coordinate specialist inputs from the oncology community and other relevant clinical groups. Work is ongoing across all four nations to identify and assemble the relevant national datasets, enable their linkage, agree mechanisms for regular updates and establish routes for expedited approval and access for approved researchers within trusted research environments in each of the four nations.

WP 2 - Analyses:

This work package aims to refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses. Analyses based on routinely collected, national healthcare datasets have the advantages of large scale and comprehensive coverage, maximising statistical power as well as inclusiveness/representativeness (e.g. across all age groups, ethnicities, geographies and socioeconomic settings).

WP 3 - Public, patient and professional involvement and communications:

Work DATA-CAN Patient, Public, Involvement and Engagement group and other PPIE panels/ professionals to provide input into refining questions, assessing the impact of the results, and preparing reports for lay audiences. Lead on communications of activity and emerging results through websites, social media and other outlets. Lead on interactions with press and other media.

These work packages relate to the use of data in the SDE in the following ways:

- WP1 has led to the identification of and aspiration to access the datasets via the SDE under this Agreement for the purposes described under WP 2.

- WP2 has yielded a number of planned analyses to be undertaken within the SDE. Those that have been planned via this process so far are described below as indicative examples to give insight into the work that will be undertaken under this Agreement. However, during the course of this Agreement, WP2 will yield additional analysis plans as new questions emerge and will go through the same ratification process prior to being assigned and undertaken.

- WP3 will focus on the outputs of WP2 including the outputs of analyses undertaken using the data in the SDE.

The following are examples of analysis plans which will be undertaken using the data in the SDE under WP2:

• WP 2.1 - Indirect impact of COVID-19 on cancer:

An analysis of time trends in hospital activity (admissions by diagnosis, treatments, procedures) using hospital and disease audit datasets, registered deaths by cause and primary care activity before, during and after COVID-19 pandemic. An immediate priority for informing government policy across the UK is to assess the indirect impact of COVID-19 on cancer. Analysis will address trends in cancer referral and diagnosis before and during the COVID-19 pandemic in England and will be extended to incorporate data from the other UK nations (Scotland, Wales and Northern Ireland) when it becomes available.

• WP 2.2 - Influence/associations of cancer on COVID-19 outcomes (such as admissions to hospital, admission to ITU, mechanical ventilation and death):

The influence/associations of pre-existing cancer diagnosis on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on previous medical history with COVID-19 test results, hospitalisation, critical care and mortality datasets, with adjustment for multiple confounders (including risk factors and co-morbidities).

• WP 2.3 - Influence/associations of cancer risk factors on COVID-19 outcomes:

The influence/associations of cancer risk factors on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on cancer risk factors such as blood pressure, body mass index and smoking status with COVID-19 tests, hospitalisation, critical care and mortality datasets, with adjustment for multiple co-morbidities.

• WP 2.4 - Influence/associations of cancer medications on COVID-19 outcomes:

This package will provide information to enable government agencies (e.g., MHRA and NICE) to give evidence-based advice to healthcare professionals and patients on drug regimens and risk of COVID-19. Impact of the NICE COVID interim treatment regimens on COVID-19 outcomes (hospitalisation, admission to ICU, mechanical ventilation and mortality).

• WP 2.5 - Direct impact of COVID-19 disease on cancer disease occurrence, re-occurrence and outcomes in short, medium and long term:

Linkage of population routine datasets (demography including mortality, primary care, hospital) and audit datasets will enable comprehensive assessment of the impact of COVID-19 disease on cancer occurrence, reoccurrence and outcomes in short, medium and long term. With SARS-CoV2 potentially circulating for at least several years in the population, it will be important to estimate the short-, medium- and long-term effects of infection on incidence of cancer.

GOVERNANCE CONSIDERATIONS:

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are joint Data Controllers.

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are founding members of DATA-CAN along with:

• UCL Partners

• Queen’s University, Belfast

• Genomics England

• IQVIA

DATA-CAN funding pays for staffing posts with founding member organisations. Acting as agents of their substantive employers, postholders have freedom to identify, plan, refine and assign work packages in support of DATA-CAN’s aims such as those to be undertaken in the SDE. All decisions concerning the purpose for and manner of processing personal data as described in this Agreement have been taken by employees of the University of Leeds and of the Leeds Teaching Hospitals NHS Trust.

The SDE will be accessed by and data will be processed by substantive employees of the Data Controllers and those under honorary contractual arrangements with the Data Controller/s. No other collaborators have involvement either in capacity as a data controller or processor.

While UCL Partners are the legal vehicle for the DATA-CAN hub, they do not have the work force for, or track record of, data analysis or data management. In accordance with the DATA-CAN consortium agreement the main data analyst resource is concentrated in Leeds and Belfast partner organisations. Under this Agreement, the Belfast partner organisation, Queens University, Belfast, has no involvement either in capacity as a data controller or processor.

The lawful basis for processing personal data under the UK GDPR is:

Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is:

Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

DATA REQUIREMENTS:

These analyses require access to linked data from the personal demographic service, primary care, hospital emergency, inpatient and outpatient care, intensive care, registered deaths by cause, cancer registries and COVID-19 laboratory testing. All data will be accessed by named, approved researchers (certified to have successfully completed safe researcher training) in the SDE within NHS England.

The data within the SDE will be pseudonymised. NHS England will strip identifiers from each record, apply a pseudo-ID to each record and perform the data linkage. No identifiable data will be accessible within the SDE.

The following linked datasets will be required for the purposes of this programme of work:

1. COVID-19 Second Generation Surveillance System (Beta version)

2. COVID-19 UK Non-hospital Antigen Testing Results (pillar 2) Service Types

3. CHESS: COVID-19 Hospitalisation in England Surveillance System

These datasets will provide details of COVID-19 test results and acute hospitalisations from COVID-19. These datasets will be used to ascertain all cases with proven SARS-CoV2 infection and to provide information on the severity and treatments of people with COVID-19.

Linkage of these data to data on hospitalisations, intensive care and mortality will be used to indicate the severity of COVID-19 disease. Data across all datasets should include information on patients who died prior to 2020 to all comparison of medical histories and mortality associated with a range of conditions prior to, during and – in due course – after the COVID-19 pandemic.

8. National Cancer Waiting Times (CWT)

9. NDRS Cancer Consolidated Dataset

These datasets will provide details of urgent cancer referrals including cancer waiting lists; details of surgeries and treatments including radiotherapy and chemotherapy including treatments within a clinical trial.

10. Civil Registration Mortality data

This dataset will provide survival data. Mortality data are needed to provide information on dates and underlying and contributing causes of death as part of the assessment of the severity of the COVID-19 disease and its impact on cancer.

11. Hospital Episode Statistics (HES) Admitted Patient Care

12. HES Outpatient

13. HES Accident & Emergency

14. Uncurated Low Latency Hospital Data Set - Emergency Care

15. GPES Data for Pandemic Planning and Research (GDPPR)

16. Medicines dispensed in Primary Care (NHS BSA data)

These datasets will provide details of patients’ prior medical history (co-morbidities); details of hospital attendances for cancer conditions before, during and (in due course) after the COVID-19 emergency, and information needed to assess other risk factors (age, sex, ethnicity, socioeconomic status, obesity, high blood pressure, high cholesterol, diabetes, etc.) and prescribed medications for those who have and have not gone on to develop COVID-19 disease with varying levels of severity.

The above data will be minimised to:

- only include those datasets required to address the cancer-related questions included within the Agreement;

- only for cancer-related research purposes, as outlined in the proposal;

- have a “per project” basis (by dataset, by year, and by “groups” of fields rather than individual fields)

- only be included if they are urgent or do not require data minimisation beyond minimisation at the dataset level (as an interim measure until these data minimisation techniques can be applied).

Some analyses based on primary care data will require analysis at the level of individual GP practices. For example, this will be required for work package 2.5, which aims to use practice prescribing preferences as an instrumental variable to assess the potential effects of different antihypertensive medications on outcomes of COVID-19. However, by default, no individual practice or health service practitioner will be identified in any research output. Should any research project be proposed that would require the identification of individual practices, researchers would seek guidance from NHS England and their GP advisory group about any issues that this might raise (for example, the potential identification of practitioners in single-handed practices) and how these should be addressed.

Uncurated Low Latency Hospital Data Set - Emergency Care is requested under this agreement as a tactical version of the Emergency Care Dataset (ECDS) as the full ECDS dataset is currently unavailable. ECDS data is included in this version of the agreement so that once the full version of the dataset is available, it can be provided via the SDE.

The outputs of each piece of work were reported to the Scientific Advisory Group for Emergencies (SAGE) and equivalent bodies in the devolved nations during the Covid19 pandemic so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs will also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK. Outputs will inform the clinical management of patients with different types of cancer presenting with COVID-19 disease.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of DATA-CAN with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS England, Public Health Scotland and the SAIL Databank for Wales.

No individual practice or health service practitioner will be identified in any research output.

Due to technical issues with the cancer data, it is expected that outputs will start to emerge within weeks of data becoming available to the research team and will continue to be produced throughout the period of the project through to April 2026. By their nature, those outputs providing information on the longer term impacts and implications of these for clinical care and public health policy will take at least several months from the availability of data to start emerging.

No outputs have been generated as yet due to the technical issues with the cancer data, experienced up to late 2023/early 2024, and it is hoped to be able to achieve these over the next 12 months.

Data was received in March 2022 and this has enabled collaboration between DATA-CAN and NHS England to develop looking at areas such as data quality, metadata and data dictionaries, as well as exploring how the SDE can be refined to suit the needs of the various users, including DATA-CAN.

Research has begun on the five work packages described in the objectives section of this DSA, with the cancer datasets released in March 2022 proving particularly helpful. The first publication linked to work package 2.1 looking at the indirect impact of Covid-19 on cancer, was due in June 2022. Unfortunately, this deadline was not met due to delays in accessing some of the cancer data. This is ongoing and hoped to be achieved within the next 6 months. To date, it has not been possible to complete the work packages outlined within this agreement as a result of the technical issues with the data. Improvements to the datasets during 2024 meant that projects could now progress and the target for publication is now to be in the next 6 to 12 months.

This extension to the agreement will enable work to continue in supporting quality check work within the SDE and also so that, once the data quality is right, work can progress within the specified work packages in line with the dates outlined.

The COVID-19 pandemic has been a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years.

During the first wave of the pandemic dramatic reductions were detected in the demand for, and supply of, cancer services which did not fully recover prior to the arrival of the COVID-19 second wave. These may contribute, to substantial excess mortality among people with cancer and multi-morbidity. It is a matter of great urgency to understand how the recovery of general practitioner, oncology and other hospital services might best mitigate these long-term excess mortality risks

The indirect impacts on the presentation, diagnosis, management and prognosis of cancer resulting from the response by governments and health services to the COVID-19 pandemic also need to be examined. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between regions), effects on different in- and out-patient services and treatments, and changes over time in response to mitigating actions (e.g. regional and national government advice), is urgently needed to inform government and NHS policy.

Under this Agreement, the University of Leeds and Leeds Teaching Hospitals NHS Foundation Trust (LTHT) will use the Secure Data Environment (SDE) service for England to enable analyses of linked, nationally collated healthcare datasets to enumerate the impact of COVID-19 on cancer pathways. The research questions will delineate the precise impact of the COVID-19 pandemic on cancer systems and cancer patients. This requires access to both historical data (pre-2020) and near real-time data on patients referred with (i) a suspicion of cancer and (ii) those diagnosed with and/or managed for cancer.

The specific aims are to examine the effects of COVID-19 on:

• Cancer referral (including those which lead to a cancer diagnosis and those where cancer is excluded);

• Cancer diagnosis (including date, tumour site, stage, grade, morphology and key molecular/genetic/ phenotype);

• Cancer treatment (including surgical procedures, chemotherapy/targeted therapy and radiotherapy);

• Clinical trial activity including recruitment to and active treatment within trials;

• Outcomes (including both hospital admission, survival, mortality and cause of death) and;

• COVID status (including COVID testing (Pillar 1&2) and results, acute hospitalisation and related direct COVID deaths in cancer patients).

• Rates of COVID infection, hospitalisation and death in discrete health care regions.

The processing of data for this study is a task of public interest. The University of Leeds and Leeds Teaching Hospitals NHS Trust are Data Controllers and process data under the legal basis of Article 6(1)(e) ‘processing is necessary for the performance of a task in the public interest and processes special category data under Article 9(2)(j) ‘processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes…’ as the data are required for research purposes in the public interest and judged subject to the appropriate safeguards.

This programme requires access to both historical data (pre 2020) and near real-time data on patients referred with

(i) a suspicion of cancer and

(ii) those diagnosed with and/or managed for cancer.

A comparison of activity from 2019 and 2020 will include patients diagnosed with cancer at any time before then. A maximum of 10 years data prior to 2020 will be worked on to enable cancer survival analyses at 1, 2, 5 and 10 year intervals. These are the standard research mortality statistics.

The work is organised into work packages (WPs) and led by representatives of DATA-CAN employed by either the University of Leeds or LTHT. Each work package is considered by the members of DATA-CAN’s Management group for scientific and clinical ratification. The Management group includes a Patient and Public Involvement and Engagement (PPIE) Lead. This group will give independent advice to the work package lead. Once finalised, the work package will be assigned to an approved individual with relevant expertise to undertake the work in the SDE.

PPIE involvement will be embedded throughout all activities, as this is a core way of working for DATA-CAN.

For instance, across DATA-CAN there has been PPIE representation in the selection and interview panels for the Chief Operating Officer, in every proposal or approach received from commercial organisations, in the development and uses of real-time data (for instance in the Covid-19 and cancer work), at all management groups and at all Steering Groups. DATA-CAN’s PPIE members have also undertaken in-depth work looking at the “value” of several large-scale organisations. To ensure PPIE members are supported and play a full and active part in all DATA-CAN activities, they are provided with in-depth training on “patient data” including 1:1 mentorship, 2-weekly data-drop-in sessions, a set of bespoke learning resources, plus direct access to the PPIE Lead for advice at any time.

In respect of DATA-CAN’s use of NHS England's SDE, some specific areas where patients will be represented by the PPIE group are in :

• The operational processes of running the SDE, including safeguards, controls audits and transparency.

• Reviewing any application to utilise the data in the SDE, including making sure that the application is clearly understandable and has clear potential for patient benefit.

• Reviewing or producing lay summaries of the activity of the SDE, including website content and external communications.

• Mapping out the optimal routes for dissemination for patient benefit, rather than just relying on publication in academic journals. This will include an up-front communications plan for different pieces of work, co-designed with the PPIE group, ensuring results are disseminated and promoted to a lay audience, encouraging them to use this information further.

• PPIE members have a real interest in impact, rather than just the “doing” of the research. They are mapping the “reach” of current PPIE group members, recognising many of them will also be involved with other local and national work, or with charities. DATA-CAN’s philosophy is to utilise those links/voices to ensure results are communicated out widely, ensuring a greater awareness and understanding of the work of the SDE.

• Working with the DATA-CAN Communications team, ensure the best use of social media to advertise the work of the SDE, the outcomes of any results, and the implications for the NHS and patients (current and future).

• Contributing to the production of a lay-accessible annual patient report, which will describe the work of the overall programme, including the activity and outputs of the SDE, with details of the benefits of the work which has been produced.

