Evaluating the Meta-Analysis Global Group in Chronic (MAGGIC) Heart Failure Risk Score

Supervisors: Dr Maria Vazquez-Montes; Dr Kathryn Taylor; Professor Clare Taylor

The guidelines on heart failure management emphasize the importance of individualized risk assessment to inform treatment decisions, but there is no consensus on how to perform this assessment. While many prognostic models exist, the MAGGIC risk score, based on 13 patient characteristics, has been widely validated but lacks reliable prediction performance data for the UK population due to variability in study quality. This proposal aims to externally validate the MAGGIC score using UK data and guidelines to improve its reliability in UK healthcare. The project also seeks to assess the patient benefit of incorporating this digital tool into clinical practice, explore its association with quality of life measures, and explore and implement adequate methods to evaluate its cost-effectiveness, considering factors such as measurement error and missing data.

Preferred applicant background/skills: We are seeking a candidate with a strong background in clinical and quantitative research. The ideal candidate will have:

• A Master's degree in Statistics (or similar) and a degree in a clinical field.
• Expertise in systematic reviews, meta-analysis, prediction modelling, large data analysis, and simulation, supported by a strong computational skill set.
• Proven ability to communicate effectively with patients and the public across diverse backgrounds.