Dr Jac Dinnes PhD, MSc, MA, PGDip

• PhD in Public Health and Medical Statistics, University of Southampton, 2009
• MSc (Res) in Public Health and Health Services Research, University of Aberdeen, 2001
• PG Dipl in Information Analysis, Robert Gordon University, 1994
• MA (Hons) Economic Science, University of Aberdeen, 1993

Jac Dinnes qualified with an MA (Hons) in Economic Science from the University of Aberdeen in 1993. She then completed a Postgraduate Diploma in Information Analysis and went on to work as a systematic reviewer for the NHS in Scotland, advising Health Boards on major purchasing decisions. Since 1998 she has held academic positions at the University of York (UK) and the University of Southampton (UK) before taking on her role at the University of Birmingham in 2009. She has completed a Masters degree in Public Health and a PhD concerned with the investigation of spectrum effects in diagnostic test accuracy systematic reviews.

Her work includes systematic reviews of both interventions and diagnostic tests across a range of clinical applications and is currently leading on a number of systematic reviews for the Birmingham Biomedical Research Centre, most recently as part of the Cochrane COVID-19 Diagnostic Test Accuracy Group. She has published 18 Cochrane reviews and several HTA monographs, and has co-authored a number of methodological projects. Her methodological interests began with a major project evaluating non-randomised intervention studies and since beginning her PhD in 2000, has focused on the evaluation of tests for diagnostic and monitoring purposes. She has contributed to the development of a number of reporting guidelines and standard for evaluating diagnostic test accuracy studies, and co-authored two chapters in the forthcoming updated Cochrane Handbook for Systematic Reviews of Test Accuracy. She regularly reviews Cochrane protocols and reviews amongst other peer review work.

Kostas Tryposkiadis - Statistical issues in assessing whether new biomarkers are fit for purpose

Jac has internationally recognised expertise in systematic reviews, particularly those of diagnostic test accuracy, and in systematic review methodology.  

Systematic reviews of diagnostic test accuracy

Jac is currently Systematic Review Programme Lead for the international Cochrane COVID-19 Diagnostic Test Accuracy Group. This is an international collaboration including representatives from WHO and FIND (Foundation for Innovative New Diagnostics) in Geneva. A suite of eight living systematic reviews to cover the roles of tests and characteristics in the diagnosis of COVID-19 are in production, four in Birmingham and a first iteration of five of the eight have already been published.  

Jac is also the Systematic Review Lead within the diagnostics and biomarkers cross-cutting theme for the NIHR Birmingham Biomedical Research Centre, advising clinicians on appropriate methodology for conducting systematic reviews and leading on two large systematic reviews of tests for early detection of undifferentiated arthritis. Prior to this she was chief investigator on an NIHR funded suite of Cochrane Reviews on the diagnosis and staging of skin cancer in collaboration with the Centre for Evidence Based Dermatology at the University of Nottingham. This consisted of a total of 13 reviews of over 400 diagnostic test accuracy studies. These reviews informed the decision by NICE to update the guideline on the management of melanoma (last updated in 2015).

Diagnostic test evaluations

Jac’s interest in diagnostic test research is longstanding. Her PhD on the effect of patient spectrum (case-mix) on diagnostic test accuracy included a thorough review of how heterogeneity has been examined in systematic reviews of diagnostic test accuracy, a comparison of three statistical methods for the meta-analysis of diagnostic accuracy studies and a meta-regression using a large sample of previously published systematic reviews of diagnostic tests to identify the influence of spectrum-related covariates. This interest has developed into a focus on how test evaluations and systematic reviews should consider the intended use of a diagnostic test and clinical pathway in which a diagnostic test will be used, to consider what the consequences of testing for patients at different points on the pathway and how best to communicate any effect from clinical pathway on test accuracy estimates to users of reviews.

Biomarkers for monitoring

Jac’s interest in diagnostic tests also extends to the use of tests for monitoring purposes. She led or contributed to a number of projects within the methodology workstream of an NIHR Programme Grant evaluating the benefits of new and existing biological fluid biomarkers in liver and renal disease. This included a consideration of current practice in establishing formal monitoring rules or strategies for monitoring and an exploration of methodological innovations for biomarkers for monitoring disease and of how successfully randomised designs can be used to evaluate the clinical effectiveness of monitoring strategies.

This work has now extended into a key BRC topic for the team, investigating methods for assessing key measurement properties of biomarkers both at primary study level and using systematic reviews.

Research groups and centres

• NIHR Birmingham Biomedical Research Centre
• Cochrane
• Cochrane Methods, Screening and Diagnostic Tests
• Cochrane Infectious Diseases
• FIND
• Amsterdam University Medical Centres
• Julius Centrum

• Editor, Cochrane Diagnostic Test Accuracy Reviews of the Cochrane Library (2020-)
• Member, Cochrane Screening and Diagnostic Test Methods Group. The Methods Group brings together expertise in study identification, risk of bias assessment, meta-analysis and interpretation of diagnostic accuracy reviews.
• Advisory group member for international reporting guidelines and quality assessment tools for test accuracy studies, most recently including the Standards for Reporting Diagnostic accuracy studies (STARD)
• ReLabel project to improve the reporting and communication of diagnostic accuracy studies, STARD Artificial Intelligence (STARD-AI) reporting guidelines and an expansion of the quality assessment tool for diagnostic accuracy studies to the assessment of studies comparing two or more tests (QUADAS-C).