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Methods for performing meta-analysis of diagnostic accuracy studies are now well established and typically use joint models for sensitivity and specificity. In some cases it is plausible that diagnostic performance might improve or get worse over time, for a variety of reasons including operators becoming more accustomed to using new technology, or a diagnostic device being used in a different patient group.

Previous work has looked at assessing trends in meta-analyses of intervention effects.1 The proposed project will review these methods and extend them to develop techniques suitable for identifying temporal trends in diagnostic meta-analysis, and implement them in software. Data will be sourced from diagnostic accuracy evaluations published in the Cochrane Library, with an emphasis on evaluations of diagnostic tools and devices suitable for use in primary care. Reasons for changes over time for particular examples will be explored, possibly including comparisons of evaluations in laboratory versus real-world healthcare settings.

The student would join the Medical Statistics group ( in the Nuffield Department of Primary Care Sciences. Applicants should have a background in statistics, medical statistics or a closely related subject. There will also be opportunities to work closely with the NIHR Community Healthcare MedTech and In Vitro Diagnostics Co-operative ( to gain further experience of diagnostic evaluation. Although no specific funding is attached to this project, potential applicants are invited to look at funding opportunities as described here (

Interested applicants should contact Tom Fanshawe ( for more information.


1. Fanshawe TR, Shaw L, Spence GT. A large-scale assessment of temporal trends in meta-analyses using systematic review reports from the Cochrane Library. Research Synthesis Methods 2017; 8: 404-415.