• Supporting the work of the use MY data patient movement, which operates independently from DATA-CAN. Their communication routes can be seen, through their Newsletter and other means, as another mechanism to communicate with a wider group.

• Lastly, the PPIE group will play a leading role in communications through media and third sector organisations by co-authoring lay summaries or case studies, by providing patient quotations in press releases, and potentially by engaging directly with the media.

A Scientific Steering Group (SSG) has been set up by DATA-CAN specifically for the SDE. All of the above elements of the PPIE group apply to this SSG. The SSG is chaired by the Scientific Director of DATA-CAN and has representation from the HRDUK research community, the National Disease Registration Service (formerly of PHE, now NHS England) and senior representation from UK-wide data research.

All purposes for which the data will be used will be reviewed and given favourable recommendation by the SSG.

The following work packages (WP) have been identified and ratified by the process described above:

WP 1 – Coordination (led by DATA-CAN):

This work package aims to identify relevant datasets and required dataset linkages across the UK; to coordinate applications for relevant research group access for work packages if not being conducted by DATA-CAN partners, and to coordinate specialist inputs from the oncology community and other relevant clinical groups. Work is ongoing across all four nations to identify and assemble the relevant national datasets, enable their linkage, agree mechanisms for regular updates and establish routes for expedited approval and access for approved researchers within trusted research environments in each of the four nations.

WP 2 - Analyses:

This work package aims to refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses. Analyses based on routinely collected, national healthcare datasets have the advantages of large scale and comprehensive coverage, maximising statistical power as well as inclusiveness/representativeness (e.g. across all age groups, ethnicities, geographies and socioeconomic settings).

WP 3 - Public, patient and professional involvement and communications:

Work DATA-CAN Patient, Public, Involvement and Engagement group and other PPIE panels/ professionals to provide input into refining questions, assessing the impact of the results, and preparing reports for lay audiences. Lead on communications of activity and emerging results through websites, social media and other outlets. Lead on interactions with press and other media.

These work packages relate to the use of data in the SDE in the following ways:

- WP1 has led to the identification of and aspiration to access the datasets via the SDE under this Agreement for the purposes described under WP 2.

- WP2 has yielded a number of planned analyses to be undertaken within the SDE. Those that have been planned via this process so far are described below as indicative examples to give insight into the work that will be undertaken under this Agreement. However, during the course of this Agreement, WP2 will yield additional analysis plans as new questions emerge and will go through the same ratification process prior to being assigned and undertaken.

- WP3 will focus on the outputs of WP2 including the outputs of analyses undertaken using the data in the SDE.

The following are examples of analysis plans which will be undertaken using the data in the SDE under WP2:

• WP 2.1 - Indirect impact of COVID-19 on cancer:

An analysis of time trends in hospital activity (admissions by diagnosis, treatments, procedures) using hospital and disease audit datasets, registered deaths by cause and primary care activity before, during and after COVID-19 pandemic. An immediate priority for informing government policy across the UK is to assess the indirect impact of COVID-19 on cancer. Analysis will address trends in cancer referral and diagnosis before and during the COVID-19 pandemic in England and will be extended to incorporate data from the other UK nations (Scotland, Wales and Northern Ireland) when it becomes available.

• WP 2.2 - Influence/associations of cancer on COVID-19 outcomes (such as admissions to hospital, admission to ITU, mechanical ventilation and death):

The influence/associations of pre-existing cancer diagnosis on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on previous medical history with COVID-19 test results, hospitalisation, critical care and mortality datasets, with adjustment for multiple confounders (including risk factors and co-morbidities).

• WP 2.3 - Influence/associations of cancer risk factors on COVID-19 outcomes:

The influence/associations of cancer risk factors on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on cancer risk factors such as blood pressure, body mass index and smoking status with COVID-19 tests, hospitalisation, critical care and mortality datasets, with adjustment for multiple co-morbidities.

• WP 2.4 - Influence/associations of cancer medications on COVID-19 outcomes:

This package will provide information to enable government agencies (e.g., MHRA and NICE) to give evidence-based advice to healthcare professionals and patients on drug regimens and risk of COVID-19. Impact of the NICE COVID interim treatment regimens on COVID-19 outcomes (hospitalisation, admission to ICU, mechanical ventilation and mortality).

• WP 2.5 - Direct impact of COVID-19 disease on cancer disease occurrence, re-occurrence and outcomes in short, medium and long term:

Linkage of population routine datasets (demography including mortality, primary care, hospital) and audit datasets will enable comprehensive assessment of the impact of COVID-19 disease on cancer occurrence, reoccurrence and outcomes in short, medium and long term. With SARS-CoV2 potentially circulating for at least several years in the population, it will be important to estimate the short-, medium- and long-term effects of infection on incidence of cancer.

GOVERNANCE CONSIDERATIONS:

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are joint Data Controllers.

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are founding members of DATA-CAN along with:

• UCL Partners

• Queen’s University, Belfast

• Genomics England

• IQVIA

DATA-CAN funding pays for staffing posts with founding member organisations. Acting as agents of their substantive employers, postholders have freedom to identify, plan, refine and assign work packages in support of DATA-CAN’s aims such as those to be undertaken in the SDE. All decisions concerning the purpose for and manner of processing personal data as described in this Agreement have been taken by employees of the University of Leeds and of the Leeds Teaching Hospitals NHS Trust.

The SDE will be accessed by and data will be processed by substantive employees of the Data Controllers and those under honorary contractual arrangements with the Data Controller/s. No other collaborators have involvement either in capacity as a data controller or processor.

While UCL Partners are the legal vehicle for the DATA-CAN hub, they do not have the work force for, or track record of, data analysis or data management. In accordance with the DATA-CAN consortium agreement the main data analyst resource is concentrated in Leeds and Belfast partner organisations. Under this Agreement, the Belfast partner organisation, Queens University, Belfast, has no involvement either in capacity as a data controller or processor.

The lawful basis for processing personal data under the UK GDPR is:

Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is:

Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

DATA REQUIREMENTS:

These analyses require access to linked data from the personal demographic service, primary care, hospital emergency, inpatient and outpatient care, intensive care, registered deaths by cause, cancer registries and COVID-19 laboratory testing. All data will be accessed by named, approved researchers (certified to have successfully completed safe researcher training) in the SDE within NHS England.

The data within the SDE will be pseudonymised. NHS England will strip identifiers from each record, apply a pseudo-ID to each record and perform the data linkage. No identifiable data will be accessible within the SDE.

The following linked datasets will be required for the purposes of this programme of work:

1. COVID-19 Second Generation Surveillance System (Beta version)

2. COVID-19 UK Non-hospital Antigen Testing Results (pillar 2) Service Types

3. CHESS: COVID-19 Hospitalisation in England Surveillance System

These datasets will provide details of COVID-19 test results and acute hospitalisations from COVID-19. These datasets will be used to ascertain all cases with proven SARS-CoV2 infection and to provide information on the severity and treatments of people with COVID-19.

Linkage of these data to data on hospitalisations, intensive care and mortality will be used to indicate the severity of COVID-19 disease. Data across all datasets should include information on patients who died prior to 2020 to all comparison of medical histories and mortality associated with a range of conditions prior to, during and – in due course – after the COVID-19 pandemic.

4. National Cancer Registration Dataset (NCRD)

5. Rapid Cancer Registration dataset

6. Systemic Anti-Cancer Therapy (SACT)

7. Radiotherapy Dataset (RTDS)

8. National Cancer Waiting Times (CWT)

9. NDRS Cancer Consolidated Dataset

These datasets will provide details of urgent cancer referrals including cancer waiting lists; details of surgeries and treatments including radiotherapy and chemotherapy including treatments within a clinical trial.

10. Civil Registration Mortality data

This dataset will provide survival data. Mortality data are needed to provide information on dates and underlying and contributing causes of death as part of the assessment of the severity of the COVID-19 disease and its impact on cancer.

11. Hospital Episode Statistics (HES) Admitted Patient Care

12. HES Outpatient

13. HES Accident & Emergency

14. Uncurated Low Latency Hospital Data Set - Emergency Care

15. GPES Data for Pandemic Planning and Research (GDPPR)

16. Medicines dispensed in Primary Care (NHS BSA data)

These datasets will provide details of patients’ prior medical history (co-morbidities); details of hospital attendances for cancer conditions before, during and (in due course) after the COVID-19 emergency, and information needed to assess other risk factors (age, sex, ethnicity, socioeconomic status, obesity, high blood pressure, high cholesterol, diabetes, etc.) and prescribed medications for those who have and have not gone on to develop COVID-19 disease with varying levels of severity.

The above data will be minimised to:

- only include those datasets required to address the cancer-related questions included within the Agreement;

- only for cancer-related research purposes, as outlined in the proposal;

- have a “per project” basis (by dataset, by year, and by “groups” of fields rather than individual fields)

- only be included if they are urgent or do not require data minimisation beyond minimisation at the dataset level (as an interim measure until these data minimisation techniques can be applied).

Some analyses based on primary care data will require analysis at the level of individual GP practices. For example, this will be required for work package 2.5, which aims to use practice prescribing preferences as an instrumental variable to assess the potential effects of different antihypertensive medications on outcomes of COVID-19. However, by default, no individual practice or health service practitioner will be identified in any research output. Should any research project be proposed that would require the identification of individual practices, researchers would seek guidance from NHS England and their GP advisory group about any issues that this might raise (for example, the potential identification of practitioners in single-handed practices) and how these should be addressed.

Uncurated Low Latency Hospital Data Set - Emergency Care is requested under this agreement as a tactical version of the Emergency Care Dataset (ECDS) as the full ECDS dataset is currently unavailable. ECDS data is included in this version of the agreement so that once the full version of the dataset is available, it can be provided via the SDE.

The outputs of each piece of work will be reported to the Scientific Advisory Group for Emergencies (SAGE) and equivalent bodies in the devolved nations so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs will also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK. Outputs will inform the clinical management of patients with different types of cancer presenting with COVID-19 disease.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of DATA-CAN with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS England, Public Health Scotland and the SAIL Databank for Wales.

No individual practice or health service practitioner will be identified in any research output.

Due to technical issues with the cancer data, it is expected that outputs will start to emerge within weeks of data becoming available to the research team and will continue to be produced throughout the period of the project through to April 2025. By their nature, those outputs providing information on the longer term impacts and implications of these for clinical care and public health policy will take at least several months from the availability of data to start emerging.

No outputs have been generated as yet due to technical issues with the cancer data and it is hoped to be able to achieve these over the next 12 months.

Data was received in March 2022 and this has enabled collaboration between DATA-CAN and NHS England to develop looking at areas such as data quality, metadata and data dictionaries, as well as exploring how the SDE can be refined to suit the needs of the various users, including DATA-CAN.

Research has begun on the five work packages described in the objectives section of this DSA, with the cancer datasets released in March 2022 proving particularly helpful. The first publication linked to work package 2.1 looking at the indirect impact of Covid-19 on cancer, was due in June 2022. Unfortunately, this deadline was not met due to delays in accessing some of the cancer data. This is ongoing and hoped to be achieved within the next 6 months. To date, it has not been possible to complete the work packages outlined within this agreement as a result of the technical issues with the data.

This extension to the agreement will enable work to continue in supporting quality check work within the SDE and also so that, once the data quality is right, work can progress within the specified work packages.

The COVID-19 pandemic has been a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years.

During the first wave of the pandemic dramatic reductions were detected in the demand for, and supply of, cancer services which did not fully recover prior to the arrival of the COVID-19 second wave. These may contribute, to substantial excess mortality among people with cancer and multi-morbidity. It is a matter of great urgency to understand how the recovery of general practitioner, oncology and other hospital services might best mitigate these long-term excess mortality risks

The indirect impacts on the presentation, diagnosis, management and prognosis of cancer resulting from the response by governments and health services to the COVID-19 pandemic also need to be examined. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between regions), effects on different in- and out-patient services and treatments, and changes over time in response to mitigating actions (e.g. regional and national government advice), is urgently needed to inform government and NHS policy.

Under this Agreement, the University of Leeds and Leeds Teaching Hospitals NHS Foundation Trust (LTHT) will use the Secure Data Environment (SDE) service for England to enable analyses of linked, nationally collated healthcare datasets to enumerate the impact of COVID-19 on cancer pathways. The research questions will delineate the precise impact of the COVID-19 pandemic on cancer systems and cancer patients. This requires access to both historical data (pre-2020) and near real-time data on patients referred with (i) a suspicion of cancer and (ii) those diagnosed with and/or managed for cancer.

The specific aims are to examine the effects of COVID-19 on:

• Cancer referral (including those which lead to a cancer diagnosis and those where cancer is excluded);

• Cancer diagnosis (including date, tumour site, stage, grade, morphology and key molecular/genetic/ phenotype);

• Cancer treatment (including surgical procedures, chemotherapy/targeted therapy and radiotherapy);

• Clinical trial activity including recruitment to and active treatment within trials;

• Outcomes (including both hospital admission, survival, mortality and cause of death) and;

• COVID status (including COVID testing (Pillar 1&2) and results, acute hospitalisation and related direct COVID deaths in cancer patients).

• Rates of COVID infection, hospitalisation and death in discrete health care regions.

The processing of data for this study is a task of public interest. The University of Leeds and Leeds Teaching Hospitals NHS Trust are Data Controllers and process data under the legal basis of Article 6(1)(e) ‘processing is necessary for the performance of a task in the public interest and processes special category data under Article 9(2)(j) ‘processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes…’ as the data are required for research purposes in the public interest and judged subject to the appropriate safeguards.

This programme requires access to both historical data (pre 2020) and near real-time data on patients referred with

(i) a suspicion of cancer and

(ii) those diagnosed with and/or managed for cancer.

A comparison of activity from 2019 and 2020 will include patients diagnosed with cancer at any time before then. A maximum of 10 years data prior to 2020 will be worked on to enable cancer survival analyses at 1, 2, 5 and 10 year intervals. These are the standard research mortality statistics.

The work is organised into work packages (WPs) and led by representatives of DATA-CAN employed by either the University of Leeds or LTHT. Each work package is considered by the members of DATA-CAN’s Management group for scientific and clinical ratification. The Management group includes a Patient and Public Involvement and Engagement (PPIE) Lead. This group will give independent advice to the work package lead. Once finalised, the work package will be assigned to an approved individual with relevant expertise to undertake the work in the SDE.

PPIE involvement will be embedded throughout all activities, as this is a core way of working for DATA-CAN.

For instance, across DATA-CAN there has been PPIE representation in the selection and interview panels for the Chief Operating Officer, in every proposal or approach received from commercial organisations, in the development and uses of real-time data (for instance in the Covid-19 and cancer work), at all management groups and at all Steering Groups. DATA-CAN’s PPIE members have also undertaken in-depth work looking at the “value” of several large-scale organisations. To ensure PPIE members are supported and play a full and active part in all DATA-CAN activities, they are provided with in-depth training on “patient data” including 1:1 mentorship, 2-weekly data-drop-in sessions, a set of bespoke learning resources, plus direct access to the PPIE Lead for advice at any time.

In respect of DATA-CAN’s use of NHS England's SDE, some specific areas where patients will be represented by the PPIE group are in :

• The operational processes of running the SDE, including safeguards, controls audits and transparency.

