The Role of Patient-Reported Outcome Measure in the Prediction of Late Cancer Outcomes (Survival)

The University of Leeds requires access to NHS England National Disease Registration Service (NDRS) National Cancer Registration and Analysis Service (NCRAS) data for the purpose of the following research project:

The Role of Patient-Reported Outcome Measure (PROMs) in the Prediction of Late Cancer Outcomes (Survival)

The following is a summary of the aims of the research project:

To determine whether the automated analysis of PROMs adds predictive value to routine healthcare data when predicting cancer survival. The study team want to understand what information in the PROMs may be useful to develop a machine learning model that predicts survival.

The following NHS England NDRS NCRAS Data will be accessed:

NDRS Cancer Registrations- necessary to understand the survival of patients who have completed the Quality of Life of Colorectal Cancer Survivors in England Survey

NDRS Quality of Life of Colorectal Cancer Survivors in England Survey- necessary to determine the predictive value of PROMS.

The level of the Data will be:

• Pseudonymised

The Data will be minimised as follows:

• Data will be limited to patients who were diagnosed with colorectal cancer and provided responses to the Living with and Beyond Bowel Cancer survey (CRC-PROMs) national PROMs survey. This is estimated to be around 34,000 individuals.

The University of Leeds is the research sponsor and 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 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.

The funding is provided by the UK Research and Innovation (UKRI). The funding is in place for two studentships at the UKRI Centre for Doctoral Training in AI for Medical Diagnosis and Care.

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

Microsoft Ltd provides IT hosting services to the University of Leeds and will store the Data as contracted by the University of Leeds.

An individual substantively employed by the University of Southampton is listed on the study protocol, this individual serves in advisory capacity only. This individual plays no role in determining the purpose and means of processing, and will not process the requested data.

Data will be accessed by:

• Named PhD students enrolled with the University of Leeds. Any student working with the Data held under this Data Sharing Agreement (DSA) must have completed relevant data protection and confidentiality training and are subject to the University of Leeds’ policies on data protection and confidentiality. Any students accessing the Data will do so under the supervision of a substantive employee of the University of Leeds. The University of Leeds is responsible and liable for any work carried out by students.

Students will only work on the Data for the purposes described in this DSA.

This project is scheduled for discussion (both during the analysis stage and when finalised) with patients and public groups (for example, the Bowel Cancer Intelligence Patient Group) to gain the views of cancer patients and their families. Currently, the project has been discussed with a panel of patient representatives at the CRUK RadNet Leeds Patient Dragons’ Den event, and with patients and the public at a useMyData webinar on AI & Patient Data. The patients have voiced support for the utilisation of PROMs to improve patient outcomes.

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

The NHS England NDRS will provide the relevant records from the above-listed dataset. 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 beyond the Leeds Analytics Secure Environment for Research (LASER) which is supported by a cloud-based IT platform provided by Microsoft Ltd.

The Data will be stored on servers at Microsoft Ltd.

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

The Controller 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 leave or be accessed outside of England at any time.

Data will be accessed by two students enrolled with the University of Leeds under the supervision of substantive employees of the University of Leeds . Aside from these individuals, access is restricted to substantive employees of the University of Leeds who have authorisation from the Principal Investigator.

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

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

Researchers will process the Data for the purposes described above.

The expected outputs of the processing will be:

• PhD thesis

• Submissions to peer reviewed journals (for example Health Informatics Journals, Medical Journals and Computer Science Journals)

• Presentations to research groups and PPIE groups

• Presentations at appropriate conferences such as UK Patient Reported Outcome Measures Research Conference, UKRI AI CDTs in Healthcare Joint Conference, International Conference on Machine Learning, Conference on Health, Inference, and Learning and also The Cancer Research UK Data-driven research conference.

• Presentations to relevant patient or health research forums

• The code used and developed for this study will be made publicly available for free on an open access repository such as GitHub.

The outputs will not contain individual level 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:

• Peer-reviewed journal articles (made open access)

• Webinars and presentations open to research groups, PPIE events and outreach events

• The code developed will be made available open source on repositories such as GitHub

• Posters displayed at local, national and international conferences

• Results fed back to focus group participants.

• Web outlets

The target dates:

• PhD thesis 1 - to be submitted and examined and completed by Dec 2026

• PhD thesis 2 – to be submitted and examined and completed by Dec 2027

• Journal articles and conferences – expected ~ mid to late 2024. Submissions will be made to Journals on an on-going basis from that point going forward.

• Presentations to research groups and patient groups – the study team expect that the project outputs are presented to relevant groups on an on-going basis

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 by informing best practice to improve the care, treatment, and experience of health care users relevant to the subject matter of the study.

The work carried out in this project will explore and identify the contribution of this PROMs data to understanding the effect on the patients’ survival as an outcome. It will investigate whether information provided in the PROMs correlates to better or worse outcomes. The potential benefits include:

• expanding the understanding of the health and care needs of cancer patients

• helping to inform decisions on how to effectively allocate and evaluate funding according to health needs

• providing a mechanism for checking the quality of care

• facilitating the routine use of PROMs will allow for the co-production of health care pathway, with the benefit of dealing with unmet need and enhancing quality of life

It is hoped that through publication of findings in appropriate media and presenting to patient and researcher forums, the findings of this research will add to the body of evidence that is considered by the organisations and individual care practitioners charged with making policy decisions for or within the NHS or treatment decisions in relation to specific patients.

Additionally, the outputs may lead to informed optimisation of clinical care pathways through patient centred care. This research has the potential to give evidence of the importance and the means to incorporate the patient voice within overall clinical policy and decision making.

The study team have already engaged with Cancer Research UK (CRUK) RadNet Leeds and useMYdata in relation to this project, and intend to make use of these connections when it comes to disseminating the findings of the study.

Yielded Benefits is not a requirement for new applications.