Cancer long-term follow-up study of clinical trial participants

The MRC Clinical Trials Unit at University College London (from here on referred to as UCL) requires access to NHS England data for the following research projects:

1) PATCH: Prostate Adenocarcinoma: TransCutaneous Hormones Trial

2) Add-Aspirin Trial

3) (RAMPART): Renal Adjuvant MultiPle Arm Randomised Trial

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

The PATCH trial (approximately 1400 trial participants) is investigating the safety and efficacy of replacing androgen suppression using luteinising hormone-releasing hormone (LHRH) analogues with transdermal oestrogen (tE2) patches in men with high-risk localised or metastatic prostate cancer.

The Add Aspirin trial (approximately 6307 trial participants) is investigating the use of adjuvant aspirin in four cohorts of non-metastatic cancer trial participants who have received curative-intent treatment (breast, colorectal, gastro-oesophageal, and prostate cancer).

The RAMPART trial (approximately 457 trial participants) is investigating adjuvant immune checkpoint inhibitors after nephrectomy for locally advanced renal cell cancer (RCC).

Across these 3 trials, approximately 8000 patients have provided consent for linkage.

The key objectives across all trials are as follows:

1. Capture Long-Term Outcomes of Cancer Trial Participants including:

• Overall survival (OS) and cancer recurrence/progression.

• Gather information on second new primary cancer and major non-cancer medical events.

• Assess whether early treatment effects are sustained in the long term.

• Identification of delayed benefits and harms from interventions that are not captured in the short term.

• Determine the long-term risk/benefit profile of the interventions.

2. Improve Trial Conduct and Data Collection Methods

• Evidence Building: Contribute to the body of evidence supporting the use of health systems data (HSD) in future clinical trials through methodological studies comparing HSD with traditional trial data collection methods.

• Streamline Data Collection: Use HSD to simplify the data collection process, reduce missing data, and lower overall trial costs.

• Reduce Burden: Minimise extra trial-specific visits required for long term follow up for participants and NHS hospital research teams.

• Cost Reduction: Potentially decrease the costs of trial coordination and long-term data collection.

The following NHS England datasets are requested:

Hospital Episode Statistics (HES) - Admitted Patient Care / Outpatients datasets are needed to assess:

o Treatment related toxicity (e.g. admission with fracture)

o Major medical events which may or may not be directly related to the cancer

National Disease Registration Service (NDRS) Cancer Consolidated Dataset

o Details of cancer recurrence to calculate disease free survival (DFS) or metastasis free survival (MFS))

o Details of new primary cancer

o Identify secondary treatments and act as a proxy for progression

Civil Registration Mortality

o Date of death to calculate overall survival

o Causes of death to identify mortality patterns / disease specific mortality

The level of the data will be:

• Identifiable – the Data will contain no direct identifying data items, it will contain a unique person ID which can be used to link the Data with other record level data already held by the recipient.

The Data will be minimised as follows:

• Limited to cohorts identified by UCL which includes those enrolled in England and Wales within the Add-Aspirin, PATCH, and RAMPART trials, who consented to have their personal identifiers shared to enable linkage to their health data.

• Limited to data from when the first participant was enrolled in either the Add-Aspirin, PATCH, or RAMPART trial. For each participant, data will only be provided from the date they joined the trial.

UCL is the research sponsor and the controller. UCL is 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 controller.

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

• 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 adheres to the UK Policy Framework for Health and Social Care Research, which protects and promotes the interests of patients, service users, and the public, and aims to produce generalisable and publicly available information to inform future decisions regarding patients’ treatments or care.

Funding is from multiple sources, including Cancer Research UK, the National Institute for Health and Care Research (NIHR), Kidney Cancer UK, MRC CTU core funding and AstraZeneca LP. The funders will have no ability to suppress or otherwise limit the publication of findings. AstraZeneca provided free drug for participants in the RAMPART trial, Bayer Pharmaceuticals AG provided free drug for participants in the Add-Asprin trial, and Bayer and Theramex provided discounted tE2 patches for participants in the PATCH trial.

Amazon Web Services provides cloud backup services to UCL and stores the data as contracted by UCL.

Data will be accessed by Masters or PhD students enrolled at UCL. Any student working with the data held under this Data Sharing Agreement (DSA) must have completed relevant data protection and confidentiality training and is subject to UCL’s policies on data protection and confidentiality. Any students accessing the data will do so under the supervision of a substantive employee of UCL. UCL will be responsible and liable for any work performed by students. These students will only work on the data for the purposes described in this DSA.

Each of the clinical trials is overseen by a Trial Management Group (TMG) comprising the Chief Investigator, co-investigators, members of the MRC CTU and an independent Trial Steering Committee (TSC).

For each trial, a Public and Patient Involvement and Engagement group helped refine the research purpose. The group supported the collection of data for the purposes described above. The PPI groups involved in the PATCH, Add-Aspirin, and RAMPART trials shared letters expressing support for the collection of data from NHS England for trial participants. Each PPI letter expressed the belief that the consent materials were compatible with the request for NHS England data and that the data would be important in supporting the findings of each trial.

UCL will combine the trial cohorts and transfer a single list of participants to NHS England to enable the cohort to be linked with NHS England Data.