• Reviewing any application to utilise the data in the SDE, including making sure that the application is clearly understandable and has clear potential for patient benefit.

• Reviewing or producing lay summaries of the activity of the SDE, including website content and external communications.

• Mapping out the optimal routes for dissemination for patient benefit, rather than just relying on publication in academic journals. This will include an up-front communications plan for different pieces of work, co-designed with the PPIE group, ensuring results are disseminated and promoted to a lay audience, encouraging them to use this information further.

• PPIE members have a real interest in impact, rather than just the “doing” of the research. They are mapping the “reach” of current PPIE group members, recognising many of them will also be involved with other local and national work, or with charities. DATA-CAN’s philosophy is to utilise those links/voices to ensure results are communicated out widely, ensuring a greater awareness and understanding of the work of the SDE.

• Working with the DATA-CAN Communications team, ensure the best use of social media to advertise the work of the SDE, the outcomes of any results, and the implications for the NHS and patients (current and future).

• Contributing to the production of a lay-accessible annual patient report, which will describe the work of the overall programme, including the activity and outputs of the SDE, with details of the benefits of the work which has been produced.

• Supporting the work of the use MY data patient movement, which operates independently from DATA-CAN. Their communication routes can be seen, through their Newsletter and other means, as another mechanism to communicate with a wider group.

• Lastly, the PPIE group will play a leading role in communications through media and third sector organisations by co-authoring lay summaries or case studies, by providing patient quotations in press releases, and potentially by engaging directly with the media.

A Scientific Steering Group (SSG) has been set up by DATA-CAN specifically for the SDE. All of the above elements of the PPIE group apply to this SSG. The SSG is chaired by the Scientific Director of DATA-CAN and has representation from the HRDUK research community, the National Disease Registration Service (formerly of PHE, now NHS England) and senior representation from UK-wide data research.

All purposes for which the data will be used will be reviewed and given favourable recommendation by the SSG.

The following work packages (WP) have been identified and ratified by the process described above:

WP 1 – Coordination (led by DATA-CAN):

This work package aims to identify relevant datasets and required dataset linkages across the UK; to coordinate applications for relevant research group access for work packages if not being conducted by DATA-CAN partners, and to coordinate specialist inputs from the oncology community and other relevant clinical groups. Work is ongoing across all four nations to identify and assemble the relevant national datasets, enable their linkage, agree mechanisms for regular updates and establish routes for expedited approval and access for approved researchers within trusted research environments in each of the four nations.

WP 2 - Analyses:

This work package aims to refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses. Analyses based on routinely collected, national healthcare datasets have the advantages of large scale and comprehensive coverage, maximising statistical power as well as inclusiveness/representativeness (e.g. across all age groups, ethnicities, geographies and socioeconomic settings).

WP 3 - Public, patient and professional involvement and communications:

Work DATA-CAN Patient, Public, Involvement and Engagement group and other PPIE panels/ professionals to provide input into refining questions, assessing the impact of the results, and preparing reports for lay audiences. Lead on communications of activity and emerging results through websites, social media and other outlets. Lead on interactions with press and other media.

These work packages relate to the use of data in the SDE in the following ways:

- WP1 has led to the identification of and aspiration to access the datasets via the SDE under this Agreement for the purposes described under WP 2.

- WP2 has yielded a number of planned analyses to be undertaken within the SDE. Those that have been planned via this process so far are described below as indicative examples to give insight into the work that will be undertaken under this Agreement. However, during the course of this Agreement, WP2 will yield additional analysis plans as new questions emerge and will go through the same ratification process prior to being assigned and undertaken.

- WP3 will focus on the outputs of WP2 including the outputs of analyses undertaken using the data in the SDE.

The following are examples of analysis plans which will be undertaken using the data in the SDE under WP2:

• WP 2.1 - Indirect impact of COVID-19 on cancer:

An analysis of time trends in hospital activity (admissions by diagnosis, treatments, procedures) using hospital and disease audit datasets, registered deaths by cause and primary care activity before, during and after COVID-19 pandemic. An immediate priority for informing government policy across the UK is to assess the indirect impact of COVID-19 on cancer. Analysis will address trends in cancer referral and diagnosis before and during the COVID-19 pandemic in England and will be extended to incorporate data from the other UK nations (Scotland, Wales and Northern Ireland) when it becomes available.

• WP 2.2 - Influence/associations of cancer on COVID-19 outcomes (such as admissions to hospital, admission to ITU, mechanical ventilation and death):

The influence/associations of pre-existing cancer diagnosis on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on previous medical history with COVID-19 test results, hospitalisation, critical care and mortality datasets, with adjustment for multiple confounders (including risk factors and co-morbidities).

• WP 2.3 - Influence/associations of cancer risk factors on COVID-19 outcomes:

The influence/associations of cancer risk factors on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on cancer risk factors such as blood pressure, body mass index and smoking status with COVID-19 tests, hospitalisation, critical care and mortality datasets, with adjustment for multiple co-morbidities.

• WP 2.4 - Influence/associations of cancer medications on COVID-19 outcomes:

This package will provide information to enable government agencies (e.g., MHRA and NICE) to give evidence-based advice to healthcare professionals and patients on drug regimens and risk of COVID-19. Impact of the NICE COVID interim treatment regimens on COVID-19 outcomes (hospitalisation, admission to ICU, mechanical ventilation and mortality).

• WP 2.5 - Direct impact of COVID-19 disease on cancer disease occurrence, re-occurrence and outcomes in short, medium and long term:

Linkage of population routine datasets (demography including mortality, primary care, hospital) and audit datasets will enable comprehensive assessment of the impact of COVID-19 disease on cancer occurrence, reoccurrence and outcomes in short, medium and long term. With SARS-CoV2 potentially circulating for at least several years in the population, it will be important to estimate the short-, medium- and long-term effects of infection on incidence of cancer.

GOVERNANCE CONSIDERATIONS:

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are joint Data Controllers.

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are founding members of DATA-CAN along with:

• UCL Partners

• Queen’s University, Belfast

• Genomics England

• IQVIA

DATA-CAN funding pays for staffing posts with founding member organisations. Acting as agents of their substantive employers, postholders have freedom to identify, plan, refine and assign work packages in support of DATA-CAN’s aims such as those to be undertaken in the SDE. All decisions concerning the purpose for and manner of processing personal data as described in this Agreement have been taken by employees of the University of Leeds and of the Leeds Teaching Hospitals NHS Trust.

The SDE will be accessed by and data will be processed by substantive employees of the Data Controllers and those under honorary contractual arrangements with the Data Controller/s. No other collaborators have involvement either in capacity as a data controller or processor.

While UCL Partners are the legal vehicle for the DATA-CAN hub, they do not have the work force for, or track record of, data analysis or data management. In accordance with the DATA-CAN consortium agreement the main data analyst resource is concentrated in Leeds and Belfast partner organisations. Under this Agreement, the Belfast partner organisation, Queens University, Belfast, has no involvement either in capacity as a data controller or processor.

The lawful basis for processing personal data under the UK GDPR is:

Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is:

Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

DATA REQUIREMENTS:

These analyses require access to linked data from the personal demographic service, primary care, hospital emergency, inpatient and outpatient care, intensive care, registered deaths by cause, cancer registries and COVID-19 laboratory testing. All data will be accessed by named, approved researchers (certified to have successfully completed safe researcher training) in the SDE within NHS England.

The data within the SDE will be pseudonymised. NHS England will strip identifiers from each record, apply a pseudo-ID to each record and perform the data linkage. No identifiable data will be accessible within the SDE.

The following linked datasets will be required for the purposes of this programme of work:

1. COVID-19 Second Generation Surveillance System (Beta version)

2. COVID-19 UK Non-hospital Antigen Testing Results (pillar 2) Service Types

3. CHESS: COVID-19 Hospitalisation in England Surveillance System

These datasets will provide details of COVID-19 test results and acute hospitalisations from COVID-19. These datasets will be used to ascertain all cases with proven SARS-CoV2 infection and to provide information on the severity and treatments of people with COVID-19.

Linkage of these data to data on hospitalisations, intensive care and mortality will be used to indicate the severity of COVID-19 disease. Data across all datasets should include information on patients who died prior to 2020 to all comparison of medical histories and mortality associated with a range of conditions prior to, during and – in due course – after the COVID-19 pandemic.

4. National Cancer Registration Dataset (NCRD)

5. Rapid Cancer Registration dataset

6. Systemic Anti-Cancer Therapy (SACT)

7. Radiotherapy Dataset (RTDS)

8. National Cancer Waiting Times (CWT)

These datasets will provide details of urgent cancer referrals including cancer waiting lists; details of surgeries and treatments including radiotherapy and chemotherapy including treatments within a clinical trial.

9. Civil Registration Mortality data

This dataset will provide survival data. Mortality data are needed to provide information on dates and underlying and contributing causes of death as part of the assessment of the severity of the COVID-19 disease and its impact on cancer.

10. Hospital Episode Statistics (HES) Admitted Patient Care

12. HES Outpatient

13. HES Accident & Emergency

14. Uncurated Low Latency Hospital Data Set - Emergency Care

15. GPES Data for Pandemic Planning and Research (GDPPR)

16. Medicines dispensed in Primary Care (NHS BSA data)

These datasets will provide details of patients’ prior medical history (co-morbidities); details of hospital attendances for cancer conditions before, during and (in due course) after the COVID-19 emergency, and information needed to assess other risk factors (age, sex, ethnicity, socioeconomic status, obesity, high blood pressure, high cholesterol, diabetes, etc.) and prescribed medications for those who have and have not gone on to develop COVID-19 disease with varying levels of severity.

The above data will be minimised to:

- only include those datasets required to address the cancer-related questions included within the Agreement;

- only for cancer-related research purposes, as outlined in the proposal;

- have a “per project” basis (by dataset, by year, and by “groups” of fields rather than individual fields)

- only be included if they are urgent or do not require data minimisation beyond minimisation at the dataset level (as an interim measure until these data minimisation techniques can be applied).

Some analyses based on primary care data will require analysis at the level of individual GP practices. For example, this will be required for work package 2.5, which aims to use practice prescribing preferences as an instrumental variable to assess the potential effects of different antihypertensive medications on outcomes of COVID-19. However, by default, no individual practice or health service practitioner will be identified in any research output. Should any research project be proposed that would require the identification of individual practices, researchers would seek guidance from NHS England and their GP advisory group about any issues that this might raise (for example, the potential identification of practitioners in single-handed practices) and how these should be addressed.

Uncurated Low Latency Hospital Data Set - Emergency Care is requested under this agreement as a tactical version of the Emergency Care Dataset (ECDS) as the full ECDS dataset is currently unavailable. ECDS data is included in this version of the agreement so that once the full version of the dataset is available, it can be provided via the SDE.

The outputs of each piece of work will be reported to the Scientific Advisory Group for Emergencies (SAGE) and equivalent bodies in the devolved nations so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs will also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK. Outputs will inform the clinical management of patients with different types of cancer presenting with COVID-19 disease.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of DATA-CAN with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS England, Public Health Scotland and the SAIL Databank for Wales.

No individual practice or health service practitioner will be identified in any research output.

Due to technical issues with the cancer data, it is expected that outputs will start to emerge within weeks of data becoming available to the research team and will continue to be produced throughout the period of the project through to April 2025. By their nature, those outputs providing information on the longer term impacts and implications of these for clinical care and public health policy will take at least several months from the availability of data to start emerging.

No outputs have been generated as yet due to technical issues with the cancer data and it is hoped to be able to achieve these over the next 12 months.

Data was received in March 2022 and this has enabled collaboration between DATA-CAN and NHS England to develop looking at areas such as data quality, metadata and data dictionaries, as well as exploring how the SDE can be refined to suit the needs of the various users, including DATA-CAN.

Research has begun on the five work packages described in the objectives section of this DSA, with the cancer datasets released in March 2022 proving particularly helpful. The first publication linked to work package 2.1 looking at the indirect impact of Covid-19 on cancer, was due in June 2022. Unfortunately, this deadline was not met due to delays in accessing some of the cancer data. This is ongoing and hoped to be achieved within the next 6 months. To date, it has not been possible to complete the work packages outlined within this agreement as a result of the technical issues with the data.

This extension to the agreement will enable work to continue in supporting quality check work within the SDE and also so that, once the data quality is right, work can progress within the specified work packages.

The COVID-19 pandemic has been a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years.

During the first wave of the pandemic dramatic reductions were detected in the demand for, and supply of, cancer services which did not fully recover prior to the arrival of the COVID-19 second wave. These may contribute, to substantial excess mortality among people with cancer and multi-morbidity. It is a matter of great urgency to understand how the recovery of general practitioner, oncology and other hospital services might best mitigate these long-term excess mortality risks

The indirect impacts on the presentation, diagnosis, management and prognosis of cancer resulting from the response by governments and health services to the COVID-19 pandemic also need to be examined. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between regions), effects on different in- and out-patient services and treatments, and changes over time in response to mitigating actions (e.g. regional and national government advice), is urgently needed to inform government and NHS policy.

Under this Agreement, the University of Leeds and Leeds Teaching Hospitals NHS Foundation Trust (LTHT) will use the Secure Data Environment (SDE) service for England to enable analyses of linked, nationally collated healthcare datasets to enumerate the impact of COVID-19 on cancer pathways. The research questions will delineate the precise impact of the COVID-19 pandemic on cancer systems and cancer patients. This requires access to both historical data (pre-2020) and near real-time data on patients referred with (i) a suspicion of cancer and (ii) those diagnosed with and/or managed for cancer.

The specific aims are to examine the effects of COVID-19 on:

• Cancer referral (including those which lead to a cancer diagnosis and those where cancer is excluded);

• Cancer diagnosis (including date, tumour site, stage, grade, morphology and key molecular/genetic/ phenotype);

• Cancer treatment (including surgical procedures, chemotherapy/targeted therapy and radiotherapy);

• Clinical trial activity including recruitment to and active treatment within trials;

• Outcomes (including both hospital admission, survival, mortality and cause of death) and;

• COVID status (including COVID testing (Pillar 1&2) and results, acute hospitalisation and related direct COVID deaths in cancer patients).

• Rates of COVID infection, hospitalisation and death in discrete health care regions.

The processing of data for this study is a task of public interest. The University of Leeds and Leeds Teaching Hospitals NHS Trust are Data Controllers and process data under the legal basis of Article 6(1)(e) ‘processing is necessary for the performance of a task in the public interest and processes special category data under Article 9(2)(j) ‘processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes…’ as the data are required for research purposes in the public interest and judged subject to the appropriate safeguards.

This programme requires access to both historical data (pre 2020) and near real-time data on patients referred with

(i) a suspicion of cancer and

(ii) those diagnosed with and/or managed for cancer.

A comparison of activity from 2019 and 2020 will include patients diagnosed with cancer at any time before then. A maximum of 10 years data prior to 2020 will be worked on to enable cancer survival analyses at 1, 2, 5 and 10 year intervals. These are the standard research mortality statistics.

The work is organised into work packages (WPs) and led by representatives of DATA-CAN employed by either the University of Leeds or LTHT. Each work package is considered by the members of DATA-CAN’s Management group for scientific and clinical ratification. The Management group includes a Patient and Public Involvement and Engagement (PPIE) Lead. This group will give independent advice to the work package lead. Once finalised, the work package will be assigned to an approved individual with relevant expertise to undertake the work in the SDE.

