The UHSM Cardiovascular Magnetic Resonance Study

Manchester University NHS Foundation Trust (MU NHS FT) requires access to NHS England data for the purpose of the following research project:

The UHSM Cardiovascular Magnetic Resonance Study

The following is a summary of the aims of the research project provided by MU NHS FT:

Cardiac Magnetic Resonance (CMR) imaging is now a form of imaging used throughout the United Kingdom to diagnose heart conditions and to guide patient management. CMR is still a relatively new technique and variable adoption in uptake has meant that the value of some components of CMR are not well established. The field of CMR is also rapidly changing and new components of the scan are regularly introduced into clinical practice. The relevance of these new components in respect to various heart conditions is not well understood.

The UHSM CMR study aims to investigate how CMR can be used to diagnose heart conditions and how certain findings on CMR can be used to predict people’s life expectancy and quality of life.

The UHSM CMR study requires follow-up information on the health status of the study cohort. This is limited to five variables (death, cause of death, hospital admission, cause of hospital admission, and method of hospital admission). Such data will be used to perform analyses such as multivariable regression to detect relationships between CMR indices and clinical factors, survival analyses to determine the relationship between CMR indices and survival or hospital admission, risk modelling and unsupervised machine learning analyses to identify linking patterns between patients that are currently unknown.

Specific aims:

> To determine the prognostic relevance of blood biomarkers for the identification of patients at risk of developing heart failure. Blood biomarkers allow for greater generalisability compared to CMR indices.

> To assess the impact of myocardial fibrosis and other CMR indices on prognosis in heart failure and other cardiovascular conditions.

> To implement a heart failure risk model for use within primary care, which will build on a previously published risk model that used data from The UHSM CMR study.

> To determine the prognostic impact of fat tissue around the heart. It is well known that obesity is associated with poor outcome. However, the link between localised tissue around the heart, and outcome, is not so clear. This will be quantified using a novel CMR method.

> To develop a risk model using CMR indices for patients with hypertrophic cardiomyopathy, the most common congenital cardiac condition. We will also attempt to reclassify hypertrophic cardiomyopathy into more distinct phenotypes using CMR indices and machine learning techniques.

> To reclassify heart failure with preserved ejection fraction (HFpEF) using CMR indices and machine learning techniques and understand reasons why certain subgroups of patients with HFpEF have different outcomes.

The following NHS England Data will be accessed:

> Hospital Episode Statistics Admitted Patient Care (HES APC) – necessary to identify if a patient was admitted to hospital and for what cause.

> Civil Registration Mortality – necessary to determine date of death and cause of death for survival analysis.

Justification of sensitive fields requested:

> Date of death is required in order to determine the time (number of days) from consent to death. This is in order to undertake survival analyses.

The level of the Data will be:

> Identifiable

The Data will be minimised as follows:

> Limited to a consented study cohort identified by MU NHS FT – a subset of patients recruited to the UHSM CMR study between 1st January 2015 and 13th December 2022. This subset of patients will include 10,007 patients aged 16 years or older who were undergoing clinically indicated CMR scanning at the MFT (Wythenshawe Hospital) CMR Unit.

> Limited to data between 1st January 2015 to latest available to enable patient follow-up.

MU NHS FT 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.

Heart Failure affects approximately 1-2% of the population and has significant societal and economic impacts. The prevalence of heart failure is increasing. It is in the public interest to improve the understanding of cardiovascular conditions such as heart failure so that novel treatments can be developed and the risk of developing this condition can be accurately quantified.

The funding is provided by the National Institute for Health Research. The funding is for the department and is not specifically limited to the study described.

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

Data will be accessed by:

• Substantive employees of MU NHS FT

• Individuals holding an honorary contract under the supervision of a substantive employee of MU NHS FT for the purposes described in this DSA only. MU NHS FT must maintain records in a single location that cover the following details of each individual given access under an honorary contract:

o Their substantive employer;

o Their role in respect of the purpose for the processing specified in the DSA;

o The start date and end date of the duration in which the Data will be accessed by the individual under an honorary contract;

o The necessity for the Data to be accessed by the person(s) holding an honorary contract, instead of a substantive employee of an organisation named as controller or a processor in this DSA;

o Confirmation that an appropriate contract is in place which follows the relevant guidance and is countersigned by the substantive employer of the honorary contract holder.

