Carl Moons

Qualifications MSc Health Sciences, MSc Clinical Epidemiology, PhD Medicine

 Current Positions

• Professor of Clinical Epidemiology, Julius Center of Health Sciences and Primary Care, University Medical Center (UMC), Utrecht (since 2005).
• Director of Research, Julius Center of Health Sciences and Primary Care (2011-2022)
• UMC Utrecht figure head Artificial Intelligence
• Director of nationwide infrastructure Health Innovation Netherlands (HI-NL; healthinnovation.nl), Dutch Ministry of Health
• Adjunct Professor of Clinical Epidemiology, Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, USA. (since 2005)
• Staff member Cochrane Netherlands.
• Member of the Methods Exec of Cochrane International.
• Convenor of Cochrane's Prognosis Methods Group.
• Editor-in-chief BMC Diagnostic and Prognostic Research.
• Editor-in-Chief Cochrane Handbook for Reviews of Prognosis Studies

Recent former Positions (a selection).

• Chair of the national advisory committee Digital Technology Covid-19 Combat of the Dutch Ministry of Health.
• Chair of Dutch ‘Reporting and Expert center for side-effects of Implants’, Dutch Ministry of Health
• Board of directors, Julius Center of Health Sciences and Primary Care, UMC, Utrecht (2011-2018)
• Adjunct Professor of Clinical Epidemiology, University of Oxford, Oxford, UK (2017-2022)
• Visiting Professor, Tokai University, Isehara, Japan (2005-2010)
• Chair Committee Introduction of Technology in Healthcare, Council for Medical Advices, the Royal Netherlands Academy of Arts and Sciences (2012-2015)
• Member of the Dutch Health Council (2016-2024)
• Visiting Professor, McGill University, Canada (2008).

Career Summary

Carl Moons is professor of Clinical Epidemiology and former director of research at the Julius Center, UMC Utrecht (www.juliuscenter.nl). He is also figure head Artificial Intelligence for Health of the UMC Utrecht and Utrecht University, developed the AI strategy of the UMC Utrecht and established 5 dedicated AI labs (AI Living Technologies and Regenerative Medicine; AI Molecular Medicine; AI Imaging and Imaging guided interventions; AI Methods and Fundamentals; AI Healthy Living and Prevention).

He has directed and co-written the development of an international quality guideline for introduction of safe and effective AI in Healthcare (see https://guideline-ai-healthcare.com) which has been adopted in various countries. He leads two large international consortia which develop guidelines for AI in Healthcare: the TRIPOD+AI guideline for transparent and explainable reporting of AI in healthcare (see www.tripod-statement.org); and the PPROBAST+AI guideline on the assessment of quality and validity of AI algorithms in healthcare (see www.probast.org).

Carl Moons is also co-initiator and co-director of the Health Innovation Netherlands (HI-NL) infrastructure (see www.healthinnovation.nl). HINL is a unique nationwide infrastructure aiming to bring new bio-medical technologies as soon as possible to the market, to ensure for a sustainable, safe, effective, affordable and profitable MedTech and Biotech ecosystem. These biomedical innovations range from robotics, medical diagnostic and screening tests to biomarkers, decisions aids, AI algorithms and eHealth applications. HINL is established and executed by all stakeholders involved in the MedTech and Biotech field including innovators (private and public), insurers, healthcare professionals, patient and citizen organizations, competent authorities, health policy organizations and HTA specialists.

Carl Moons is former chair of the Dutch ‘Reporting and Expert center for side-effects of Implants’ (Meldpunt en Expertisecentrum Bijwerkingen Implantaten: MEBI). Furthermore, he chaired the Royal Netherlands Academy of Arts and Sciences (KNAW) committee ‘Evaluation of new technology in healthcare’. He chaired during the covid-19 pandemic the national advisory committee for the Dutch Ministry of Health on ‘Digital Solutions to Control Covid-19’.

His scientific career (>750 peer reviewed publications, books and book chapters) focuses on research on the methods for the evaluation and introduction of medical innovations, ranging from medical drugs, robotics, tests, eHealth and AI-algorithms. He is principal investigator in numerous international clinical (epidemiology) studies funded by various national and international organisations (EU, NHS, NIH). His experience covers the full range of conduct, data analysis, reporting and dissemination of such studies, varying from studies on the evaluation of medical devices and tests for diagnosis, prognosis, screening and monitoring, to etiological studies and randomised therapeutic trials, to meta-epidemiological studies, both on aggregate and individual participant data. His main focus concerns improving the methods and approaches for evaluation and implementation of medical devices, (bio)markers and prediction models. His major expertise is introducing innovations for the design, conducting, analysis and reporting of evaluations of diagnostic and prognostic tests, devices, (bio)markers and prediction models. Clinical topics include cancer, deep vein thrombosis, stroke, heart failure and peri-operative risk assessment. He teaches graduate and postgraduate students in all aspects of clinical (epidemiological) research design, conducting, analysis and reporting, throughout the world.