PPIE involvement will be embedded throughout all activities, as this is a core way of working for DATA-CAN.

For instance, across DATA-CAN there has been PPIE representation in the selection and interview panels for the Chief Operating Officer, in every proposal or approach received from commercial organisations, in the development and uses of real-time data (for instance in the Covid-19 and cancer work), at all management groups and at all Steering Groups. DATA-CAN’s PPIE members have also undertaken in-depth work looking at the “value” of several large-scale organisations. To ensure PPIE members are supported and play a full and active part in all DATA-CAN activities, they are provided with in-depth training on “patient data” including 1:1 mentorship, 2-weekly data-drop-in sessions, a set of bespoke learning resources, plus direct access to the PPIE Lead for advice at any time.

In respect of DATA-CAN’s use of NHS England's SDE, some specific areas where patients will be represented by the PPIE group are in :

• The operational processes of running the SDE, including safeguards, controls audits and transparency.

• Reviewing any application to utilise the data in the SDE, including making sure that the application is clearly understandable and has clear potential for patient benefit.

• Reviewing or producing lay summaries of the activity of the SDE, including website content and external communications.

• Mapping out the optimal routes for dissemination for patient benefit, rather than just relying on publication in academic journals. This will include an up-front communications plan for different pieces of work, co-designed with the PPIE group, ensuring results are disseminated and promoted to a lay audience, encouraging them to use this information further.

• PPIE members have a real interest in impact, rather than just the “doing” of the research. They are mapping the “reach” of current PPIE group members, recognising many of them will also be involved with other local and national work, or with charities. DATA-CAN’s philosophy is to utilise those links/voices to ensure results are communicated out widely, ensuring a greater awareness and understanding of the work of the SDE.

• Working with the DATA-CAN Communications team, ensure the best use of social media to advertise the work of the SDE, the outcomes of any results, and the implications for the NHS and patients (current and future).

• Contributing to the production of a lay-accessible annual patient report, which will describe the work of the overall programme, including the activity and outputs of the SDE, with details of the benefits of the work which has been produced.

• Supporting the work of the use MY data patient movement, which operates independently from DATA-CAN. Their communication routes can be seen, through their Newsletter and other means, as another mechanism to communicate with a wider group.

• Lastly, the PPIE group will play a leading role in communications through media and third sector organisations by co-authoring lay summaries or case studies, by providing patient quotations in press releases, and potentially by engaging directly with the media.

A Scientific Steering Group (SSG) has been set up by DATA-CAN specifically for the SDE. All of the above elements of the PPIE group apply to this SSG. The SSG is chaired by the Scientific Director of DATA-CAN and has representation from the HRDUK research community, the National Disease Registration Service (formerly of PHE, now NHS England) and senior representation from UK-wide data research.

All purposes for which the data will be used will be reviewed and given favourable recommendation by the SSG.

The following work packages (WP) have been identified and ratified by the process described above:

WP 1 – Coordination (led by DATA-CAN):

This work package aims to identify relevant datasets and required dataset linkages across the UK; to coordinate applications for relevant research group access for work packages if not being conducted by DATA-CAN partners, and to coordinate specialist inputs from the oncology community and other relevant clinical groups. Work is ongoing across all four nations to identify and assemble the relevant national datasets, enable their linkage, agree mechanisms for regular updates and establish routes for expedited approval and access for approved researchers within trusted research environments in each of the four nations.

WP 2 - Analyses:

This work package aims to refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses. Analyses based on routinely collected, national healthcare datasets have the advantages of large scale and comprehensive coverage, maximising statistical power as well as inclusiveness/representativeness (e.g. across all age groups, ethnicities, geographies and socioeconomic settings).

WP 3 - Public, patient and professional involvement and communications:

Work DATA-CAN Patient, Public, Involvement and Engagement group and other PPIE panels/ professionals to provide input into refining questions, assessing the impact of the results, and preparing reports for lay audiences. Lead on communications of activity and emerging results through websites, social media and other outlets. Lead on interactions with press and other media.

These work packages relate to the use of data in the SDE in the following ways:

- WP1 has led to the identification of and aspiration to access the datasets via the SDE under this Agreement for the purposes described under WP 2.

- WP2 has yielded a number of planned analyses to be undertaken within the SDE. Those that have been planned via this process so far are described below as indicative examples to give insight into the work that will be undertaken under this Agreement. However, during the course of this Agreement, WP2 will yield additional analysis plans as new questions emerge and will go through the same ratification process prior to being assigned and undertaken.

- WP3 will focus on the outputs of WP2 including the outputs of analyses undertaken using the data in the SDE.

The following are examples of analysis plans which will be undertaken using the data in the SDE under WP2:

• WP 2.1 - Indirect impact of COVID-19 on cancer:

An analysis of time trends in hospital activity (admissions by diagnosis, treatments, procedures) using hospital and disease audit datasets, registered deaths by cause and primary care activity before, during and after COVID-19 pandemic. An immediate priority for informing government policy across the UK is to assess the indirect impact of COVID-19 on cancer. Analysis will address trends in cancer referral and diagnosis before and during the COVID-19 pandemic in England and will be extended to incorporate data from the other UK nations (Scotland, Wales and Northern Ireland) when it becomes available.

• WP 2.2 - Influence/associations of cancer on COVID-19 outcomes (such as admissions to hospital, admission to ITU, mechanical ventilation and death):

The influence/associations of pre-existing cancer diagnosis on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on previous medical history with COVID-19 test results, hospitalisation, critical care and mortality datasets, with adjustment for multiple confounders (including risk factors and co-morbidities).

• WP 2.3 - Influence/associations of cancer risk factors on COVID-19 outcomes:

The influence/associations of cancer risk factors on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on cancer risk factors such as blood pressure, body mass index and smoking status with COVID-19 tests, hospitalisation, critical care and mortality datasets, with adjustment for multiple co-morbidities.

• WP 2.4 - Influence/associations of cancer medications on COVID-19 outcomes:

This package will provide information to enable government agencies (e.g., MHRA and NICE) to give evidence-based advice to healthcare professionals and patients on drug regimens and risk of COVID-19. Impact of the NICE COVID interim treatment regimens on COVID-19 outcomes (hospitalisation, admission to ICU, mechanical ventilation and mortality).

• WP 2.5 - Direct impact of COVID-19 disease on cancer disease occurrence, re-occurrence and outcomes in short, medium and long term:

Linkage of population routine datasets (demography including mortality, primary care, hospital) and audit datasets will enable comprehensive assessment of the impact of COVID-19 disease on cancer occurrence, reoccurrence and outcomes in short, medium and long term. With SARS-CoV2 potentially circulating for at least several years in the population, it will be important to estimate the short-, medium- and long-term effects of infection on incidence of cancer.

GOVERNANCE CONSIDERATIONS:

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are joint Data Controllers.

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are founding members of DATA-CAN along with:

• UCL Partners

• Queen’s University, Belfast

• Genomics England

• IQVIA

DATA-CAN funding pays for staffing posts with founding member organisations. Acting as agents of their substantive employers, postholders have freedom to identify, plan, refine and assign work packages in support of DATA-CAN’s aims such as those to be undertaken in the SDE. All decisions concerning the purpose for and manner of processing personal data as described in this Agreement have been taken by employees of the University of Leeds and of the Leeds Teaching Hospitals NHS Trust.

The SDE will be accessed by and data will be processed by substantive employees of the Data Controllers and those under honorary contractual arrangements with the Data Controller/s. No other collaborators have involvement either in capacity as a data controller or processor.

While UCL Partners are the legal vehicle for the DATA-CAN hub, they do not have the work force for, or track record of, data analysis or data management. In accordance with the DATA-CAN consortium agreement the main data analyst resource is concentrated in Leeds and Belfast partner organisations. Under this Agreement, the Belfast partner organisation, Queens University, Belfast, has no involvement either in capacity as a data controller or processor.

The lawful basis for processing personal data under the UK GDPR is:

Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is:

Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

DATA REQUIREMENTS:

These analyses require access to linked data from the personal demographic service, primary care, hospital emergency, inpatient and outpatient care, intensive care, registered deaths by cause, cancer registries and COVID-19 laboratory testing. All data will be accessed by named, approved researchers (certified to have successfully completed safe researcher training) in the SDE within NHS England.

The data within the SDE will be pseudonymised. NHS England will strip identifiers from each record, apply a pseudo-ID to each record and perform the data linkage. No identifiable data will be accessible within the SDE.

The following linked datasets will be required for the purposes of this programme of work:

1. COVID-19 Second Generation Surveillance System (Beta version)

2. COVID-19 UK Non-hospital Antigen Testing Results (pillar 2) Service Types

3. CHESS: COVID-19 Hospitalisation in England Surveillance System

These datasets will provide details of COVID-19 test results and acute hospitalisations from COVID-19. These datasets will be used to ascertain all cases with proven SARS-CoV2 infection and to provide information on the severity and treatments of people with COVID-19.

Linkage of these data to data on hospitalisations, intensive care and mortality will be used to indicate the severity of COVID-19 disease. Data across all datasets should include information on patients who died prior to 2020 to all comparison of medical histories and mortality associated with a range of conditions prior to, during and – in due course – after the COVID-19 pandemic.

4. National Cancer Registration Dataset (NCRD)

5. Rapid Cancer Registration dataset

6. Systemic Anti-Cancer Therapy (SACT)

7. Radiotherapy Dataset (RTDS)

8. National Cancer Waiting Times (CWT)

These datasets will provide details of urgent cancer referrals including cancer waiting lists; details of surgeries and treatments including radiotherapy and chemotherapy including treatments within a clinical trial.

9. Civil Registration Mortality data

This dataset will provide survival data. Mortality data are needed to provide information on dates and underlying and contributing causes of death as part of the assessment of the severity of the COVID-19 disease and its impact on cancer.

10. Hospital Episode Statistics (HES) Admitted Patient Care

12. HES Outpatient

13. HES Accident & Emergency

14. Uncurated Low Latency Hospital Data Set - Emergency Care

15. GPES Data for Pandemic Planning and Research (GDPPR)

16. Medicines dispensed in Primary Care (NHS BSA data)

These datasets will provide details of patients’ prior medical history (co-morbidities); details of hospital attendances for cancer conditions before, during and (in due course) after the COVID-19 emergency, and information needed to assess other risk factors (age, sex, ethnicity, socioeconomic status, obesity, high blood pressure, high cholesterol, diabetes, etc.) and prescribed medications for those who have and have not gone on to develop COVID-19 disease with varying levels of severity.

The above data will be minimised to:

- only include those datasets required to address the cancer-related questions included within the Agreement;

- only for cancer-related research purposes, as outlined in the proposal;

- have a “per project” basis (by dataset, by year, and by “groups” of fields rather than individual fields)

- only be included if they are urgent or do not require data minimisation beyond minimisation at the dataset level (as an interim measure until these data minimisation techniques can be applied).

Some analyses based on primary care data will require analysis at the level of individual GP practices. For example, this will be required for work package 2.5, which aims to use practice prescribing preferences as an instrumental variable to assess the potential effects of different antihypertensive medications on outcomes of COVID-19. However, by default, no individual practice or health service practitioner will be identified in any research output. Should any research project be proposed that would require the identification of individual practices, researchers would seek guidance from NHS England and their GP advisory group about any issues that this might raise (for example, the potential identification of practitioners in single-handed practices) and how these should be addressed.

Uncurated Low Latency Hospital Data Set - Emergency Care is requested under this agreement as a tactical version of the Emergency Care Dataset (ECDS) as the full ECDS dataset is currently unavailable. ECDS data is included in this version of the agreement so that once the full version of the dataset is available, it can be provided via the SDE.

The outputs of each piece of work will be reported to the Scientific Advisory Group for Emergencies (SAGE) and equivalent bodies in the devolved nations so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs will also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK. Outputs will inform the clinical management of patients with different types of cancer presenting with COVID-19 disease.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of DATA-CAN with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS England, Public Health Scotland and the SAIL Databank for Wales.

No individual practice or health service practitioner will be identified in any research output.

Due to technical issues with the cancer data, it is expected that outputs will start to emerge within weeks of data becoming available to the research team and will continue to be produced throughout the period of the project through to April 2025. By their nature, those outputs providing information on the longer term impacts and implications of these for clinical care and public health policy will take at least several months from the availability of data to start emerging.

No outputs have been generated as yet due to technical issues with the cancer data and it is hoped to be able to achieve these over the next 12 months.

Data was received in March 2022 and this has enabled collaboration between DATA-CAN and NHS England to develop looking at areas such as data quality, metadata and data dictionaries, as well as exploring how the SDE can be refined to suit the needs of the various users, including DATA-CAN.

Research has begun on the five work packages described in the objectives section of this DSA, with the cancer datasets released in March 2022 proving particularly helpful. The first publication linked to work package 2.1 looking at the indirect impact of Covid-19 on cancer, was due in June 2022. Unfortunately this deadline was not met due to delays in accessing some of the Cancer data, this is ongoing and hoped to be achieved within the next 6 months. To date, it has not been possible to complete the work packages outlined within this agreement as a result of the technical issues with the data.

This extension to the agreement will enable work to continue in supporting quality check work within the SDE and also so that, once the data quality is right, work can progress within the specified work packages.

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years.

During the first wave of the pandemic dramatic reductions were detected in the demand for, and supply of, cancer services which did not fully recover prior to the arrival of the COVID-19 second wave. These may contribute, to substantial excess mortality among people with cancer and multimorbidity. It is a matter of great urgency to understand how the recovery of general practitioner, oncology and other hospital services might best mitigate these long-term excess mortality risks

The indirect impacts on the presentation, diagnosis, management and prognosis of cancer resulting from the response by governments and health services to the COVID-19 pandemic also need to be examined. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between regions), effects on different in- and out-patient services and treatments, and changes over time in response to mitigating actions (e.g. regional and national government advice), is urgently needed to inform government and NHS policy.

Under this Agreement, the University of Leeds and Leeds Teaching Hospitals NHS Foundation Trust (LTHT) will use the Cancer Trusted Research Environment (TRE) service for England to enable analyses of linked, nationally collated healthcare datasets to enumerate the impact of COVID-19 on cancer pathways. The research questions will delineate the precise impact of the COVID-19 pandemic on cancer systems and cancer patients. This requires access to both historical data (pre-2020) and near real-time data on patients referred with (i) a suspicion of cancer and (ii) those diagnosed with and/or managed for cancer.

The specific aims are to examine the effects of COVID-19 on:

• Cancer referral (including those which lead to a cancer diagnosis and those where cancer is excluded);

• Cancer diagnosis (including date, tumour site, stage, grade, morphology and key molecular/genetic/ phenotype);

• Cancer treatment (including surgical procedures, chemotherapy/targeted therapy and radiotherapy);

• Clinical trial activity including recruitment to and active treatment within trials;

• Outcomes (including both hospital admission, survival, mortality and cause of death) and;

• COVID status (including COVID testing (Pillar 1&2) and results, acute hospitalisation and related direct COVID deaths in cancer patients).

• Rates of COVID infection, hospitalisation and death in discrete health care regions.