The data will consist of the following:

• NHS Number

• Date of Birth

• Gender

• Unique person ID (a composite of trial number and pseudonymised patient identifier)

• Date of enrolment into the relevant trial

NHS England will provide the relevant records from the HES, Civil Registration Deaths, and NDRS datasets to UCL. The Data will contain no direct identifying data items but will contain a unique person ID which can be used to link the data with other record-level data already held by the MRC CTU.

The Data will be stored on servers at UCL’s Data Safe Haven (DSH). UCL stores data on the Cloud provided by Amazon Web Services.

The Data will not be transferred to any other location.

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 possible 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, is used for 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 England/Wales. The Data will not leave England/Wales at any time.

Access is restricted to substantive UCL employees and UCL enrolled students who have authorisation from the UCL lead investigator for each of the three trials.

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

The Data will be linked at person record level with clinical trial data.

The identifying details will be stored in a separate database from the linked dataset used for analysis. All analyses will use the pseudonymised dataset. There will be no requirement and no attempt to re-identify individuals when using the pseudonymised dataset.

Researchers from UCL will process and analyse the Data for the purposes described above.

The expected outputs of the processing will be:

- Presentations at major international and national scientific conference. The choice of platforms will depend on the key findings and target audience to enable maximum impact. This approach ensures engagement with stakeholders involved in use of health data, cancer researchers and clinical trial design and conduct methodologists

- Publication in high impact peer-reviewed journals

- A written summary of results produced for hospital sites, to distribute to trial participants by their doctors

- News articles on each trial website

- Tweets on the @MRCCTU Twitter account / Bluesky account

- For relevant data obtained from NHS England that may impact the important outcomes of the trial (e.g. survival data from CRD), MRC CTU at UCL will create intermediate trial reports for review by the Independent Data Monitoring Committee (IDMC), who are an independent group of experts who monitor patient safety and treatment efficacy data

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

- Journals: Cancer-specific journals (for example Journal of clinical oncology, British journal of cancer or Lancet Oncology) or general medical journals (for example Lancet, The Journal of the American Medical Association, The New England Journal of Medicine). All publications will be published based on UCL open access policy, including publication in open access journals and access to the results on the MRC clinical trials website which is freely open to the public.

- Research events and seminars to communicate results to health workers and patients.

- Briefing papers

- Trial participant communications: Results will be disseminated to trial participants using various media and patient publications, in collaboration with the MRC impact and communications team and PPIE trial representatives.

- Wider public communications: Results will be disseminated to the wider public and cancer community, through collaborations with supporting charities (e.g. Action Kidney Cancer, CRUK) through various media outlets such as articles on charity websites.

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 target dates for production and dissemination of the outputs will vary according to clinical trial. The anticipated timelines of the primary analysis for the three trials are as follows:

- Add-Aspirin - 2028

- PATCH – Autumn 2026

- RAMPART – Spring 2026

Multiple publications are planned beyond these timepoints to report on long term events.

The findings of this work will contribute to the evidence-based decision making for policy makers, in particular health care professionals. The beneficiaries of this research include:

Cancer trial participants

- For the patients on trials, using health care data linkage could streamline data collection needed for cancer trials. This could potentially reduce the need for intensive follow up which is currently required. In practice, this would mean fewer visits to hospital which can often be time consuming and costly.

- Data enabled trials may enable primary outcomes to be reported more quickly which would accelerate the process of introducing new cancer treatments for patients. As an example, in the STAMPEDE Metformin trial using CRD data allowed faster reporting of the trials primary outcome.

Cancer patients in the NHS

- Historically, clinical trials have taken many years to conduct and then report outcomes. More streamlined and efficiently run cancer trials could help to deliver improvements to cancer care faster which would directly benefit all cancer patients

- Understanding and developing strategies to mitigate or treat long-term toxicities of cancer treatments can directly optimise patient care. For example, refer back to the objectives section where we discussed previous examples from the STAMPEDE trial of outputs which lead to changes in patient care.

- Understanding the longer-term implications of emerging cancer treatments, could impact health policy planning and delivery, benefiting cancer patients across the NHS.

Clinicians and research teams delivering clinical trials in NHS hospitals

- Enabling linkage to healthcare data to clinical trials quickly and efficiently will mean staff would have more time for direct patient care and greater capacity to conduct clinical trials.

Clinical trial researchers at sponsor level

- By utilising linkage to healthcare data, sponsors may have decreased workload from processing data from trial sites and querying site-reported data. This could significantly decrease the cost and improve efficiency of clinical trials.

Benefit to the wider trials’ community in health and social care research

- This work will help validate data-enabled clinical trials and pave the way for innovative trial designs utilising national registries across the health and social care research community.

Data users and providers

- Combining several research projects under a single DSA provides potential resource efficiencies in accessing Data from NHS England.

- Clinical trials units and other academic institutions devote a significant amount of time and resources to submitting multiple DARS applications. We anticipate this application will provide a framework for other academic institutions accessing the same data assets for multiple trials under a single data sharing agreement, benefiting both institutions and NHS data providers.

- This work has the potential to demonstrate the value of NHS datasets in driving medical research and will strengthen partnerships with NHS England and academic institutions to use such data for vital research in health and social care.

Yielded Benefits is not a requirement for new applications.