Indicators of Research Excellence

Over his career Professor Moons has published over 750 peer-reviewed publications (including scientific papers, books and book chapters) with >30,000 citations. He has obtained numerous (methodological and applied) research grants, including large prestigious personal grants (in summary over 20 million euro as (co-)PI). The (societal) impact of his research record has also been recognised by his memberships of, e.g., Dutch Health Council, Chair of Committee of the Royal Netherlands Academy of Arts and Sciences, membership of numerous committees of Dutch Scientific Organisations and the Dutch Ministry of Health, and interviews for national and internal news magazines. He also teaches bachelor, master, post-doctoral students in clinical research across the world, including Asia and Africa.

Top 20 career publications

• Moons, KG, Collins GS, Dhiman P, et al. TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods. BMJ. 2024 Apr 16;385:e078378. doi: 10.1136/bmj-2023-078378.
• LIFE-CVD2 Working Group. Prediction of individual lifetime cardiovascular risk and potential treatment benefit: development and recalibration of the LIFE-CVD2 model to four European risk regions. Eur J Prev Cardiol. 2024 May 16:zwae174. doi: 10.1093/eurjpc/zwae174. PMID: 38752762.
• Andaur Navarro CL, Damen JAA, …, Moons KGM, Hooft L. SPIN-PM: a consensus framework to evaluate the presence of spin in studies on prediction models. J Clin Epidemiol. 2024 Apr 15;170:111364. doi: 10.1016/j.jclinepi.2024.111364.
• van Smeden M, Heinze G, …, Moons KGM. Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease. Eur Heart J. 2022 May 26:ehac238. doi: 10.1093/eurheartj/ehac238.
• de Hond AAH, Leeuwenberg AM, …., Moons KGM. Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a scoping review. NPJ Digit Med. 2022 Jan 10;5(1):2. doi: 10.1038/s41746-021-00549-7.
• Wynants L, Van Calster B, Collins GS, … Hooft L, Moons KGM, van Smeden M. Prediction models for diagnosis and prognosis of covid-19: systematic review and critical appraisal. BMJ. 2020 Apr 7;369:m1328. doi: 10.1136/bmj.m1328. Update in: BMJ. 2021 Feb 3;372:n236.
• van Smeden M, Reitsma JB, Riley RD, Collins GS, Moons KG. Clinical prediction models: diagnosis versus prognosis. J Clin Epidemiol. 2021 Apr;132:142-145. doi: 10.1016/j.jclinepi.2021.01.009. 
• Schuit E, Veldhuijzen IK, Venekamp RP, van den Bijllaardt W, Pas SD, Lodder EB, Molenkamp R, GeurtsvanKessel CH, Velzing J, Huisman RC, Brouwer L, Boelsums TL, Sips GJ, Benschop KSM, Hooft L, van de Wijgert JHHM, van den Hof S, Moons KGM. Diagnostic accuracy of rapid antigen tests in asymptomatic and presymptomatic close contacts of individuals with confirmed SARS-CoV-2 infection: cross sectional study. BMJ. 2021 Jul 27;374:n1676. doi: 10.1136/bmj.n1676. 
• Damen JAAG, Hooft L, Moons KGM. Contemporary cardiovascular risk prediction. Lancet. 2018 May 12;391(10133):1867-1868. doi: 10.1016/S0140-6736(18)30842-0. 
• Moons KGM, Wolff RF, Riley RD, Whiting PF, Westwood M, Collins GS, Reitsma JB, Kleijnen J, Mallett S; PROBAST Group†. PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies. Ann Intern Med. 2019 Jan 1;170(1):51-58. doi: 10.7326/M18-1376..
• Moons KGM, Wolff RF, Riley RD, Whiting PF, Westwood M, Collins GS, Reitsma JB, Kleijnen J, Mallett S. PROBAST: A Tool to Assess Risk of Bias and Applicability of Prediction Model Studies: Explanation and Elaboration. Ann Intern Med. 2019 Jan 1;170(1):W1-W33. doi: 10.7326/M18-1377.
• Riley RD, Snell KI, Ensor J, Burke DL, Harrell FE Jr, Moons KG, Collins GS. Minimum sample size for developing a multivariable prediction model: PART II - binary and time-to-event outcomes. Stat Med. 2019 Mar 30;38(7):1276-1296. doi: 10.1002/sim.7992.
• van Smeden M, Moons KG, de Groot JA, Collins GS, Altman DG, Eijkemans MJ, Reitsma JB. Sample size for binary logistic prediction models: Beyond events per variable criteria. Stat Methods Med Res. 2019 Aug;28(8):2455-2474. doi: 10.1177/0962280218784726.
• Moons KG, Hooft L, Williams K, Hayden JA, Damen JA, Riley RD. Implementing systematic reviews of prognosis studies in Cochrane. Cochrane Database Syst Rev. 2018 Oct 11;10:ED000129. doi: 10.1002/14651858.ED000129
• Debray TP, Damen JA, Snell KI, Ensor J, Hooft L, Reitsma JB, Riley RD, Moons KG. A guide to systematic review and meta-analysis of prediction model performance. BMJ. 2017 Jan 5;356:i6460. doi: 10.1136/bmj.i6460.
• Moons KG, Altman DG, Reitsma JB, Ioannidis JP, Macaskill P, Steyerberg EW, Vickers AJ, Ransohoff DF, Collins GS. Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med 2015; 162(1): W1-73.
• Collins GS, Reitsma JB, Altman DG, Moons KGM. Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement. Ann Int Med 2015; 162: 55-63.
• Steyerberg EW, Moons KGM, Windt DA van der, Hayden JA, Perel P, Schroter S, et al. Prognosis Research Strategy (PROGRESS) 3: prognostic model research. Plos Med 2013; 10(2): e1001381.
• Altman DG, Vergouwe Y, Royston P, Moons KGM. Prognosis and prognostic research: Validating a prognostic model. BMJ Online 2009; 338: 1432-5.
• Moons KGM, Groot JA de, Bouwmeester W, Vergouwe Y, Mallett S, Altman DG, Reitsma JB, Collins GS. Critical appraisal and data extraction for systematic reviews of prediction modelling studies: the CHARMS checklist. PLoS Med 2014;11(10): e1001744.
• Moons KGM, Royston P, Vergouwe Y, Grobbee DE, Altman DG. Prognosis and prognostic research: What, why, and how? BMJ Online 2009; 338: 1317-20.
• Moons KGM, Kengne AP, Woodward M, Royston P, Vergouwe Y, Altman DG, Grobbee DE. Risk prediction models: I. Development, internal validation, and assessing the incremental value of a new (bio)marker) Heart 2012; 98: 683-90.
• Moons KGM. Criteria for scientific evaluation of novel markers: a perspective. Clin Chem 2010; 56(4): 537-41.