The processing of data for this study is a task of public interest. The University of Leeds and Leeds Teaching Hospitals NHS Trust are Data Controllers and process data under the legal basis of Article 6(1)(e) ‘processing is necessary for the performance of a task in the public interest and processes special category data under Article 9(2)(j) ‘processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes…’ as the data are required for research purposes in the public interest and judged subject to the appropriate safeguards.

This programme requires access to both historical data (pre 2020) and near real-time data on patients referred with (i) a suspicion of cancer and (ii) those diagnosed with and/or managed for cancer. A comparison of activity from 2019 and 2020 will be undertaken but this will include patients diagnosed with cancer at any time before then. A maximum of 10 years data prior to 2020 would be required to enable cancer survival analyses at 1, 2, 5 and 10 year intervals. These are the standard research mortality statistics.

The work would be organised into work packages (WPs) to be led by representatives of DATA-CAN employed by either the University of Leeds or LTHT. Each work package is considered by the members of DATA-CAN’s Management group for scientific and clinical ratification. The Management group includes a Patient and Public Involvement and Engagement (PPIE) Lead. This group will give independent advice to the work package lead. Once finalised, the work package will be assigned to an approved individual with relevant expertise to undertake the work in the Cancer TRE.

PPIE involvement will be embedded throughout all activities, as this is a core way of working for DATA-CAN.

For instance, across DATA-CAN there has been PPIE representation in the selection and interview panels for the Chief Operating Officer, in every proposal or approach received from commercial organisations, in the development and uses of real-time data (for instance in the Covid-19 and cancer work), at all management groups and at all Steering Groups. DATA-CAN’s PPIE members have also undertaken in-depth work looking at the “value” of several large-scale organisations. To ensure PPIE members are supported and play a full and active part in all DATA-CAN activities, they are provided with in-depth training on “patient data” including 1:1 mentorship, 2-weekly data-drop-in sessions, a set of bespoke learning resources, plus direct access to the PPIE Lead for advice at any time.

In respect of DATA-CAN’s use of NHS Digital’s Cancer TRE, some specific areas some specific areas where patients will be represented by the PPIE group are in :

• The operational processes of running the TRE, including safeguards, controls audits and transparency.

• Reviewing any application to utilise the data in the TRE, including making sure that the application is clearly understandable and has clear potential for patient benefit.

• Reviewing or producing lay summaries of the activity of the TRE, including website content and external communications.

• Mapping out the optimal routes for dissemination for patient benefit, rather than just relying on publication in academic journals. This will include an up-front communications plan for different pieces of work, co-designed with the PPIE group, ensuring results are disseminated and promoted to a lay audience, encouraging them to use this information further.

• PPIE members have a real interest in impact, rather than just the “doing” of the research. They are mapping the “reach” of current PPIE group members, recognising many of them will also be involved with other local and national work, or with charities. DATA-CAN’s philosophy is to utilise those links/voices to ensure results are communicated out widely, ensuring a greater awareness and understanding of the work of the TRE.

• Working with the DATA-CAN Communications team, ensure the best use of social media to advertise the work of the TRE, the outcomes of any results, and the implications for the NHS and patients (current and future).

• Contributing to the production of a lay-accessible annual patient report, which will describe the work of the overall programme, including the activity and outputs of the TRE, with details of the benefits of the work which has been produced.

• Supporting the work of the use MY data patient movement, which operates independently from DATA-CAN. Their communication routes can be seen, through their Newsletter and other means, as another mechanism to communicate with a wider group.

• Lastly, the PPIE group will play a leading role in communications through media and third sector organisations by co-authoring lay summaries or case studies, by providing patient quotations in press releases, and potentially by engaging directly with the media.

A Scientific Steering Group (SSG) has been set up by DATA-CAN specifically for the national cancer TRE. All of the above elements of the PPIE group apply to this SSG. The SSG is chaired by the Scientific Director of DATA-CAN and has representation from the HRDUK research community, the National Disease Registration Service (formerly of PHE, now NHS Digital) and senior representation from UK-wide data research.

All purposes for which the data will be used will be reviewed and given favourable recommendation by the SSG.

The following work packages (WP) have been identified and ratified by the process described above:

WP 1 – Coordination (led by DATA-CAN):

This work package aims to identify relevant datasets and required dataset linkages across the UK; to coordinate applications for relevant research group access for work packages if not being conducted by DATA-CAN partners, and to coordinate specialist inputs from the oncology community and other relevant clinical groups. Work is ongoing across all four nations to identify and assemble the relevant national datasets, enable their linkage, agree mechanisms for regular updates and establish routes for expedited approval and access for approved researchers within trusted research environments in each of the four nations.

WP 2 - Analyses:

This work package aims to refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses. Analyses based on routinely collected, national healthcare datasets have the advantages of large scale and comprehensive coverage, maximising statistical power as well as inclusiveness/representativeness (e.g. across all age groups, ethnicities, geographies and socioeconomic settings).

WP 3 - Public, patient and professional involvement and communications:

Work DATA-CAN Patient, Public, Involvement and Engagement group and other PPIE panels/ professionals to provide input into refining questions, assessing the impact of the results, and preparing reports for lay audiences. Lead on communications of activity and emerging results through websites, social media and other outlets. Lead on interactions with press and other media.

These work packages relate to the use of data in the TRE in the following ways:

- WP1 has led to the identification of and aspiration to access the datasets via the TRE under this Agreement for the purposes described under WP 2.

- WP2 has yielded a number of planned analyses to be undertaken within the TRE. Those that have been planned via this process so far are described below as indicative examples to give insight into the work that will be undertaken under this Agreement. However, during the course of this Agreement, WP2 will yield additional analysis plans as new questions emerge and will go through the same ratification process prior to being assigned and undertaken.

- WP3 will focus on the outputs of WP2 including the outputs of analyses undertaken using the data in the TRE.

The following are examples of analysis plans which will be undertaken using the data in the TRE under WP2:

• WP 2.1 - Indirect impact of COVID-19 on cancer:

An analysis of time trends in hospital activity (admissions by diagnosis, treatments, procedures) using hospital and disease audit datasets, registered deaths by cause and primary care activity before, during and after COVID-19 pandemic. An immediate priority for informing government policy across the UK is to assess the indirect impact of COVID-19 on cancer. Analysis will address trends in cancer referral and diagnosis before and during the COVID-19 pandemic in England and will be extended to incorporate data from the other UK nations (Scotland, Wales and Northern Ireland) when it becomes available.

• WP 2.2 - Influence/associations of cancer on COVID-19 outcomes (such as admissions to hospital, admission to ITU, mechanical ventilation and death):

The influence/associations of pre-existing cancer diagnosis on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on previous medical history with COVID-19 test results, hospitalisation, critical care and mortality datasets, with adjustment for multiple confounders (including risk factors and co-morbidities).

• WP 2.3 - Influence/associations of cancer risk factors on COVID-19 outcomes:

The influence/associations of cancer risk factors on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on cancer risk factors such as blood pressure, body mass index and smoking status with COVID-19 tests, hospitalisation, critical care and mortality datasets, with adjustment for multiple co-morbidities.

• WP 2.4 - Influence/associations of cancer medications on COVID-19 outcomes:

This package will provide information to enable government agencies (e.g., MHRA and NICE) to give evidence-based advice to healthcare professionals and patients on drug regimens and risk of COVID-19. Impact of the NICE COVID interim treatment regimens on COVID-19 outcomes (hospitalisation, admission to ICU, mechanical ventilation and mortality).

• WP 2.5 - Direct impact of COVID-19 disease on cancer disease occurrence, re-occurrence and outcomes in short, medium and long term:

Linkage of population routine datasets (demography including mortality, primary care, hospital) and audit datasets will enable comprehensive assessment of the impact of COVID-19 disease on cancer occurrence, reoccurrence and outcomes in short, medium and long term. With SARS-CoV2 potentially circulating for at least several years in the population, it will be important to estimate the short-, medium- and long-term effects of infection on incidence of cancer.

Governance Considerations:

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are joint Data Controllers.

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are founding members of DATA-CAN along with:

• UCLPartners

• Queen’s University, Belfast

• Genomics England

• IQVIA

DATA-CAN funding pays for staffing posts with founding member organisations. Acting as agents of their substantive employers, postholders have freedom to identify, plan, refine and assign work packages in support of DATA-CAN’s aims such as those to be undertaken in the Cancer TRE. All decisions concerning the purpose for and manner of processing personal data as described in this Agreement have been taken by employees of the University of Leeds and of the Leeds Teaching Hospitals NHS Trust.

The TRE will be accessed by and data will be processed by substantive employees of the Data Controllers and those under honorary contractual arrangements with the Data Controller/s. No other collaborators have involvement either in capacity as a data controller or processor.

While UCLPartners are the legal vehicle for the DATA-CAN hub, they do not have the work force for, or track record of, data analysis or data management. In accordance with the DATA-CAN consortium agreement the main data analyst resource is concentrated in Leeds and Belfast partner organisations. Under this Agreement, the Belfast partner organisation, Queens University, Belfast, has no involvement either in capacity as a data controller or processor.

The lawful basis for processing personal data under the UK GDPR is:

Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is:

Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

Data Requirements:

These analyses require access to linked data from the personal demographic service, primary care, hospital emergency, inpatient and outpatient care, intensive care, registered deaths by cause, cancer registries and COVID-19 laboratory testing. All data will be accessed by named, approved researchers (certified to have successfully completed safe researcher training) in the Cancer TRE within NHS Digital.

The data within the TRE will be pseudonymised. NHS Digital will strip identifiers from each record, apply a pseudo-ID to each record and perform the data linkage. No identifiable data will be accessible within the TRE.

The following linked datasets will be required for the purposes of this programme of work:

1. COVID-19 Second Generation Surveillance System (Beta version)

2. COVID-19 UK Non-hospital Antigen Testing Results (pillar 2) Service Types

3. CHESS: COVID-19 Hospitalisation in England Surveillance System

These datasets will provide details of COVID-19 test results and acute hospitalisations from COVID-19. These datasets will be used to ascertain all cases with proven SARS-CoV2 infection and to provide information on the severity and treatments of people with COVID-19.

Linkage of these data to data on hospitalisations, intensive care and mortality will be used to indicate the severity of COVID-19 disease. Data across all datasets should include information on patients who died prior to 2020 to all comparison of medical histories and mortality associated with a range of conditions prior to, during and – in due course – after the COVID-19 pandemic.

4. National Cancer Registration Dataset (NCRD)

5. Rapid Cancer Registration dataset

6. Systemic Anti-Cancer Therapy (SACT)

7. Radiotherapy Dataset (RTDS)

8. National Cancer Waiting Times (CWT)

These datasets will provide details of urgent cancer referrals including cancer waiting lists; details of surgeries and treatments including radiotherapy and chemotherapy including treatments within a clinical trial.

9. Civil Registration Mortality data

This dataset will provide survival data. Mortality data are needed to provide information on dates and underlying and contributing causes of death as part of the assessment of the severity of the COVID-19 disease and its impact on cancer.

10. Hospital Episode Statistics (HES) Admitted Patient Care

12. HES Outpatient

13. HES Accident & Emergency

14. GPES Data for Pandemic Planning and Research (GDPPR)

15. Medicines dispensed in Primary Care (NHS BSA data)

These datasets will provide details of patients’ prior medical history (co-morbidities); details of hospital attendances for cancer conditions before, during and (in due course) after the COVID-19 emergency, and information needed to assess other risk factors (age, sex, ethnicity, socioeconomic status, obesity, high blood pressure, high cholesterol, diabetes, etc.) and prescribed medications for those who have and have not gone on to develop COVID-19 disease with varying levels of severity.

The above data will be minimised to:

- only include those datasets required to address the cancer-related questions included within the Agreement;

- only for cancer-related research purposes, as outlined in the proposal;

- have a “per project” basis (by dataset, by year, and by “groups” of fields rather than individual fields)

- only be included if they are urgent or do not require data minimisation beyond minimisation at the dataset level (as an interim measure until these data minimisation techniques can be applied).

Some analyses based on primary care data will require analysis at the level of individual GP practices. For example, this will be required for work package 2.5, which aims to use practice prescribing preferences as an instrumental variable to assess the potential effects of different antihypertensive medications on outcomes of COVID-19. However, by default, no individual practice or health service practitioner will be identified in any research output. Should any research project be proposed that would require the identification of individual practices, researchers would seek guidance from NHS Digital and their GP advisory group about any issues that this might raise (for example, the potential identification of practitioners in single-handed practices) and how these should be addressed.

The outputs of each piece of work will be reported to the Scientific Advisory Group for Emergencies (SAGE) and equivalent bodies in the devolved nations so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs will also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK. Outputs will inform the clinical management of patients with different types of cancer presenting with COVID-19 disease.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of DATA-CAN with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS England, Public Health Scotland and the SAIL Databank for Wales.

No individual practice or health service practitioner will be identified in any research output.

Due to technical issues with the cancer data, it is expected that outputs will start to emerge within weeks of data becoming available to the research team and will continue to be produced throughout the three-year period of the project through to January 2024. By their nature, those outputs providing information on the longer term impacts and implications of these for clinical care and public health policy will take at least several months from the availability of data to start emerging.

No outputs have been generated as yet due to technical issues with the cancer data and it is hoped to be able to to achieve these over the next 12 months.

Data was received in March 2022 and this has enabled collaboration between DATA-CAN and NHS Digital to develop looking at areas such as data quality, metadata and data dictionaries, as well as exploring how the TRE can be refined to suit the needs of the various users, including DATA-CAN.

Research has begun on the five work packages described in the objectives section of this DSA, with the cancer datasets released in March 2022 proving particularly helpful. The first publication linked to work package 2.1 looking at the indirect impact of Covid-19 on cancer, was due in June 2022 but unfortunately this deadline was not met due to delays in accessing some of the Cancer data, this is ongoing and hoped to be achieved within the next 6 months.

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years.

During the first wave of the pandemic dramatic reductions were detected in the demand for, and supply of, cancer services which did not fully recover prior to the arrival of the COVID-19 second wave. These may contribute, to substantial excess mortality among people with cancer and multimorbidity. It is a matter of great urgency to understand how the recovery of general practitioner, oncology and other hospital services might best mitigate these long-term excess mortality risks

The indirect impacts on the presentation, diagnosis, management and prognosis of cancer resulting from the response by governments and health services to the COVID-19 pandemic also need to be examined. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between regions), effects on different in- and out-patient services and treatments, and changes over time in response to mitigating actions (e.g. regional and national government advice), is urgently needed to inform government and NHS policy.

Under this Agreement, employees of the University of Leeds and Leeds Teaching Hospitals NHS Foundation Trust (LTHT) will use the Cancer Trusted Research Environment (TRE) service for England to enable analyses of linked, nationally collated healthcare datasets to enumerate the impact of COVID-19 on cancer pathways. The research questions will delineate the precise impact of the COVID-19 pandemic on cancer systems and cancer patients. This requires access to both historical data (pre-2020) and near real-time data on patients referred with (i) a suspicion of cancer and (ii) those diagnosed with and/or managed for cancer.

