Medical Statistics
We are interested in diagnostic accuracy, prognostic research, and systematic reviews. We look at the design of studies and conduct systematic reviews of how reporting of these models can be improved.
Introduction: Designing diagnostic test accuracy studies
Professor Sue Mallett presents an essentials short course to help you understand the importance of the reference standard to interpretation of diagnostic accuracy results. These pause-and-think exercises will help you identify circumstances when an antibody test for the COVID-19 virus can be useful or not, for guiding health policy.
Evidence-based assessment of imaging tests
The Centre for Medical Imaging has a long-standing interest in the design and analysis of imaging studies and similar diagnostic tests.
These studies exhibit key distinctions from studies in multiple other medical fields. Statistical tests and study designs that may be appropriate for research of, for example, novel therapeutics, do not necessarily translate into the imaging domain.
We also have a strong interest in the design and execution of studies that seek to develop diagnostic or prognostic models that diagnose or predict events in individual patients.
Much of our work in this area centres around systematic reviews that detail how the design, execution, and reporting of such models can be improved.
Experts
Prof. Sue Mallett
Diagnostic Medical Statistics
Prof. Steve Halligan
Gastrointestinal Radiology
Publications
- Eze VN, Parry T, Boone D, Mallett S, Halligan S (2024). Prognostic factors to identify resolution of small bowel obstruction without need for operative management: systematic review. Eur Radiol. 2024 Jun;34(6): 3861-3871.
- Halligan S, Boone D, Archer L ... Mallett S (2021). Prognostic biomarkers to identify patients likely to develop severe Crohn's disease: a systematic review. Health Technol Assess. 2021 Jul;25(45): 1-66.
