Characterising cancer in individuals with cystic fibrosis

The Data will be used for the purpose of a research project:

Characterising cancer in individuals with cystic fibrosis

The incidence of cancer among individuals with cystic fibrosis (CF) is thought to be significantly higher than observed in the background population. For example, work undertaken by the project team has demonstrated a 5-fold increased incidence of colorectal cancer in individuals with CF when age standardised. However, to date there have been no studies examining this relationship using the UK CF Registry dataset alongside national cancer registration data, both of which are regarded as gold standard.

Building on work undertaken by the project team examining the relationship between CF and colorectal cancer, this study seeks to determine the precise risk associated with CF and the development of cancer more widely. This will include transplant status, exposure to antibiotics and treatment interventions.

Overall Aim: Characterising cancer in individuals with CF and identifying phenotypes at elevated risk of developing cancer, and/or poor outcomes, to inform screening and surveillance of this population.

The study objectives are:

1. To identify the true prevalence and characteristics of the cancers diagnosed in the CF population.

2. To identify any predisposing factors (such as specific CFTR mutations, diabetic status, disease severity, solid organ transplant, frequency of intravenous antibiotic usage) and how these may be associated with differing risk.

3. To assess the relationship between CF and cancer outcomes (such as stage at diagnosis, receipt of surgical treatment, mortality and survival) and whether these differ to the non-CF cancer population.

4. To acquire the knowledge required to inform the development of educational resources and screening protocols to reduce the risk of people with CF unnecessarily developing cancer.

This project forms a PhD studentship which will run for three years.

UK Cystic Fibrosis Trust will transfer data to NHS England. The data will consist of identifying details (specifically NHS Number, Date of Birth, and a unique person ID) for the cohort to be linked with NHS England data.

NHS England will provide the relevant records from the HES and NDRS Cancer datasets to the University of Leeds. 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 recipient.

The Data will be stored on a secure data platform, Leeds Analytic Secure Environment for Research (LASER), at the University of Leeds.

The University of Leeds stores Data on the Cloud provided by Microsoft Limited.

The Data will be accessed onsite at the premises of the University of Leeds and 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).

Data will be linked at record level with clinical data from the CF registry, containing information such as data on lung function and medication use.

This project is funded by an educational grant through Boehringer Ingelheim, a private commercial pharmaceutical company. Boehringer Ingleheim will have no access to the Data, have not been involved in the design of the project and will not be involved in the delivery of the work.

The expected outputs of the processing will be:

- A report of findings to UK CF and the funder, Boehringer Ingleheim (expected to be one report at the end, and annual report updates to the funder)

- Submissions to peer reviewed journals (expected to be around 3-4 over the course of the PhD)

- Results will also be used to write grant applications to expand the scope of the work. This work forms the first part of a wider work package and will enable applications for funding to be submitted to funders (e.g. MRC, Wellcome). Any expansions in scope will first require approval from NHS England before the Data is used for these additional purposes.

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

- Social media (e.g. Bluesky, Facebook) via CF Trust and University of Leeds

- Reports to UK CF and the funder, Boehringer Ingleheim, which will present the results in an accessible, lay manner in order to inform patients, family members and clinical teams of the main results

The findings of this research study are expected to result in new and accurate information on the risks of developing cancer and the outcomes from cancer in the CF population, which can be fed back to the CF Trust and to the clinicians and teams treating these patients.

In the longer-term, this research study is expected to lead to a potential for service change based on the findings, for example, increased surveillance of at-risk groups, different treatments targeted at higher or lower risk groups. This will depend on discussions with clinicians, policy makers and commissioners, as examples. Processing of the Data is also expected to lead to the development of patient specific educational material to empower and facilitate decision making. Such material would be developed with the CF Trust and patient representatives. This research is also expected to add to the growing evidence that the CFTR gene is a cancer suppressor gene. Understanding the risks and outcomes in people with CF will provide important relevant information to guide mechanistic research in cancer in the wider population.

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 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.

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

Yielded Benefits is not a requirement for new applications.