The research team at MU NHS FT work closely with patients and members of the public in the design and management of research including this study. Through meetings with patients, patients have inputted to study design and analysis.

MU NHS FT 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 deaths datasets to MU NHS FT. 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 not be transferred to any other location.

The Data will be stored on servers at MU NHS FT.

The Data will be accessed onsite at the premises of MU NHS FT only.

The Data will not leave England at any time.

Data will be accessed by individuals with an honorary contract with MU NHS FT. The individuals will act as agents of MU NHS FT at all times under supervision from employees of MU NHS FT. Aside from these individuals, access is restricted to employees or agents of MU NHS FT who have authorisation from the Principal Investigator.

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

The Data will be linked at person record level with participant record data held within the UHSM CMR Study database. The record data is pseudonymised and includes demographics, medical history, laboratory results, electrocardiography results, and cardiac MRI data.

The Data may also be compared with, but not linked with, data from the University of Pittsburgh for validation purposes. University of Pittsburgh data will include clinical data such as past medical history, physical status, laboratory results and health status. University of Pittsburgh will not have any access to MU NHS FT data or NHS England Data.

The Data will not be linked with any other data.

Analysts from the MU NHS FT and individuals who hold an honorary contract with MU NHS FT will analyse the Data for the purposes described above.

Following the completion of the analysis, MU NHS FT would like to retain this Data to ensure reconstruction of the trial analysis is possible if required.

The expected outputs of the processing will be:

> Submissions to peer reviewed journals, with the aim of publishing 2-3 times per year

> Presentations at conferences, such as the British Society for Heart Failure annual meeting, the Society of Cardiovascular magnetic resonance annual meeting, the British Society of Cardiovascular magnetic resonance annual meeting, the British Cardiac Society annual meeting and the European Society of Cardiology annual meeting

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

> National and international conferences to the scientific community

> Patient and Public Involvement (PPI) including charity foundations such as the Pumping Marvellous Foundation

The aim is to analyse the data in 2024-2025 with submissions to scientific journal beginning in 2025.

There are several potential benefits to health and/or social care. Improving the detection of heart failure, which affects 2-3% of the population, at an earlier stage in at-risk patients, to facilitate earlier treatment and potentially improve prognosis is one of the key benefits. This work will build on previously published work that used UHSM CMR data.

MU NHS FT aim to:

> increase the adoption and access of CMR across the country by demonstrating the ability of novel CMR indices to identify cardiovascular conditions and improve risk prediction.

> improve the understanding of heart failure with preserved ejection fraction (HFpEF), which is currently a poorly understood, heterogenous condition that affects approximately half of patients with heart failure and has very limited treatment.

> demonstrate, with the use of CMR, that HFpEF is an umbrella term for a range of conditions and that by breaking HFpEF down into subgroups, more successful treatments can be developed.

> improve the understanding of hypertrophic cardiomyopathy (the most common inherited cardiac disorder), for which there remains a critical need for therapies and greater prediction of risk for adverse outcomes in affected individual.

> improve understanding of health in the UKs third largest region (Greater Manchester). The UHSM CMR study includes patients from across the North-West region as the CMR scans are undertaken in the primary centre for cardiovascular imaging across this region.

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 such as obesity and diabetes.

> 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).

Specific benefits for patients may include:

1. Increased availability of cardiac MRI scanners

2. Earlier interventions in patients to prevent heart failure in at-risk individuals

3. Improved understanding of heart failure to allow discovery of new treatments

4. Improved identification of patients with hypertrophic cardiomyopathy at high risk of adverse events

How the proposed outputs will lead to the above benefits:

1. Demonstrating to the cardiovascular and healthcare community the benefit of cardiac MRI to identify cardiovascular conditions.

2. Publishing a risk prediction model for the development of heart failure.

3. Demonstrating that heart failure with preserved ejection fraction is a heterogenous condition made up of multiple subgroups that can be targeted with specific therapies.

4. Publishing a novel risk prediction model in patients with hypertrophic cardiomyopathy.

If the findings are significant, the aim will be to advertise them to a wider audience through the use of social media, for example, via a MFT social media account, and charities such as the British Society for Heart Failure, a charity for which the PI sits on the scientific steering committee.

Yielded Benefits is not a requirement for new applications.