OLIVE: Improving the early detection of lung cancer in never-smokers

University College London (UCL) requires access to NHS England data for the purpose of the following research project:

OLIVE: Improving the early detection of lung cancer in never-smokers

The following is a summary of the aims of the research project provided by UCL:

Lung cancer is the second most common cancer and the biggest cause of cancer death both worldwide and in the UK. Only 39% of adults diagnosed with lung cancer survive more than one year and this is likely related to late diagnosis: half of all individuals are diagnosed with stage IV disease at presentation and a quarter are diagnosed through emergency care. Although commonly associated with smoking, lung cancer also occurs in ‘never-smokers’, or adults who have smoked less than 100 tobacco cigarettes in their lifetime. Up to 25% of lung cancer worldwide is diagnosed in never-smokers; lung cancer in never-smokers (LCINS) is the seventh most common cause of cancer death.

In the UK, people who have smoked are invited for screening with scans. However, we do not have any methods to detect lung cancer in never-smokers (LCINS) early. LCINS is generally not very well understood. If this is changed, more lives can be saved and more lives of people living with lung cancer can be improved. With the proportion of never-smokers increasing worldwide and in Europe, LCINS mortality is likely to increase further. Methods to reduce mortality are clearly needed and this is likely to be best achieved by ensuring adults are diagnosed early and at an earlier stage.

OLIVE is a PhD project with four work packages.

> WP1: A systematic review will be performed to identify and summarise factors which predict LCINS.

> WP2: Registry data will be analysed to examine the relationship between sociodemographic factors (such as gender and ethnicity) and LCINS (including outcomes like survival).

> WP3: Standard statistical and machine learning techniques in multiple datasets will be used to create and validate a risk prediction model to estimate the five-year incidence and mortality risk of LCINS.

> WP4: Machine learning will be used to review primary care data of never-smokers to identify patterns that will contribute to early diagnosis.

The NHS England Data requested under this Agreement is only required for WP2. Only aggregated results with small numbers suppressed generated from the processing of NHS England Data for WP2 may be used for the other WPs. The aim of this part of the project is to describe LCINS in the UK and the relationship between factors such as age, gender and ethnicity and LCINS.

The following NHS England Data will be accessed:

> NDRS Cancer Registration and NDRS Somatic Molecular Testing – necessary to understand important variables which may be associated with the outcomes of stage and survival from LCINS.

> NDRS Cancer Pathway - necessary to understand treatment which may affect outcomes, treatment data is required as it may be linked to survival from lung cancer.

The level of the Data will be:

> Pseudonymised

The Data will be minimised as follows :

> Limited to a study cohort identified by NHS England as meeting the following criteria:

- Inclusion Criteria

• For cases: adults over the age of 21 with a diagnosis of primary lung cancer

- Exclusion Criteria

• Adults who do not meet inclusion criteria

> Limited to data between 2015-2022.

> Limited to a diagnosis of primary lung cancer

> Limited to the following geographic areas: England.

> Data requested will be minimised to avoid any chance of re-identifiability e.g. age in years instead of birth date.

> Ethnicity will be requested as it is likely to be associated with diagnosis of and survival from lung cancer.

UCL as the research sponsor is the controller as the organisation responsible for ensuring that the Data will only be processed for the purpose described above.

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 University College London (UCL);

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.

This processing is in the public interest because it could lead to a better understanding of LCINS which could ultimately save more lives and improve the lives of people living with lung cancer.

The funding comes from multiple sources. Funders include:

> NIHR Doctoral Fellowship

> Ruth Strauss Foundation – a charity which aims to provide emotional support for families to prepare for the death of a parent and raise awareness of the need for more research & collaboration in the fight against non-smoking lung cancers.

The funding is specifically for the project described.

The funders will have no ability to suppress or otherwise limit the publication of findings.

Amazon Web Services (AWS) is the processor acting under the instructions of UCL. AWS’ role is limited to secure back-up of data stored in UCL’s Data Safe Haven.

UCL uses offsite data centre services provided by VIRTUS data centre. VIRTUS does not have access to the data.

Data will be accessed by:

- Substantive employees of UCL

- A PhD student enrolled with UCL. The individual has completed mandatory data protection and confidentiality training and is subject to UCL’s policies on data protection and confidentiality. The individual accessing the data will do so under the supervision of a substantive employee of UCL. UCL would be responsible and liable for any work carried out by the individual. The PhD student would only work on the data for the purposes described in this Data Sharing Agreement (DSA).

A Public and Patient Involvement and Engagement group helped refine the purpose of the research. The group supported the collection of the data for the purposes described above. Patients also helped to ensure that the research outcomes and variables studied are appropriate and acceptable to the public. They felt this research is important and likely to lead to meaningful change for other patients and the public. They also felt the processes, such as data storage, were acceptable and did not raise any other concerns or ethical objections. Ongoing research will be discussed to ensure it remains acceptable and gather structured feedback for change. Feedback from patient representatives has been invaluable in adapting the methods and outcomes of this research to ensure it is relevant to patients and the public. These representatives will continue to be involved to guide research and develop effective methods for implementing findings.

No data will flow to NHS England for the purposes of this Data Sharing Agreement (DSA).

NHS England will provide the relevant records from the Cancer Pathway Data, Cancer Registration Data and Somatic Molecular Data datasets to University College London (UCL). The Data will contain no direct identifying data items. The Data will be pseudonymised and individuals cannot be reidentified through linkage with other data in the possession of the recipient.

The Data will not be transferred to any other location.

The Data will be stored on servers at UCL Data Safe Haven.

UCL uses offsite data centre services provided by VIRTUS data centre.

Amazon Web Services provides cloud hosting services to UCL and will store the data as contracted by UCL.