Awards and Grants (a brief selection)

ZonMw  personal grant (VICI): A different view on diagnostic research: a framework for studying the differential diagnosis and diseases with an imperfect or missing reference test (ZonMw VICI 016.106.615).

ZonMw Personal Grant (TOP): Clinical prediction rules: towards a framework for meta-analysis, validation, and updating (ZONMW 40-00812-98-08004).

ZON-MW personal grant (VIDI): Diagnostic prediction rules: how to improve their applicability in clinical practice (ZON-MW VIDI 016.046.360).

ZonMw VISTA grant: Cost-effectiveness of tailoring anticoagulant therapy by D-Dimer testing in patients with venous thromboembolism compared to care-as-usual: VISTA study (ZONMW 80-82310-97-10062).

Current / recent grant income – As (Co-)principal investigator over the past ten years over 20 million euro.

Collaborative Track Record

Karel Moons is (co-)principal investigator in numerous international clinical (epidemiology) studies funded by various organisations (EU, NHS, NIH, Cochrane) and member of various international research consortia (including EPIC-CVD, IMI projects, FP7 and Horizons 2020 projects, TRIPOD, PROBAST, EQUATOR).

Contribution to Scientific and Community Engagement

Over his career Professor Moons has published over 600 peer-reviewed papers and book chapters, and teaches his work to bachelor, master and post-doctoral students all over the world. Besides, his (societal) impact is evident from his various memberships of Dutch Health Council committees, Chair of Committee of the Royal Netherlands Academy of Arts and Sciences, membership of numerous committees of Dutch Scientific Organisations, and interviews for national and internal news magazines.