Population-level analysis of cancer natural history, diagnostic pathways and outcomes across cancer types and ethnic groups in England

​​​​The Data will be used for the purpose of  ​​a research project: Population-level analysis of cancer natural history, diagnostic pathways and outcomes across cancer types and ethnic groups in England

​​The research project aims to examine cancer incidence, diagnostic pathways, delays and outcomes across population groups, and to develop models (including breast cancer screening models) to assess impacts on mortality, inequalities and health service outcomes.

​​The following are the aims/objectives of the processing:

Workstream 1: Diagnostic delay across the 12 most common cancers

• To understand cancer progression rates and quantify how diagnostic delay affects stage at diagnosis, mortality, and economic outcomes across the 12 most common cancers in England.

• To identify cancer types and population groups where timely diagnosis has the greatest impact.

• ​To develop cancer-type-specific multistate models using national cancer registry data.

Workstream 2: Breast cancer natural history and screening evaluation

• ​To develop ethnicity-specific models of breast cancer natural history and evaluate alternative screening strategies.

​The Data will be used to answer the following questions:

​1) How does diagnostic delay influence the likelihood of being diagnosed with advanced-stage cancer and subsequent mortality across different cancer types?

2) ​How do cancer progression, outcomes, and the impact of delay vary by ethnicity, socioeconomic status, and other patient characteristics?

3) ​What are the health and economic impacts of different diagnostic timelines, and could cancer-specific timelines improve outcomes compared to the current uniform approach?

4) ​What are the health and economic impacts of different diagnostic timelines, and could cancer-specific timelines improve outcomes compared to the current uniform approach?

5) ​For breast cancer, how does natural history and progression differ across ethnic groups, and how might alternative screening strategies affect detection, outcomes, and inequalities?​

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

​​​​NHS England will grant access to the Data via the Secure Data Environment (SDE).  The SDE is a secure data and research analysis platform. It allows approved researchers with approved projects access to pseudonymised data and industry-leading analytics tools.

​​NHS England will provide access to the relevant records from the NDRS Cancer Consolidated Dataset to University of Cambridge via NHS England Secure Data Environment (SDE). The Data will contain no direct identifying data items. The Data will be pseudonymised and individuals cannot be reidentified.

​SDE users can request exportation of aggregated analysis results (suppressed and summarised according to the NHSE SDE Disclosure Control rules) subject to review and approval by the NHS England SDE Output Checking team. The SDE Output Checking team will ensure that no output contains information which could be used either on its own or in conjunction with other data to breach an individual's privacy.

​Users must identify themselves via a multi-factor authentication mechanism and are only able to access the datasets detailed within this DSA. The access and use of the system is fully auditable, and all users must comply with the use of the Data as specified in this DSA.

​  ​​Users are only authorised to access the Data specified in this DSA and can utilise a variety of analytical tools available within the SDE platform. Users are not permitted to export record-level data from the SDE.

The Data will not be transferred to any other location.​

​​The Data will be stored on servers at NHSE Secure Data Environment​.

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).​

​The Data will not be linked with any other data outside of this DSA.​

The expected outputs of the processing will be:

-​​ A report of findings to academic, clinical, and policy stakeholders, including aggregate analyses of cancer incidence, stage at diagnosis, diagnostic pathways, and mortality outcomes across the study period.

​​- Submissions to peer-reviewed journals, including final publications reporting aggregated findings on diagnostic delay, cancer progression, and screening strategies across the duration of the project.​

​- Presentations to stakeholders and engagement activities, including a final stakeholder workshop to support interpretation of findings and their implications for cancer policy, screening, and service planning.

- ​Presentations at appropriate academic and policy conferences, as part of dissemination of findings relating to cancer early detection, diagnostic pathways, and screening strategies.

- ​Development of analytical models and simulation frameworks, including multistate models of cancer progression and microsimulation tools to evaluate diagnostic timelines and screening strategies.

