Systematic reviews of prediction modelling studies: designing, critical appraisal and data collection

Moons K1, Hooft L2, Reitsma J3, Altman D4, Riley R5, Hayden J6, Williams K7, Woolfenden S8
1University Medical Center Utrecht, 2Dutch Cochrane Centre, 3Julius Center, University Medical Center Utrecht , 4Centre for Statistics in Medicine, University of Oxford, United Kingdom, 5University of Birmingham, United Kingdom, 6Dalhousie University, Canada, 7University of Melbourne and The Royal Children’s Hospital Melbourne, Australia, 8Sydney Children’s Hospitals Network and University of New South Wales, Australia


This workshop will introduce participants to the critical appraisal and data extraction in systematic reviews of prediction modelling studies. We will discuss and provide guidance on how to define a proper review question, how to critically appraise primary prediction modelling studies, and which data to extract and why. We will illustrate the guidance using real examples.


Prognostic prediction models are developed and validated for predicting the future occurrence of a particular outcome. Publications on prediction models have become abundant in the literature. Hence, systematic reviews of these studies are increasingly required and conducted, to identify and critically appraise the existing evidence. There is currently no checklist or tool providing guidance for systematic reviews of studies developing and/or validating prediction models that can assist authors to define the review objectives and appraise the primary studies. We discuss the key items important for framing the review question, and related items for critical appraisal.

In this workshop we will discuss the use of the CHARMS checklist that was recently developed to assist authors in framing their review objective, and to critically appraise primary studies on the development and/or validation of prediction models.