The specific aims are to examine the effects of COVID-19 on:

• Cancer referral (including those which lead to a cancer diagnosis and those where cancer is excluded);

• Cancer diagnosis (including date, tumour site, stage, grade, morphology and key molecular/genetic/ phenotype);

• Cancer treatment (including surgical procedures, chemotherapy/targeted therapy and radiotherapy);

• Clinical trial activity including recruitment to and active treatment within trials;

• Outcomes (including both hospital admission, survival, mortality and cause of death) and;

• COVID status (including COVID testing (Pillar 1&2) and results, acute hospitalisation and related direct COVID deaths in cancer patients).

• Rates of COVID infection, hospitalisation and death in discrete health care regions.

The processing of data for this study is a task of public interest. The University of Leeds and Leeds Teaching Hospitals NHS Trust are Data Controllers and process data under the legal basis of Article 6(1)(e) ‘processing is necessary for the performance of a task in the public interest and processes special category data under Article 9(2)(j) ‘processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes…’ as the data are required for research purposes in the public interest and judged subject to the appropriate safeguards.

This programme requires access to both historical data (pre 2020) and near real-time data on patients referred with (i) a suspicion of cancer and (ii) those diagnosed with and/or managed for cancer. A comparison of activity from 2019 and 2020 will be undertaken but this will include patients diagnosed with cancer at any time before then. A maximum of 10 years data prior to 2020 would be required to enable cancer survival analyses at 1, 2, 5 and 10 year intervals. These are the standard research mortality statistics.

The work would be organised into work packages (WPs) to be led by representatives of DATA-CAN employed by either the University of Leeds or LTHT. Each work package is considered by the members of DATA-CAN’s Management group for scientific and clinical ratification. The Management group includes a Patient and Public Involvement and Engagement (PPIE) Lead. This group will give independent advice to the work package lead. Once finalised, the work package will be assigned to an approved individual with relevant expertise to undertake the work in the Cancer TRE.

PPIE involvement will be embedded throughout all activities, as this is a core way of working for DATA-CAN.

For instance, across DATA-CAN there has been PPIE representation in the selection and interview panels for the Chief Operating Officer, in every proposal or approach received from commercial organisations, in the development and uses of real-time data (for instance in the Covid-19 and cancer work), at all management groups and at all Steering Groups. DATA-CAN’s PPIE members have also undertaken in-depth work looking at the “value” of several large-scale organisations. To ensure PPIE members are supported and play a full and active part in all DATA-CAN activities, they are provided with in-depth training on “patient data” including 1:1 mentorship, 2-weekly data-drop-in sessions, a set of bespoke learning resources, plus direct access to the PPIE Lead for advice at any time.

In respect of DATA-CAN’s use of NHS Digital’s Cancer TRE, some specific areas some specific areas where patients will be represented by the PPIE group are in :

• The operational processes of running the TRE, including safeguards, controls audits and transparency.

• Reviewing any application to utilise the data in the TRE, including making sure that the application is clearly understandable and has clear potential for patient benefit.

• Reviewing or producing lay summaries of the activity of the TRE, including website content and external communications.

• Mapping out the optimal routes for dissemination for patient benefit, rather than just relying on publication in academic journals. This will include an up-front communications plan for different pieces of work, co-designed with the PPIE group, ensuring results are disseminated and promoted to a lay audience, encouraging them to use this information further.

• PPIE members have a real interest in impact, rather than just the “doing” of the research. They are mapping the “reach” of current PPIE group members, recognising many of them will also be involved with other local and national work, or with charities. DATA-CAN’s philosophy is to utilise those links/voices to ensure results are communicated out widely, ensuring a greater awareness and understanding of the work of the TRE.

• Working with the DATA-CAN Communications team, ensure the best use of social media to advertise the work of the TRE, the outcomes of any results, and the implications for the NHS and patients (current and future).

• Contributing to the production of a lay-accessible annual patient report, which will describe the work of the overall programme, including the activity and outputs of the TRE, with details of the benefits of the work which has been produced.

• Supporting the work of the use MY data patient movement, which operates independently from DATA-CAN. Their communication routes can be seen, through their Newsletter and other means, as another mechanism to communicate with a wider group.

• Lastly, the PPIE group will play a leading role in communications through media and third sector organisations by co-authoring lay summaries or case studies, by providing patient quotations in press releases, and potentially by engaging directly with the media.

A Scientific Steering Group (SSG) has been set up by DATA-CAN specifically for the national cancer TRE. All of the above elements of the PPIE group apply to this SSG. The SSG is chaired by the Scientific Director of DATA-CAN and has representation from the HRDUK research community, the National Disease Registration Service (formerly of PHE, now NHS Digital) and senior representation from UK-wide data research.

All purposes for which the data will be used will be reviewed and given favourable recommendation by the SSG.

The following work packages (WP) have been identified and ratified by the process described above:

WP 1 – Coordination (led by DATA-CAN):

This work package aims to identify relevant datasets and required dataset linkages across the UK; to coordinate applications for relevant research group access for work packages if not being conducted by DATA-CAN partners, and to coordinate specialist inputs from the oncology community and other relevant clinical groups. Work is ongoing across all four nations to identify and assemble the relevant national datasets, enable their linkage, agree mechanisms for regular updates and establish routes for expedited approval and access for approved researchers within trusted research environments in each of the four nations.

WP 2 - Analyses:

This work package aims to refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses. Analyses based on routinely collected, national healthcare datasets have the advantages of large scale and comprehensive coverage, maximising statistical power as well as inclusiveness/representativeness (e.g. across all age groups, ethnicities, geographies and socioeconomic settings).

WP 3 - Public, patient and professional involvement and communications:

Work DATA-CAN Patient, Public, Involvement and Engagement group and other PPIE panels/ professionals to provide input into refining questions, assessing the impact of the results, and preparing reports for lay audiences. Lead on communications of activity and emerging results through websites, social media and other outlets. Lead on interactions with press and other media.

These work packages relate to the use of data in the TRE in the following ways:

- WP1 has led to the identification of and aspiration to access the datasets via the TRE under this Agreement for the purposes described under WP 2.

- WP2 has yielded a number of planned analyses to be undertaken within the TRE. Those that have been planned via this process so far are described below as indicative examples to give insight into the work that will be undertaken under this Agreement. However, during the course of this Agreement, WP2 will yield additional analysis plans as new questions emerge and will go through the same ratification process prior to being assigned and undertaken.

- WP3 will focus on the outputs of WP2 including the outputs of analyses undertaken using the data in the TRE.

The following are examples of analysis plans which will be undertaken using the data in the TRE under WP2:

• WP 2.1 - Indirect impact of COVID-19 on cancer:

An analysis of time trends in hospital activity (admissions by diagnosis, treatments, procedures) using hospital and disease audit datasets, registered deaths by cause and primary care activity before, during and after COVID-19 pandemic. An immediate priority for informing government policy across the UK is to assess the indirect impact of COVID-19 on cancer. Analysis will address trends in cancer referral and diagnosis before and during the COVID-19 pandemic in England and will be extended to incorporate data from the other UK nations (Scotland, Wales and Northern Ireland) when it becomes available.

• WP 2.2 - Influence/associations of cancer on COVID-19 outcomes (such as admissions to hospital, admission to ITU, mechanical ventilation and death):

The influence/associations of pre-existing cancer diagnosis on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on previous medical history with COVID-19 test results, hospitalisation, critical care and mortality datasets, with adjustment for multiple confounders (including risk factors and co-morbidities).

• WP 2.3 - Influence/associations of cancer risk factors on COVID-19 outcomes:

The influence/associations of cancer risk factors on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on cancer risk factors such as blood pressure, body mass index and smoking status with COVID-19 tests, hospitalisation, critical care and mortality datasets, with adjustment for multiple co-morbidities.

• WP 2.4 - Influence/associations of cancer medications on COVID-19 outcomes:

This package will provide information to enable government agencies (e.g., MHRA and NICE) to give evidence-based advice to healthcare professionals and patients on drug regimens and risk of COVID-19. Impact of the NICE COVID interim treatment regimens on COVID-19 outcomes (hospitalisation, admission to ICU, mechanical ventilation and mortality).

• WP 2.5 - Direct impact of COVID-19 disease on cancer disease occurrence, re-occurrence and outcomes in short, medium and long term:

Linkage of population routine datasets (demography including mortality, primary care, hospital) and audit datasets will enable comprehensive assessment of the impact of COVID-19 disease on cancer occurrence, reoccurrence and outcomes in short, medium and long term. With SARS-CoV2 potentially circulating for at least several years in the population, it will be important to estimate the short-, medium- and long-term effects of infection on incidence of cancer.

Governance Considerations:

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are joint Data Controllers.

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are founding members of DATA-CAN along with:

• UCLPartners

• Queen’s University, Belfast

• Genomics England

• IQVIA

DATA-CAN funding pays for staffing posts with founding member organisations. Acting as agents of their substantive employers, postholders have freedom to identify, plan, refine and assign work packages in support of DATA-CAN’s aims such as those to be undertaken in the Cancer TRE. All decisions concerning the purpose for and manner of processing personal data as described in this Agreement have been taken by employees of the University of Leeds and of the Leeds Teaching Hospitals NHS Trust.

Only the University of Leeds and Leeds Teaching Hospitals NHS Trust, who are the data controllers, and substantive employees of these organisations will have access to the record level data within the TRE. No other collaborators have involvement either in capacity as a data controller or processor.

While UCLPartners are the legal vehicle for the DATA-CAN hub, they do not have the work force for, or track record of, data analysis or data management. In accordance with the DATA-CAN consortium agreement the main data analyst resource is concentrated in Leeds and Belfast partner organisations. Under this Agreement, the Belfast partner organisation, Queens University, Belfast, has no involvement either in capacity as a data controller or processor.

The lawful basis for processing personal data under the UK GDPR is:

Article 6(1)(e) - processing is necessary for the performance of a task carried out in the public interest or in the exercise of official authority vested in the controller;

The lawful basis for processing special category data under the UK GDPR is:

Article 9(2)(j) - processing is necessary for archiving purposes in the public interest, scientific or historical research purposes or statistical purposes in accordance with Article 89(1) based on Union or Member State law which shall be proportionate to the aim pursued, respect the essence of the right to data protection and provide for suitable and specific measures to safeguard the fundamental rights and the interests of the data subject.

Data Requirements:

These analyses require access to linked data from the personal demographic service, primary care, hospital emergency, inpatient and outpatient care, intensive care, registered deaths by cause, cancer registries and COVID-19 laboratory testing. All data will be accessed by named, approved researchers (certified to have successfully completed safe researcher training) in the Cancer TRE within NHS Digital.

The data within the TRE will be pseudonymised. NHS Digital will strip identifiers from each record, apply a pseudo-ID to each record and perform the data linkage. No identifiable data will be accessible within the TRE.

The following linked datasets will be required for the purposes of this programme of work:

1. COVID-19 Second Generation Surveillance System (Beta version)

2. COVID-19 UK Non-hospital Antigen Testing Results (pillar 2) Service Types

3. CHESS: COVID-19 Hospitalisation in England Surveillance System

These datasets will provide details of COVID-19 test results and acute hospitalisations from COVID-19. These datasets will be used to ascertain all cases with proven SARS-CoV2 infection and to provide information on the severity and treatments of people with COVID-19.

Linkage of these data to data on hospitalisations, intensive care and mortality will be used to indicate the severity of COVID-19 disease. Data across all datasets should include information on patients who died prior to 2020 to all comparison of medical histories and mortality associated with a range of conditions prior to, during and – in due course – after the COVID-19 pandemic.

4. National Cancer Registration Dataset (NCRD)

5. Rapid Cancer Registration dataset

6. Systemic Anti-Cancer Therapy (SACT)

7. Radiotherapy Dataset (RTDS)

8. National Cancer Waiting Times (CWT)

These datasets will provide details of urgent cancer referrals including cancer waiting lists; details of surgeries and treatments including radiotherapy and chemotherapy including treatments within a clinical trial.

9. Civil Registration Mortality data

This dataset will provide survival data. Mortality data are needed to provide information on dates and underlying and contributing causes of death as part of the assessment of the severity of the COVID-19 disease and its impact on cancer.

10. Hospital Episode Statistics (HES) Admitted Patient Care

12. HES Outpatient

13. HES Accident & Emergency

14. GPES Data for Pandemic Planning and Research (GDPPR)

15. Medicines dispensed in Primary Care (NHS BSA data)

These datasets will provide details of patients’ prior medical history (co-morbidities); details of hospital attendances for cancer conditions before, during and (in due course) after the COVID-19 emergency, and information needed to assess other risk factors (age, sex, ethnicity, socioeconomic status, obesity, high blood pressure, high cholesterol, diabetes, etc.) and prescribed medications for those who have and have not gone on to develop COVID-19 disease with varying levels of severity.

The above data will be minimised to:

- only include those datasets required to address the cancer-related questions included within the Agreement;

- only for cancer-related research purposes, as outlined in the proposal;

- have a “per project” basis (by dataset, by year, and by “groups” of fields rather than individual fields)

- only be included if they are urgent or do not require data minimisation beyond minimisation at the dataset level (as an interim measure until these data minimisation techniques can be applied).

Some analyses based on primary care data will require analysis at the level of individual GP practices. For example, this will be required for work package 2.5, which aims to use practice prescribing preferences as an instrumental variable to assess the potential effects of different antihypertensive medications on outcomes of COVID-19. However, by default, no individual practice or health service practitioner will be identified in any research output. Should any research project be proposed that would require the identification of individual practices, researchers would seek guidance from NHS Digital and their GP advisory group about any issues that this might raise (for example, the potential identification of practitioners in single-handed practices) and how these should be addressed.

The outputs of each piece of work will be reported to the Scientific Advisory Group for Emergencies (SAGE) and equivalent bodies in the devolved nations so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs will also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK. Outputs will inform the clinical management of patients with different types of cancer presenting with COVID-19 disease.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of DATA-CAN with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS Digital, Public Health Scotland and the SAIL Databank for Wales.

No individual practice or health service practitioner will be identified in any research output.

Due to technical issues with the cancer data, it is expected that outputs will start to emerge within weeks of data becoming available to the research team and will continue to be produced throughout the three-year period of the project through to January 2024. By their nature, those outputs providing information on the longer term impacts and implications of these for clinical care and public health policy will take at least several months from the availability of data to start emerging.

No outputs have been generated as yet due to technical issues with the cancer data and it is hoped to be able to to achieve these over the next 12 months.

Data was received in March 2022 and this has enabled collaboration between DATA-CAN and NHS Digital to develop looking at areas such as data quality, metadata and data dictionaries, as well as exploring how the TRE can be refined to suit the needs of the various users, including DATA-CAN.

Research has begun on the five work packages described in the objectives section of this DSA, with the cancer datasets released in March 2022 proving particularly helpful. The first publication linked to work package 2.1 looking at the indirect impact of Covid-19 on cancer, was due in June 2022 but unfortunately this deadline was not met due to delays in accessing some of the Cancer data, this is ongoing and hoped to be achieved within the next 6 months.

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years.

During the first wave of the pandemic dramatic reductions were detected in the demand for, and supply of, cancer services which did not fully recover prior to the arrival of the COVID-19 second wave. These may contribute, over a 1-year time horizon, to substantial excess mortality among people with cancer and multimorbidity. It is a matter of great urgency to understand how the recovery of general practitioner, oncology and other hospital services might best mitigate these long-term excess mortality risks

The indirect impacts on the presentation, diagnosis, management and prognosis of cancer resulting from the response by governments and health services to the COVID-19 pandemic also need to be examined. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between regions), effects on different in- and out-patient services and treatments, and changes over time in response to mitigating actions (e.g. regional and national government advice), is urgently needed to inform government and NHS policy.