Within 12 months of data access:

For Workstream 1:

• Aggregate statistical summaries of age-, ethnicity-, and cancer-specific incidence and mortality patterns across the 12 included cancers;

• Aggregate analyses of stage at diagnosis, routes to diagnosis, and related mortality outcomes across cancer types;

For Workstream 2:

• Development of ethnicity-specific population-level natural history models for breast cancer;

• Aggregate analyses of breast cancer mode of detection, including screen-detected and clinically detected cancers;

• Development of the microsimulation framework required to evaluate the population-level effects of alternative breast cancer screening strategies;

• Early PPIE-informed discussion of emerging findings, particularly where results relate to fairness, acceptability, and ethnic differences in early detection;

Within 24 months of data access:

For Workstream 1:

• Development of modelling work on diagnostic pathways and the impact of diagnostic delay across the 12 included cancers;

• Aggregate analyses of the potential economic burden associated with alternative diagnostic delay scenarios and cancer-specific diagnostic timelines;

For Workstream 2:

• Preparation and submission of peer-reviewed manuscripts arising from the breast cancer natural history;

• Conference presentations and academic dissemination of findings relevant to breast cancer screening policy, including how these alternative screening strategies may affect cancer detection, mortality outcomes, the extent to which alternative strategies may reduce inequalities across ethnic groups, and the potential economic and service implications at the population level.

Within 36 months of data access:

For Workstream 1:

• Peer-reviewed publications reporting final aggregated findings from the diagnostic pathway and diagnostic delay work across the 12 included cancers;

• Policy-facing outputs synthesising implications for cancer-specific diagnostic timelines, service planning, and inequalities in early diagnosis across population groups;

• Final stakeholder dissemination activities, including discussion of implications for early detection policy and cancer diagnostic pathways where appropriate.

​​​​​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 – submission of peer‑ reviewed publications reporting aggregated findings from the analysis of diagnostic delay, cancer progression, and screening strategies.

• ​Workshops involving academic, clinical, and policy stakeholders – including a planned stakeholder workshop to support interpretation of findings and discussion of implications for cancer policy, screening, and diagnostic.

• ​Briefing documents provided to relevant stakeholders – including policy-facing outputs synthesising implications for service planning, diagnostic timelines, and inequalities in early diagnosis.

• ​Presentations at appropriate conferences – dissemination of findings through academic and professional forums relating to cancer research, early detection, and public health

• ​Public reports – production of aggregated, anonymised statistical outputs suitable for wider dissemination, with no release of record-level data.

• ​Direct engagement with stakeholders and communities – including ongoing involvement of patient and public contributors (PPIE) in interpreting findings and supporting clear communication of results.

• ​Public promotion of the research – through appropriate academic and stakeholder engagement activities, ensuring findings are communicated in a way that supports understanding and avoids misinterpretation.

​​The findings of this research study are expected to contribute to evidence-based decision-making for policymakers, local decision-makers such as doctors, and patients to inform best practice to improve the care, treatment and experience of health care users relevant to the subject matter of the study.

​​The use of the data could:

​​Help the system to better understand the health and care needs of populations, particularly in relation to cancer progression, diagnostic delay, and outcomes across different cancers and population groups.

​Lead to improved understanding of how diagnostic delay affects stage at diagnosis and mortality, supporting earlier detection and better patient outcomes.

​Inform the design and refinement of diagnostic pathways and screening strategies, including evaluation of more tailored and equitable approaches to breast cancer screening.

​Advance understanding of inequalities in cancer outcomes, including variation by ethnicity and socioeconomic status, supporting more equitable service delivery

​Inform planning of health services and programmes by providing evidence on cancer-specific diagnostic timelines and service needs.

​Support decisions on how to prioritise resources and manage the economic burden of delayed diagnosis, through analysis of cost and outcome scenarios.

​Support knowledge creation and further research through development of population-level models and analytical frameworks relevant to cancer early detection and policy.​

Informed by Patient and Public Involvement and Engagement (PPIE) discussion, findings will be interpreted and communicated with particular attention to fairness, acceptability, and the potential differential impact of screening or diagnostic strategies across population groups. This will include discussion of how alternative screening eligibility rules and diagnostic timelines may be understood by affected communities, and how findings should be communicated to avoid misinterpretation or unintended stigma. These perspectives will also help inform discussions with clinical, policy, and screening stakeholders about the practical implications of the findings for equitable screening and early diagnosis.

Yielded Benefits is not a requirement for new applications.