Robert F. Wolff, MD *; Karel G.M. Moons, PhD *; Richard D. Riley, PhD; Penny F. Whiting, PhD; Marie Westwood, PhD; Gary S. Collins, PhD; Johannes B. Reitsma, MD, PhD; Jos Kleijnen, MD, PhD; Sue Mallett, DPhil; for the PROBAST Group†
Disclaimer: This report presents independent research supported by the National Institute for Health Research (NIHR). The views and opinions expressed in this publication are those of the authors and do not necessarily reflect those of the National Health Service (NHS), the NIHR, or the Department of Health and Social Care.
Acknowledgment: The authors thank the members of the Delphi panel () for their valuable input and all testers, especially Cordula Braun, Johanna A.A.G. Damen, Paul Glasziou, Pauline Heus, Lotty Hooft, and Romin Pajouheshnia, for providing feedback on PROBAST. They also thank Janine Ross and Steven Duffy for support in managing the references.
Financial Support: Drs. Moons and Reitsma received financial support from the Netherlands Organisation for Scientific Research (ZONMW 918.10.615 and 91208004). Dr. Riley is a member of the Evidence Synthesis Working Group funded by the NIHR School for Primary Care Research (project 390). Dr. Whiting (time) was supported by the NIHR Collaboration for Leadership in Applied Health Research and Care West at University Hospitals Bristol NHS Foundation Trust. Dr. Collins was supported by the NIHR Biomedical Research Centre, Oxford. Dr. Mallett is supported by NIHR Birmingham Biomedical Research Centre at the University Hospitals Birmingham NHS Foundation Trust and the University of Birmingham. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Disclosures: Dr. Wolff reports grants from Bayer, Biogen, Pfizer, UCB, Amgen, BioMarin, Grünenthal, Chiesi, and TESARO outside the submitted work. Dr. Westwood reports grants from Bayer, Biogen, Pfizer, UCB, Amgen, BioMarin, Grünenthal, Chiesi, and TESARO outside the submitted work. Dr. Kleijnen reports grants from Bayer, Biogen, Pfizer, UCB, Amgen, BioMarin, Grünenthal, Chiesi, and TESARO outside the submitted work. Authors not named here have disclosed no conflicts of interest. Disclosures can also be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M18-1376.
Corresponding Author: Robert F. Wolff, MD, Kleijnen Systematic Reviews Ltd, Unit 6, Escrick Business Park, Riccall Road, Escrick, York YO19 6FD, United Kingdom; e-mail, firstname.lastname@example.org.
Current Author Addresses: Drs. Wolff, Westwood, and Kleijnen: Kleijnen Systematic Reviews Ltd, Unit 6, Escrick Business Park, Riccall Road, Escrick, York YO19 6FD, United Kingdom.
Drs. Moons and Reitsma: Julius Centre for Health Sciences and Primary Care, UMC Utrecht, Utrecht University, PO Box 85500, 3508 GA Utrecht, the Netherlands.
Dr. Riley: Centre for Prognosis Research, Research Institute for Primary Care and Health Sciences, Keele University, Staffordshire ST5 5BG, United Kingdom.
Dr. Whiting: NIHR CLAHRC West, University Hospitals Bristol NHS Foundation Trust and School of Social and Community Medicine, University of Bristol, Bristol BS1 2NT, United Kingdom.
Dr. Collins: Centre for Statistics in Medicine, NDORMS, University of Oxford, Botnar Research Centre, Windmill Road, Oxford OX3 7LD, United Kingdom.
Dr. Mallett: Institute of Applied Health Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom.
Author Contributions: Conception and design: R.F. Wolff, K.G.M. Moons, R.D. Riley, P.F. Whiting, M. Westwood, G.S. Collins, J.B. Reitsma, J. Kleijnen, S. Mallett.
Analysis and interpretation of the data: R.F. Wolff, K.G.M. Moons, R.D. Riley, P.F. Whiting, M. Westwood, G.S. Collins, J.B. Reitsma, J. Kleijnen, S. Mallett.
Drafting of the article: R.F. Wolff, K.G.M. Moons, P.F. Whiting, M. Westwood, S. Mallett.
Critical revision of the article for important intellectual content: R.F. Wolff, K.G.M. Moons, R.D. Riley, P.F. Whiting, M. Westwood, G.S. Collins, J.B. Reitsma, J. Kleijnen, S. Mallett.
Final approval of the article: R.F. Wolff, K.G.M. Moons, R.D. Riley, P.F. Whiting, M. Westwood, G.S. Collins, J.B. Reitsma, J. Kleijnen, S. Mallett.
Statistical expertise: K.G.M. Moons, R.D. Riley, G.S. Collins, J.B. Reitsma, S. Mallett.
Obtaining of funding: K.G.M. Moons, R.D. Riley, P.F. Whiting, G.S. Collins, J.B. Reitsma, J. Kleijnen, S. Mallett.
Administrative, technical, or logistic support: R.F. Wolff, K.G.M. Moons, J. Kleijnen, S. Mallett.
Collection and assembly of data: R.F. Wolff, K.G.M. Moons, R.D. Riley, P.F. Whiting, M. Westwood, G.S. Collins, J.B. Reitsma, J. Kleijnen, S. Mallett.
Clinical prediction models combine multiple predictors to estimate risk for the presence of a particular condition (diagnostic models) or the occurrence of a certain event in the future (prognostic models).
PROBAST (Prediction model Risk Of Bias ASsessment Tool), a tool for assessing the risk of bias (ROB) and applicability of diagnostic and prognostic prediction model studies, was developed by a steering group that considered existing ROB tools and reporting guidelines. The tool was informed by a Delphi procedure involving 38 experts and was refined through piloting.
PROBAST is organized into the following 4 domains: participants, predictors, outcome, and analysis. These domains contain a total of 20 signaling questions to facilitate structured judgment of ROB, which was defined to occur when shortcomings in study design, conduct, or analysis lead to systematically distorted estimates of model predictive performance. PROBAST enables a focused and transparent approach to assessing the ROB and applicability of studies that develop, validate, or update prediction models for individualized predictions.
Although PROBAST was designed for systematic reviews, it can be used more generally in critical appraisal of prediction model studies. Potential users include organizations supporting decision making, researchers and clinicians who are interested in evidence-based medicine or involved in guideline development, journal editors, and manuscript reviewers.
Types of diagnostic and prognostic modeling studies or reports addressed by PROBAST.
Adopted from the TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) and CHARMS (CHecklist for critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies) guidance (7, 26). PROBAST = Prediction model Risk Of Bias ASsessment Tool.
Differences between diagnostic and prognostic prediction model studies.
PROBAST = Prediction model Risk Of Bias ASsessment Tool.
Table 1. Four Steps in PROBAST
Table 2. PROBAST: Summary of Step 3—Assessment of Risk of Bias and Concerns Regarding Applicability*
Table 3. Suggested Tabular Presentation for PROBAST Results*
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Wolff RF, Moons KG, Riley RD, Whiting PF, Westwood M, Collins GS, et al. PROBAST: A Tool to Assess the Risk of Bias and Applicability of Prediction Model Studies. Ann Intern Med. ;170:51–58. doi: 10.7326/M18-1376
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Published: Ann Intern Med. 2019;170(1):51-58.
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