Library of risk of bias tools


Study design(s) targeted by the tool Prediction modelsprediction-models
Additional details on designs NA
Tool area Health
Link to the tool Get the PROBAST Tool


Primary publication Wolff RF, Moons KGM, 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. 2019;170(1):51-8.
DOI 10.7326/M18-1376
Guidance document Get the PROBAST guidance

None known – please contact us if you are aware of any training that should be listed here.

Language English

None known – please contact us if you are aware of any translations that should be listed here.

Record last updated 14/08/2023

Related tools and Publications

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Kaiser I, Pfahlberg AB, Mathes S, Uter W, Diehl K, Steeb T, Heppt MV, Gefeller O. Inter-Rater Agreement in Assessing Risk of Bias in Melanoma Prediction Studies Using the Prediction Model Risk of Bias Assessment Tool (PROBAST): Results from a Controlled Experiment on the Effect of Specific Rater Training. Journal of Clinical Medicine. 2023 Mar 2;12(5):1976

Langenhuijsen LF, Janse RJ, Venema E, Kent DM, van Diepen M, Dekker FW, Steyerberg EW, de Jong Y. Systematic meta-review of prediction studies demonstrates stable trends in bias and low PROBAST inter-rater agreement. Journal of Clinical Epidemiology. 2023 May 2.

Venema E, Wessler BS, Paulus JK, Salah R, Raman G, Leung LY, et al. Large-scale validation of the prediction model risk of bias assessment Tool (PROBAST) using a short form: high risk of bias models show poorer discrimination. J Clin Epidemiol. 2021;138:32-9.

Other publications

None known – please contact us if you are aware of any publications that should be listed here.

Key Criteria

Focuses on risk of bias, or makes a distinction between items that assess risk of bias and other aspects of study quality Yes
Offers a method to reach either a domain specific or overall assessment of risk of bias Yes
Tool development involving a range of stakeholders from different disciplines (e.g. methodologists, statisticians, clinicians) Yes
Avoids recommending use of summary numerical quality scores Yes