Michael is Head of the new Leeds Centre for Personalised Medicine and Health, matching population health and care needs with excellent science and innovation, as part of the Leeds Academic Health Partnership. The Partnership identifies, attracts and implements innovation and inward investment that responds to the challenges facing health and care, including reducing health inequalities across the city. He is also the Deputy Director of the National Institute for Health Research (NIHR) Leeds MedTech and In-Vitro Diagnostic Co-Operative (MIC), an industry facing collaboration aimed at catalysing evaluations of commercial tests and providing evidence for NHS adoption – with a focus on cancer diagnostics. As a standing member of the National Institute for Health and Care Excellence (NICE) Diagnostics Advisory Committee, Michael provides advice to NICE on the formulation of guidance on diagnostic technologies and any other matter related to the evaluation of diagnostic technologies.
Michael has end-to-end experience across the “diagnostic pipeline” and is focused on developing, evaluating and implementing diagnostic tests with the potential to improve health outcomes and cost-effectiveness. His role in the CanTest Collaborative will be to provide an interface and capability with NHS pathology, advising on issues pertaining to system integration, analytical performance evaluation, pre-analytical factors, biological factors and quality control and assurance processes. He also brings an extensive network of commercial diagnostic developers and a track record of working successfully with industry.
View Michael’s LinkedIn profile.
+44 (0)113 2067980
University of Leeds, UK
In Vitro Diagnostics
- Are common blood tests being optimally used for early cancer diagnosis? (PhD)
- Investigation of potential for using point of care tests for early cancer diagnosis in primary care (PhD)
- Determining which biomarkers are ready for evaluation in primary care for use in early detection and diagnosis of gastro-intestinal cancers: a systematic review
- Investigating the use of routine blood tests and reflex testing to improve the early diagnosis of myeloma
- Target Product Profiles for Early Cancer Diagnostics
- Walter FM, Thompson MJ, Wellwood I, Abel GA, Hamilton W, Johnson M, Lyratzopoulos G, Messenger MP, Neal RD, Rubin G, Singh H, Spencer A, Sutton S, Vedstead P, Emery JD. Evaluating diagnostic strategies for early detection of cancer: the CanTest framework. BMC Cancer, 2019, 19:586
- Smith AF, Shinkins B, Hall PS, Hulme CT, Messenger MP. Towards a framework for outcome-based analytical performance specifications: a methodology review of indirect methods for evaluating the impact of measurement uncertainty on clinical outcomes. Clinical Chemistry, 65:11 (1363-1374), doi: 10.1373/clinchem.2018.300954
- Cocco, P., Ayaz-Shah, A., Messenger, M.P. et al. Target Product Profiles for medical tests: a systematic review of current methods. BMC Medicine, 2020, 18(119), doi: 10.1186/s12916-020-01582-1
- Calanzani N, Druce PE, Snudden C, Milley KM, Boscott R, Behiyat D, Saji S, Martinez Gutierrez J, Oberoi J, Funston G, Messenger M, Emery J, Walter FM. Identifying Novel Biomarkers Ready for Evaluation in Low-Prevalence Populations for the Early Detection of Upper Gastrointestinal Cancers: A Systematic Review. Adv Ther (2020). doi: 10.1007/s12325-020-01571-z
- Cocco P, Messenger MP, Smith AF, West RM, Shinkins B. Integrating Early Economic Evaluation into Target Product Profile development for medical tests: advantages and potential applications. International Journal of Technology Assessment in Health Care. 2021;37(1):e68. doi: 10.1017/S0266462321000374
- Savage R, Messenger M, Neal RD, Ferguson R, Johnston C, Lloyd KL, Neal MD, Sansom N, Selby P, Sharma N, Shinkins B, Skinner JR, Tully G, Duffy S, Hall G. Development and validation of multivariable machine learning algorithms to predict risk of cancer in symptomatic patients referred urgently from primary care: a diagnostic accuracy study. BMJ Open 2022; 12:e053590. doi: 10.1136/bmjopen-2021-053590