Objectives: To introduce the design, conduct, data extraction and critical appraisal in systematic reviews of prediction modelling studies. We will discuss and provide guidance on how to define a proper review question and how to design data extraction forms to enhance critical appraisal of primary prediction modelling studies. We will illustrate this using real examples.

Description: Prediction models are developed and validated for predicting current or future occurrence of a particular outcome. Publications on prediction models are abundant, so systematic reviews of these studies are increasingly required and conducted, to identify and critically appraise the existing evidence. A tool has been developed to provide guidance for design and conduct of systematic reviews of studies developing and/or validating prediction models. This assists reviewers to define review objectives, to design the review and the data extraction list to facilitate appraisal of the primary studies. We discuss key items important for framing the review question, and domains with corresponding signalling items for data extraction and critical appraisal.

We discuss use of the CHARMS (Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies) checklist, developed to assist reviewers to frame review objectives, to design reviews, and to formulate data extraction lists to facilitate critical appraisal of the primary studies on development and/or their validation.