Systematic reviews of prognostic studies 1: assessing risk of bias in studies of prediction models using the PROBAST tool

Article type
Authors
Wolff R1, Whiting P2, Moons K3
1Kleijnen Systematic Reviews Ltd
2University of Bristol
3Julius Center for Health Sciences and Primary Care
Abstract
Objectives: Quality assessment of included studies is a crucial step in any systematic review. Review and synthesis of prediction modelling studies is a relatively new and evolving area. The QUIPS (QUality In Prognostic Studies) tool for prognostic factor studies has been recently updated. However, a tool facilitating quality assessment for prediction modelling studies, both for diagnostic and prognostic prediction models, is needed. We have developed PROBAST (Prediction study Risk Of Bias assessment Tool), a tool for assessing the risk of bias and applicability of all types of prediction modelling studies. PROBAST assesses risk of bias and applicability of prediction modelling studies. It consists of five domains (participant selection, outcome, predictors, sample size and flow, analysis) and 22 signalling questions across these domains.
Description:The workshop will be split into two sessions. The first session will give an overview of the development and structure of PROBAST. We have used a Delphi process, including 42 experts in the field of prediction research. The presentation will give an overview of the process of development, the final version of the tool (including the domains covered and signalling questions) and guidance on how to use it. In the second half of the workshop, participants will have the opportunity to experience this new tool first hand and to discuss issues with the creators of PROBAST.