Tools

Moons, K, Wolff, R, Riley, RD ORCID: https://orcid.org/0000-0001-8699-0735, Whiting, P, Westwood, M, Collins, G, Reitsma, J, Kleijnen, J and Mallett, S (2019) PROBAST: a tool to assess risk of bias and applicability of prediction model studies – explanation and elaboration. Annals of Internal Medicine, 170 (1). pp. 1-33.

[img] Text
R Riley - PROBAST.docx - Accepted Version
Restricted to Repository staff only until 22 April 2019.
Available under License Creative Commons Attribution Non-commercial.
Download (702kB) | Request a copy

Abstract

Prediction models in health care use predictors to estimate for an individual the probability that a condition or disease is already present (diagnostic model) or will occur in the future (prognostic model).

Publications on prediction models have become more common in recent years, and competing prediction models frequently exist for the same outcome or target population. Health care providers, guideline developers, and policymakers are often unsure which model to use or recommend, and in which persons or settings. Hence, systematic reviews of these studies are increasingly demanded, required, and performed.

A key part of a systematic review of prediction models is examination of risk of bias and applicability to the intended population and setting. To help reviewers with this process, the authors developed PROBAST (Prediction model Risk Of Bias ASsessment Tool) for studies developing, validating, or updating (for example, extending) prediction models, both diagnostic and prognostic.

PROBAST was developed through a consensus process involving a group of experts in the field. It includes 20 signaling questions across 4 domains (participants, predictors, outcome, and analysis). This explanation and elaboration document describes the rationale for including each domain and signaling question and guides researchers, reviewers, readers, and guideline developers in how to use them to assess risk of bias and applicability concerns. All concepts are illustrated with published examples across different topics. The latest version of the PROBAST checklist, accompanying documents, and filled-in examples can be downloaded from www.probast.org.

Item Type: Article
Additional Information: This is the accepted author manuscript (AAM). The final published version (version of record) is available online via American College of Physicians at http://doi.org/10.7326/M18-1377 - please refer to any applicable terms of use of the publisher.
Uncontrolled Keywords: Bias (Epidemiology); Diagnosis, Evidence-Based Medicine; Multivariable Analysis; Prediction; Prognosis; Reproducibility of Results
Subjects: R Medicine > RA Public aspects of medicine
Divisions: Faculty of Medicine and Health Sciences > Primary Care Health Sciences
Depositing User: Symplectic
Date Deposited: 24 Oct 2018 15:04
Last Modified: 01 Apr 2019 09:39
URI: http://eprints.keele.ac.uk/id/eprint/5457

Actions (login required)

View Item View Item
Altmetric