The Data will be accessed by authorised personnel via remote access.

The Controller(s) must confirm and provide evidence upon audit by NHS England that access via any remote device complies with the data security obligations within this DSA and the Data Sharing Framework Contract.

For remote access:

- Remote access will only be from secure locations situated within the territory of use (as further restricted elsewhere within the DSA if so done) stated within this DSA;

- Access controls granting users the minimum level of access required are in place;

- Remote access is only via secure connections (e.g., VPNs or secure protocols) to protect data;

- Multifactor authentication (MFA) is required for remote access;

- Device security, including up-to-date software and operating systems, antivirus software, and enabled firewalls are utilised for the remote access;

- All remote access is undertaken within the scope of the organisation’s DSPT (or other security arrangements as per this DSA) and complies with the organisation’s remote access policy.

The above applies in addition to any condition set out elsewhere within the DSA (e.g. who may carry out processing, and for what purpose).

Remote processing will be from secure locations within the UK. The data will not leave the UK at any time.

Access is restricted to employees of University College London (UCL).

University College London Hospitals NHS Foundation Trust (UCLH) is not permitted to access the Data.

All personnel accessing the Data have been appropriately trained in data protection and confidentiality.

The Data will not be linked with any other data.

There will be no requirement and no attempt to reidentify individuals when using the Data.

Researchers from the University College London (UCL) will analyse the Data for the purposes described above.

The expected outputs of the processing will be:

> Annual reports to NIHR

> At least one submission to peer reviewed journals e.g. European respiratory journal, Lung cancer, Thorax.

> Presentations at appropriate conferences e.g. British thoracic society annual conference, British thoracic oncology group conference.

> Production of algorithms and risk prediction models to predict and detect lung cancer in never-smokers for use in NHS healthcare. Expected completion date 2027.

> Inclusion in PhD thesis

The outputs will not contain NHS England Data and will only contain aggregated information with small numbers suppressed as appropriate in line with the relevant disclosure rules for the dataset(s) from which the information was derived.

The outputs will be communicated to relevant recipients through the following dissemination channels:

> Journals

> Patient engagement events at least twice a year

> Patient information leaflets either at GP practices or work with the Ruth Strauss charity.

> Posters at GP practices and work with the Ruth Strauss charity.

> Oral presentations at national and international meetings

The target date will be 2027 (end of PhD fellowship).

This research will improve the currently limited understanding of LCINS by advancing knowledge about symptoms as well as sociodemographic and risk factors. As recommended by patient representatives and the National Cancer Equality Initiative, measuring and understanding differences leads to improving inequalities and designing appropriate interventions. Understanding symptoms may influence a future NICE guideline update on referral from primary care.

It will also contribute to creating novel risk prediction models to identify high-risk adults who will benefit from early detection strategies. Such research will be word-leading and capitalise on the co-operation between primary and secondary care already established by screening ever-smokers.

Many patient representatives say this research will increase awareness of LCINS amongst healthcare professionals and health-seeking individuals and contribute to other research and public health measures.

The use of the data could:

> help the system to better understand the health and care needs of populations.

> lead to the identification or improvement of treatments or interventions, or health and care system design to improve health and care outcomes or experience.

> advance understanding of regional and national trends in health and social care needs.

> advance understanding of the need for, or effectiveness of, preventative health and care measures for particular populations or conditions.

> inform planning health services and programmes, for example to improve equity of access, experience and outcomes.

> inform decisions on how to effectively allocate and evaluate funding according to health needs.

> provide a mechanism for checking the quality of care. This could include identifying areas of good practice to learn from, or areas of poorer practice which need to be addressed.

> support knowledge creation or exploratory research (and the innovations and developments that might result from that exploratory work).

This research will improve the currently limited understanding of LCINS by advancing knowledge about symptoms as well as sociodemographic and risk factors. Measuring and understanding differences leads to improving inequalities and designing appropriate interventions. Understanding symptoms may influence a future NICE guideline update on referral from primary care.  It will also contribute to creating novel risk prediction models to identify high-risk adults who will benefit from early detection strategies.

It is hoped that through publication of findings in appropriate media, the findings of this research will add to the body of evidence that is considered by the bodies, organisations and individual care practitioners charged with making policy decisions for or within the NHS or treatment decisions in relation to specific patients. Clients will need to take action based on the information provided to them in order to realise the potential improvement opportunities.

The applicant is funded by a charity, Ruth Strauss Foundation, as well as NIHR. The applicant will work with the funders and with patient representatives to ensure that the research is shared with a wider audience than the academic/scientific community.

Cancer registry data was released to our team in March 2024 and we are currently reviewing the data prior to formal analysis.

Reviewing the data has allowed our research team to develop pivotal experience and research expertise with understanding cancer registry data, its strengths and limitations. This will allow us to achieve our intended benefit of improving the currently limited understanding of lung cancer in never-smokers (LCINS) and the health and care needs of populations. We have also increased engagement with patients and members of the public by discussing research objectives and methodology with our patient experience group. This experience and public engagement were reported, as planned in our data sharing agreement, in our annual report to National Institute of Health and Care Research (NIHR) as part of a doctoral fellowship.

Analysis of the data is expected to yield the following outputs (as previously stated in our data sharing agreement):

• At least one submission to peer reviewed journals e.g. European Respiratory journal, Lung Cancer, Thorax

• Presentations at appropriate conferences e.g. British Thoracic Society Annual Conference, British Thoracic Oncology Group Conference

• Information to help produce algorithms and risk prediction models to predict and detect lung cancer in never-smokers for use in NHS healthcare

• Inclusion in PhD thesis

The target completion date remains 2027 (end of PhD fellowship).