(MRC DTP CASE) Understanding Disease Management and Outcomes for Myositis Patients: An International Real-World Study Utilising Multiple Data Sources to Investigate Treatment Patterns, Health-Related Quality of Life, Clinical Outcomes, and Burden of Illness for Patients With Rare Autoimmune Disease

The University of Manchester

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Myositis is a group of rare conditions which present with physical symptoms that can significantly impact a patient’s life. Many patients are permanently disabled due to irreversible muscle damage. This disease space is receiving increasing attention and consequently management of these patients is evolving rapidly. Better knowledge and understanding of treatment and clinical outcomes are vital to continue to improve disease management and patients’ quality of life.

In this PhD project, you will use large international physician and patient-completed real-world datasets across myositis (~n=2500 patients) to understand disease, clinical and humanistic burden in patients across these rare autoimmune neuromuscular inflammatory diseases, from multi-stakeholder perspective. Data and results will also be compared and analysed alongside University of Manchester-affiliated datasets, including UKMYONET cross-sectional study, MYOPROSP prospective cohort study, MYOACT novel therapies registry, UK neuromuscular biobank datasets. Your research will involve analysis of several real-world data sources to understand outcomes for myositis patients, seeking to understand quality of life, clinical biomarkers, treatment patterns and patient-reported outcomes across different healthcare systems.

We expect your research to improve our understanding of disease course and appreciate the effect of disease burden on myositis patients, and how this differs across types, and within different healthcare settings.

You will join our active and vibrant Manchester Myositis Research group, part of the wider UK Myositis Network and our successful international myositis collaborations. Through collaboration with Adelphi Real World, you will be integrated into the Adelphi team to work with disease area experts, health economists and biostatisticians, to analyse the datasets and highlight key findings and evidence. There will be opportunities to attend and present results at national and international meetings and conferences, and public and patient engagement events. Through both parties, findings from this PhD research study can help to drive understanding and learnings for the wider healthcare industry. The findings will improve the evidence-base for precision and stratified medicine, leading to more focussed disease management and treatment.

Eligibility

Applicants must have obtained or be about to obtain a First or Upper Second class UK honours degree, or the equivalent qualifications gained outside the UK, in a relevant discipline.

Before you Apply

Applicants must make direct contact with preferred supervisors before applying. It is your responsibility to make arrangements to meet with potential supervisors, prior to submitting a formal online application.

How to Apply

To be considered for this project you MUST submit a formal online application form – full details on how to apply can be found on the MRC DTP website https://www.bmh.manchester.ac.uk/study/research/mrc-dtp/ 

Your application form must be accompanied by a number of supporting documents by the advertised deadlines. Without all the required documents submitted at the time of application, your application will not be processed and we cannot accept responsibility for late or missed deadlines. Incomplete applications will not be considered. If you have any queries regarding making an application please contact our admissions team.

Equality, Diversity and Inclusion

Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website https://www.bmh.manchester.ac.uk/study/research/apply/equality-diversity-inclusion/

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