Under this Agreement, employees of the University of Leeds and Leeds Teaching Hospitals NHS Foundation Trust (LTHT) will use the Cancer Trusted Research Environment (TRE) service for England to enable analyses of linked, nationally collated healthcare datasets to enumerate the impact of COVID-19 on cancer pathways. The research questions will delineate the precise impact of the COVID-19 pandemic on cancer systems and cancer patients. This requires access to both historical data (pre-2020) and near real-time data on patients referred with (i) a suspicion of cancer and (ii) those diagnosed with and/or managed for cancer.

The specific aims are to examine the effects of COVID-19 on:

• Cancer referral (including those which lead to a cancer diagnosis and those where cancer is excluded);

• Cancer diagnosis (including date, tumour site, stage, grade, morphology and key molecular/genetic/ phenotype);

• Cancer treatment (including surgical procedures, chemotherapy/targeted therapy and radiotherapy);

• Clinical trial activity including recruitment to and active treatment within trials;

• Outcomes (including both hospital admission, survival, mortality and cause of death) and;

• COVID status (including COVID testing (Pillar 1&2) and results, acute hospitalisation and related direct COVID deaths in cancer patients).

• Rates of COVID infection, hospitalisation and death in discrete health care regions

This programme requires access to both historical data (pre 2020) and near real-time data on patients referred with (i) a suspicion of cancer and (ii) those diagnosed with and/or managed for cancer. A comparison of activity from 2019 and 2020 will be undertaken but this will include patients diagnosed with cancer at any time before then. A maximum of 10 years data prior to 2020 would be required to enable cancer survival analyses at 1, 2, 5 and 10 year intervals. These are the standard research mortality statistics.

The work would be organised into work packages (WPs) to be led by representatives of DATA-CAN employed by either the University of Leeds or LTHT. Each work package is considered by the members of DATA-CAN’s Management group for scientific and clinical ratification. The Management group includes a Patient and Public Involvement and Engagement (PPIE) Lead. This group will give independent advice to the work package lead. Once finalised, the work package will be assigned to an approved individual with relevant expertise to undertake the work in the Cancer TRE.

PPIE involvement will be embedded throughout all activities, as this is a core way of working for DATA-CAN.

For instance, across DATA-CAN have had PPIE representation in the selection and interview panels for the Chief Operating Officer, in every proposal or approach received from commercial organisations, in the development and uses of real-time data (for instance in the Covid-19 and cancer work), at all management groups and at all Steering Groups. DATA-CAN’s PPIE members have also undertaken in-depth work looking at the “value” of several large-scale organisations. To ensure PPIE members are supported and play a full and active part in all DATA-CAN activities, they are provided with in-depth training on “patient data” including 1:1 mentorship, 2-weekly data-drop-in sessions, a set of bespoke learning resources, plus direct access to the PPIE Lead for advice at any time.

In respect of DATA-CAN’s use of NHS Digital’s Cancer TRE, some specific areas where patients will be represented by the PPIE group is in:

• The operational processes of running the TRE, including safeguards, controls audits and transparency.

• Reviewing any application to utilise the data in the TRE, including making sure that the application is clearly understandable and has clear potential for patient benefit.

• Reviewing or producing lay summaries of the activity of the TRE, including website content and external communications.

• Mapping out the optimal routes for dissemination for patient benefit, rather than just relying on publication in academic journals. This will include an up-front communications plan for different pieces of work, co-designed with the PPIE group, ensuring results are disseminated and promoted to a lay audience, encouraging them to use this information further.

• PPIE members have a real interest in impact, rather than just the “doing” of the research. They are mapping the “reach” of current PPIE group members, recognising many of them will also be involved with other local and national work, or with charities. DATA-CAN’s philosophy is to utilise those links/voices to ensure results are communicated out widely, ensuring a greater awareness and understanding of the work of the TRE.

• Working with the DATA-CAN Communications team, ensure the best use of social media to advertise the work of the TRE, the outcomes of any results, and the implications for the NHS and patients (current and future).

• Contributing to the production of a lay-accessible annual patient report, which will describe the work of the overall programme, including the activity and outputs of the TRE, with details of the benefits of the work which has been produced.

• Supporting the work of the use MY data patient movement, which operates independently from DATA-CAN. Their communication routes can be seen, through their Newsletter and other means, as another mechanism to communicate with a wider group.

• Lastly, the PPIE group will play a leading role in communications through media and third sector organisations by co-authoring lay summaries or case studies, by providing patient quotations in press releases, and potentially by engaging directly with the media.

A Scientific Steering Group (SSG) has been set up by DATA-CAN specifically for the national cancer TRE. All of the above elements of the PPIE group apply to this SSG. The SSG is chaired by the Scientific Director of DATA-CAN and has representation from the HRDUK research community, the National Disease Registration Service (formerly of PHE, now NHS Digital) and senior representation from UK-wide data research.

All purposes for which the data will be used will be reviewed and given favourable recommendation by the SSG.

The following work packages (WP) have been identified and ratified by the process described above:

WP 1 – Coordination (led by DATA-CAN):

This work package aims to identify relevant datasets and required dataset linkages across the UK; to coordinate applications for relevant research group access for work packages if not being conducted by DATA-CAN partners, and to coordinate specialist inputs from the oncology community and other relevant clinical groups. Work is ongoing across all four nations to identify and assemble the relevant national datasets, enable their linkage, agree mechanisms for regular updates and establish routes for expedited approval and access for approved researchers within trusted research environments in each of the four nations.

WP 2 - Analyses:

This work package aims to refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses. Analyses based on routinely collected, national healthcare datasets have the advantages of large scale and comprehensive coverage, maximising statistical power as well as inclusiveness/representativeness (e.g. across all age groups, ethnicities, geographies and socioeconomic settings).

WP 3 - Public, patient and professional involvement and communications:

Work DATA-CAN Patient, Public, Involvement and Engagement group and other PPIE panels/ professionals to provide input into refining questions, assessing the impact of the results, and preparing reports for lay audiences. Lead on communications of activity and emerging results through websites, social media and other outlets. Lead on interactions with press and other media.

These work packages relate to the use of data in the TRE in the following ways:

- WP1 has led to the identification of and aspiration to access the datasets via the TRE under this Agreement for the purposes described under WP 2.

- WP2 has yielded a number of planned analyses to be undertaken within the TRE. Those that have been planned via this process so far are described below as indicative examples to give insight into the work that will be undertaken under this Agreement. However, during the course of this Agreement, WP2 will yield additional analysis plans as new questions emerge and will go through the same ratification process prior to being assigned and undertaken.

- WP3 will focus on the outputs of WP2 including the outputs of analyses undertaken using the data in the TRE.

The following are examples of analysis plans which will be undertaken using the data in the TRE under WP2:

• WP 2.1 - Indirect impact of COVID-19 on cancer:

An analysis of time trends in hospital activity (admissions by diagnosis, treatments, procedures) using hospital and disease audit datasets, registered deaths by cause and primary care activity before, during and after COVID-19 pandemic. An immediate priority for informing government policy across the UK is to assess the indirect impact of COVID-19 on cancer. Analysis will address trends in cancer referral and diagnosis before and during the COVID-19 pandemic in England and will be extended to incorporate data from the other UK nations (Scotland, Wales and Northern Ireland) when it becomes available.

• WP 2.2 - Influence/associations of cancer on COVID-19 outcomes (such as admissions to hospital, admission to ITU, mechanical ventilation and death):

The influence/associations of pre-existing cancer diagnosis on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on previous medical history with COVID-19 test results, hospitalisation, critical care and mortality datasets, with adjustment for multiple confounders (including risk factors and co-morbidities).

• WP 2.3 - Influence/associations of cancer risk factors on COVID-19 outcomes:

The influence/associations of cancer risk factors on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on cancer risk factors such as blood pressure, body mass index and smoking status with COVID-19 tests, hospitalisation, critical care and mortality datasets, with adjustment for multiple co-morbidities.

• WP 2.4 - Influence/associations of cancer medications on COVID-19 outcomes:

This package will provide information to enable government agencies (e.g., MHRA and NICE) to give evidence-based advice to healthcare professionals and patients on drug regimens and risk of COVID-19. Impact of the NICE COVID interim treatment regimens on COVID-19 outcomes (hospitalisation, admission to ICU, mechanical ventilation and mortality).

• WP 2.5 - Direct impact of COVID-19 disease on cancer disease occurrence, re-occurrence and outcomes in short, medium and long term:

Linkage of population routine datasets (demography including mortality, primary care, hospital) and audit datasets will enable comprehensive assessment of the impact of COVID-19 disease on cancer occurrence, reoccurrence and outcomes in short, medium and long term. With SARS-CoV2 potentially circulating for at least several years in the population, it will be important to estimate the short-, medium- and long-term effects of infection on incidence of cancer.

Governance Considerations:

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are joint Data Controllers.

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are founding members of DATA-CAN along with:

• UCLPartners

• Queen’s University, Belfast

• Genomics England

• IQVIA

DATA-CAN funding pays for staffing posts with founding member organisations. Acting as agents of their substantive employers, postholders have freedom to identify, plan, refine and assign work packages in support of DATA-CAN’s aims such as those to be undertaken in the Cancer TRE. All decisions concerning the purpose for and manner of processing personal data as described in this Agreement have been taken by employees of the University of Leeds and of the Leeds Teaching Hospitals NHS Trust.

Only the University of Leeds and Leeds Teaching Hospitals NHS Trust, who are the data controllers, and substantive employees of these organisations will have access to the record level data within the TRE. No other collaborators have involvement either in capacity as a data controller or processor.

While UCLPartners are the legal vehicle for the DATA-CAN hub, they do not have the work force for, or track record of, data analysis or data management. In accordance with the DATA-CAN consortium agreement the main data analyst resource is concentrated in Leeds and Belfast partner organisations. Under this Agreement, the Belfast partner organisation, Queens University, Belfast, has no involvement either in capacity as a data controller or processor.

The legal basis for the data controllers to process personal data is GDPR Article 6(1)(e) ‘task in the public interest’ and for processing special categories of personal data the legal basis is GDPR Article 9(2)(j) ‘archiving, research and statistics (with a basis in law)’.

Data Requirements:

These analyses require access to linked data from the personal demographic service, primary care, hospital emergency, inpatient and outpatient care, intensive care, registered deaths by cause, cancer registries and COVID-19 laboratory testing. All data will be accessed by named, approved researchers (certified to have successfully completed safe researcher training) in the Cancer TRE within NHS Digital.

The data within the TRE will be pseudonymised. NHS Digital will strip identifiers from each record, apply a pseudo-ID to each record and perform the data linkage. No identifiable data will be accessible within the TRE.

The following linked datasets will be required for the purposes of this programme of work:

1. COVID-19 Second Generation Surveillance System (Beta version)

2. COVID-19 UK Non-hospital Antigen Testing Results (pillar 2) Service Types

3. CHESS: COVID-19 Hospitalisation in England Surveillance System

These datasets will provide details of COVID-19 test results and acute hospitalisations from COVID-19. These datasets will be used to ascertain all cases with proven SARS-CoV2 infection and to provide information on the severity and treatments of people with COVID-19.

Linkage of these data to data on hospitalisations, intensive care and mortality will be used to indicate the severity of COVID-19 disease. Data across all datasets should include information on patients who died prior to 2020 to all comparison of medical histories and mortality associated with a range of conditions prior to, during and – in due course – after the COVID-19 pandemic.

4. National Cancer Registration Dataset (NCRD)

5. Rapid Cancer Registration dataset

6. Systemic Anti-Cancer Therapy (SACT)

7. Radiotherapy Dataset (RTDS)

8. National Cancer Waiting Times (CWT)

These datasets will provide details of urgent cancer referrals including cancer waiting lists; details of surgeries and treatments including radiotherapy and chemotherapy including treatments within a clinical trial.

9. Civil Registration Mortality data

This dataset will provide survival data. Mortality data are needed to provide information on dates and underlying and contributing causes of death as part of the assessment of the severity of the COVID-19 disease and its impact on cancer.

10. Secondary Uses Service (including SUS PBR for HRGs cost analysis)

11. Hospital Episode Statistics (HES) Admitted Patient Care

12. HES Outpatient

13. HES Accident & Emergency

14. Emergency Care Data Set (ECDS)

15. GPES Data for Pandemic Planning and Research (GDPPR)

16. Medicines dispensed in Primary Care (NHS BSA data)

These datasets will provide details of patients’ prior medical history (co-morbidities); details of hospital attendances for cancer conditions before, during and (in due course) after the COVID-19 emergency, and information needed to assess other risk factors (age, sex, ethnicity, socioeconomic status, obesity, high blood pressure, high cholesterol, diabetes, etc.) and prescribed medications for those who have and have not gone on to develop COVID-19 disease with varying levels of severity.

The above data will be minimised to:

- only include those datasets required to address the cancer-related questions included within the Agreement;

- only for cancer-related research purposes, as outlined in the proposal;

- have a “per project” basis (by dataset, by year, and by “groups” of fields rather than individual fields)

- only be included if they are urgent or do not require data minimisation beyond minimisation at the dataset level (as an interim measure until these data minimisation techniques can be applied).

Some analyses based on primary care data will require analysis at the level of individual GP practices. For example, this will be required for work package 2.5, which aims to use practice prescribing preferences as an instrumental variable to assess the potential effects of different antihypertensive medications on outcomes of COVID-19. However, by default, no individual practice or health service practitioner will be identified in any research output. Should any research project be proposed that would require the identification of individual practices, researchers would seek guidance from NHS Digital and their GP advisory group about any issues that this might raise (for example, the potential identification of practitioners in single-handed practices) and how these should be addressed.

The outputs of each piece of work will be reported to the Scientific Advisory Group for Emergencies (SAGE) and equivalent bodies in the devolved nations so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs will also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK. Outputs will inform the clinical management of patients with different types of cancer presenting with COVID-19 disease.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of DATA-CAN with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS Digital, Public Health Scotland and the SAIL Databank for Wales.

No individual practice or health service practitioner will be identified in any research output.

It is expected that outputs will start to emerge within weeks of data becoming available to the research team and will continue to be produced throughout the three-year period of the project through to January 2024. By their nature, those outputs providing information on the longer term impacts and implications of these for clinical care and public health policy will take at least several months to start emerging.

No data has been made available to the University of Leeds or LTHT, and as such no yielded benefits have been generated yet.

The COVID-19 pandemic is a major global challenge, whose impacts on the population’s health, healthcare systems and services and the wider economy will be apparent for many years.

During the first wave of the pandemic dramatic reductions were detected in the demand for, and supply of, cancer services which did not fully recover prior to the arrival of the COVID-19 second wave. These may contribute, over a 1-year time horizon, to substantial excess mortality among people with cancer and multimorbidity. It is a matter of great urgency to understand how the recovery of general practitioner, oncology and other hospital services might best mitigate these long-term excess mortality risks

The indirect impacts on the presentation, diagnosis, management and prognosis of cancer resulting from the response by governments and health services to the COVID-19 pandemic also need to be examined. A deeper understanding of the nature and extent of these unintended consequences, including the range of conditions affected, variation by patient characteristics (such as age, sex, ethnicity, and deprivation) and geography (both within and between regions), effects on different in- and out-patient services and treatments, and changes over time in response to mitigating actions (e.g. regional and national government advice), is urgently needed to inform government and NHS policy.

Under this Agreement, employees of the University of Leeds and Leeds Teaching Hospitals NHS Foundation Trust (LTHT) will use the Cancer Trusted Research Environment (TRE) service for England to enable analyses of linked, nationally collated healthcare datasets to enumerate the impact of COVID-19 on cancer pathways. The research questions will delineate the precise impact of the COVID-19 pandemic on cancer systems and cancer patients. This requires access to both historical data (pre-2020) and near real-time data on patients referred with (i) a suspicion of cancer and (ii) those diagnosed with and/or managed for cancer.

The specific aims are to examine the effects of COVID-19 on:

• Cancer referral (including those which lead to a cancer diagnosis and those where cancer is excluded);

• Cancer diagnosis (including date, tumour site, stage, grade, morphology and key molecular/genetic/ phenotype);

• Cancer treatment (including surgical procedures, chemotherapy/targeted therapy and radiotherapy);

• Clinical trial activity including recruitment to and active treatment within trials;

• Outcomes (including both hospital admission, survival, mortality and cause of death) and;

• COVID status (including COVID testing (Pillar 1&2) and results, acute hospitalisation and related direct COVID deaths in cancer patients).

• Rates of COVID infection, hospitalisation and death in discrete health care regions

This programme requires access to both historical data (pre 2020) and near real-time data on patients referred with (i) a suspicion of cancer and (ii) those diagnosed with and/or managed for cancer. A comparison of activity from 2019 and 2020 will be undertaken but this will include patients diagnosed with cancer at any time before then. A maximum of 10 years data prior to 2020 would be required to enable cancer survival analyses at 1, 2, 5 and 10 year intervals. These are the standard research mortality statistics.

The work would be organised into work packages (WPs) to be led by representatives of DATA-CAN employed by either the University of Leeds or LTHT. Each work package is considered by the members of DATA-CAN’s Management group for scientific and clinical ratification. The Management group includes a Patient and Public Involvement and Engagement (PPIE) Lead. This group will give independent advice to the work package lead. Once finalised, the work package will be assigned to an approved individual with relevant expertise to undertake the work in the Cancer TRE.

PPIE involvement will be embedded throughout all activities, as this is a core way of working for DATA-CAN.

For instance, across DATA-CAN have had PPIE representation in the selection and interview panels for the Chief Operating Officer, in every proposal or approach received from commercial organisations, in the development and uses of real-time data (for instance in the Covid-19 and cancer work), at all management groups and at all Steering Groups. DATA-CAN’s PPIE members have also undertaken in-depth work looking at the “value” of several large-scale organisations. To ensure PPIE members are supported and play a full and active part in all DATA-CAN activities, they are provided with in-depth training on “patient data” including 1:1 mentorship, 2-weekly data-drop-in sessions, a set of bespoke learning resources, plus direct access to the PPIE Lead for advice at any time.

In respect of DATA-CAN’s used of NHS Digital’s Cancer TRE, some specific areas where patients will be represented by the PPIE group is in:

• The operational processes of running the TRE, including safeguards, controls audits and transparency.

• Reviewing any application to utilise the data in the TRE, including making sure that the application is clearly understandable and has clear potential for patient benefit.

• Reviewing or producing lay summaries of the activity of the TRE, including website content and external communications.

• Mapping out the optimal routes for dissemination for patient benefit, rather than just relying on publication in academic journals. This will include an up-front communications plan for different pieces of work, co-designed with the PPIE group, ensuring results are disseminated and promoted to a lay audience, encouraging them to use this information further.

• PPIE members have a real interest in impact, rather than just the “doing” of the research. They are mapping the “reach” of current PPIE group members, recognising many of them will also be involved with other local and national work, or with charities. DATA-CAN’s philosophy is to utilise those links/voices to ensure results are communicated out widely, ensuring a greater awareness and understanding of the work of the TRE.

• Working with the DATA-CAN Communications team, ensure the best use of social media to advertise the work of the TRE, the outcomes of any results, and the implications for the NHS and patients (current and future).

• Contributing to the production of a lay-accessible annual patient report, which will describe the work of the overall programme, including the activity and outputs of the TRE, with details of the benefits of the work which has been produced.

• Supporting the work of the use MY data patient movement, which operates independently from DATA-CAN. Their communication routes can be seen, through their Newsletter and other means, as another mechanism to communicate with a wider group.

• Lastly, the PPIE group will play a leading role in communications through media and third sector organisations by co-authoring lay summaries or case studies, by providing patient quotations in press releases, and potentially by engaging directly with the media.

The following work packages (WP) have been identified and ratified by the process described above:

WP 1 – Coordination (led by DATA-CAN):

This work package aims to identify relevant datasets and required dataset linkages across the UK; to coordinate applications for relevant research group access for work packages if not being conducted by DATA-CAN partners, and to coordinate specialist inputs from the oncology community and other relevant clinical groups. Work is ongoing across all four nations to identify and assemble the relevant national datasets, enable their linkage, agree mechanisms for regular updates and establish routes for expedited approval and access for approved researchers within trusted research environments in each of the four nations.

WP 2 - Analyses:

This work package aims to refine questions with appropriate clinical specialist input, draw up analysis plans for different datasets (individually and linked), assess data completeness and quality, conduct analyses, interpret results, iterative reporting and refining of analyses. Analyses based on routinely collected, national healthcare datasets have the advantages of large scale and comprehensive coverage, maximising statistical power as well as inclusiveness/representativeness (e.g. across all age groups, ethnicities, geographies and socioeconomic settings).

WP 3 - Public, patient and professional involvement and communications:

Work DATA-CAN Patient, Public, Involvement and Engagement group and other PPIE panels/ professionals to provide input into refining questions, assessing the impact of the results, and preparing reports for lay audiences. Lead on communications of activity and emerging results through websites, social media and other outlets. Lead on interactions with press and other media.

These work packages relate to the use of data in the TRE in the following ways:

- WP1 has led to the identification of and aspiration to access the datasets via the TRE under this Agreement for the purposes described under WP 2.

- WP2 has yielded a number of planned analyses to be undertaken within the TRE. Those that have been planned via this process so far are described below as indicative examples to give insight into the work that will be undertaken under this Agreement. However, during the course of this Agreement, WP2 will yield additional analysis plans as new questions emerge and will go through the same ratification process prior to being assigned and undertaken.

- WP3 will focus on the outputs of WP2 including the outputs of analyses undertaken using the data in the TRE.

The following are examples of analysis plans which will be undertaken using the data in the TRE under WP2:

• WP 2.1 - Indirect impact of COVID-19 on cancer:

An analysis of time trends in hospital activity (admissions by diagnosis, treatments, procedures) using hospital and disease audit datasets, registered deaths by cause and primary care activity before, during and after COVID-19 pandemic. An immediate priority for informing government policy across the UK is to assess the indirect impact of COVID-19 on cancer. Analysis will address trends in cancer referral and diagnosis before and during the COVID-19 pandemic in England and will be extended to incorporate data from the other UK nations (Scotland, Wales and Northern Ireland) when it becomes available.

• WP 2.2 - Influence/associations of cancer on COVID-19 outcomes (such as admissions to hospital, admission to ITU, mechanical ventilation and death):

The influence/associations of pre-existing cancer diagnosis on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on previous medical history with COVID-19 test results, hospitalisation, critical care and mortality datasets, with adjustment for multiple confounders (including risk factors and co-morbidities).

• WP 2.3 - Influence/associations of cancer risk factors on COVID-19 outcomes:

The influence/associations of cancer risk factors on COVID-19 incidence and outcomes will be studied through linkage of large scale population wide datasets that contain information on cancer risk factors such as blood pressure, body mass index and smoking status with COVID-19 tests, hospitalisation, critical care and mortality datasets, with adjustment for multiple co-morbidities.

• WP 2.4 - Influence/associations of cancer medications on COVID-19 outcomes:

This package will provide information to enable government agencies (e.g., MHRA and NICE) to give evidence-based advice to healthcare professionals and patients on drug regimens and risk of COVID-19. Impact of the NICE COVID interim treatment regimens on COVID-19 outcomes (hospitalisation, admission to ICU, mechanical ventilation and mortality).

• WP 2.5 - Direct impact of COVID-19 disease on cancer disease occurrence, re-occurrence and outcomes in short, medium and long term:

Linkage of population routine datasets (demography including mortality, primary care, hospital) and audit datasets will enable comprehensive assessment of the impact of COVID-19 disease on cancer occurrence, reoccurrence and outcomes in short, medium and long term. With SARS-CoV2 potentially circulating for at least several years in the population, it will be important to estimate the short-, medium- and long-term effects of infection on incidence of cancer.

Governance Considerations:

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are joint Data Controllers.

The University of Leeds and the Leeds Teaching Hospitals NHS Trust are founding members of DATA-CAN along with:

• UCLPartners

• Queen’s University, Belfast

• Genomics England

• IQVIA

DATA-CAN funding pays for staffing posts with founding member organisations. Acting as agents of their substantive employers, postholders have freedom to identify, plan, refine and assign work packages in support of DATA-CAN’s aims such as those to be undertaken in the Cancer TRE. All decisions concerning the purpose for and manner of processing personal data as described in this Agreement have been taken by employees of the University of Leeds and of the Leeds Teaching Hospitals NHS Trust.

Only the University of Leeds and Leeds Teaching Hospitals NHS Trust, who are the data controllers, and substantive employees of these organisations will have access to the record level data within the TRE. No other collaborators have involvement either in capacity as a data controller or processor.

While UCLPartners are the legal vehicle for the DATA-CAN hub, they do not have the work force for, or track record of, data analysis or data management. In accordance with the DATA-CAN consortium agreement the main data analyst resource is concentrated in Leeds and Belfast partner organisations. Under this Agreement, the Belfast partner organisation, Queens University, Belfast, has no involvement either in capacity as a data controller or processor.

The legal basis for the data controllers to process personal data is GDPR Article 6(1)(e) ‘task in the public interest’ and for processing special categories of personal data the legal basis is GDPR Article 9(2)(j) ‘archiving, research and statistics (with a basis in law)’.

Data Requirements:

These analyses require access to linked data from the personal demographic service, primary care, hospital emergency, inpatient and outpatient care, intensive care, registered deaths by cause, cancer registries and COVID-19 laboratory testing. All data will be accessed by named, approved researchers (certified to have successfully completed safe researcher training) in the Cancer TRE within NHS Digital.

The data within the TRE will be pseudonymised. NHS Digital will strip identifiers from each record, apply a pseudo-ID to each record and perform the data linkage. No identifiable data will be accessible within the TRE.

The following linked datasets will be required for the purposes of this programme of work:

1. COVID-19 Second Generation Surveillance System (Beta version)

2. COVID-19 UK Non-hospital Antigen Testing Results (pillar 2) Service Types

3. CHESS: COVID-19 Hospitalisation in England Surveillance System

These datasets will provide details of COVID-19 test results and acute hospitalisations from COVID-19. These datasets will be used to ascertain all cases with proven SARS-CoV2 infection and to provide information on the severity and treatments of people with COVID-19.

Linkage of these data to data on hospitalisations, intensive care and mortality will be used to indicate the severity of COVID-19 disease. Data across all datasets should include information on patients who died prior to 2020 to all comparison of medical histories and mortality associated with a range of conditions prior to, during and – in due course – after the COVID-19 pandemic.

4. National Cancer Registration Dataset

5. Rapid Cancer Registration dataset

6. Systemic Anti-Cancer Therapy (SACT)

7. Radiotherapy Dataset (RTDS)

8. National Cancer Waiting Times (NCWT)

These datasets will provide details of urgent cancer referrals including cancer waiting lists; details of surgeries and treatments including radiotherapy and chemotherapy including treatments within a clinical trial.

9. Civil Registration Mortality data

This dataset will provide survival data. Mortality data are needed to provide information on dates and underlying and contributing causes of death as part of the assessment of the severity of the COVID-19 disease and its impact on cancer.

10. Secondary Uses Service (including SUS PBR for HRGs cost analysis)

11. Hospital Episode Statistics (HES) Admitted Patient Care

12. HES Outpatient

13. HES Accident & Emergency

14. Emergency Care Data Set (ECDS)

15. GPES Data for Pandemic Planning and Research (GDPPR)

16. Medicines dispensed in Primary Care (NHS BSA data)

These datasets will provide details of patients’ prior medical history (co-morbidities); details of hospital attendances for cancer conditions before, during and (in due course) after the COVID-19 emergency, and information needed to assess other risk factors (age, sex, ethnicity, socioeconomic status, obesity, high blood pressure, high cholesterol, diabetes, etc.) and prescribed medications for those who have and have not gone on to develop COVID-19 disease with varying levels of severity.

The above data will be minimised to:

- only include those datasets required to address the cancer-related questions included within the Agreement;

- only for cancer-related research purposes, as outlined in the proposal;

- have a “per project” basis (by dataset, by year, and by “groups” of fields rather than individual fields)

- only be included if they are urgent or do not require data minimisation beyond minimisation at the dataset level (as an interim measure until these data minimisation techniques can be applied).

Some analyses based on primary care data will require analysis at the level of individual GP practices. For example, this will be required for work package 2.5, which aims to use practice prescribing preferences as an instrumental variable to assess the potential effects of different antihypertensive medications on outcomes of COVID-19. However, by default, no individual practice or health service practitioner will be identified in any research output. Should any research project be proposed that would require the identification of individual practices, researchers would seek guidance from NHS Digital and their GP advisory group about any issues that this might raise (for example, the potential identification of practitioners in single-handed practices) and how these should be addressed.

The outputs of each piece of work will be reported to the Scientific Advisory Group for Emergencies (SAGE) and equivalent bodies in the devolved nations so helping to drive evidence-based policy decisions for health service providers and clinical professional groups. Outputs will also form the basis of manuscripts for publication in peer-reviewed scientific and medical journals, presentations at national and international scientific and medical professional conferences, and reports aimed at lay audiences, available through websites, in particular those of Health Data Research UK. Outputs will inform the clinical management of patients with different types of cancer presenting with COVID-19 disease.

All analysis plans, protocols and reports arising from this proposal will be made publicly available via the HDR UK website (linking to additional institutional documentation if appropriate), HDR UK github repository and open access publications. Hence all outputs will be freely available.

All reports for government advisory groups and policy makers, the lay public and academic publications will be written in the name of DATA-CAN with all relevant individual contributions (coordination, writing, analysis, interpretation etc.) listed.

Outputs will contain only aggregate data with small numbers suppressed in line with the HES analysis guidance from NHS Digital, Public Health Scotland and the SAIL Databank for Wales.

No individual practice or health service practitioner will be identified in any research output.

It is expected that outputs will start to emerge within weeks of data becoming available to the research team and will continue to be produced throughout the three-year period of the project through to January 2024. By their nature, those outputs providing information on the longer term impacts and implications of these for clinical care and public health policy will take at least several months to start emerging.

Yielded Benefits is not a requirement for new applications.