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Prediction models combine values of multiple predictors to estimate an individual’s risk of having a certain outcome or disease (diagnostic models) or developing a future outcome (prognostic models). Systematic reviews are needed to identify existing prediction models for a certain target population or outcome and to summarize their predictive performance and heterogeneity in their performance. Appraising the quality and reporting of a prediction model study is essential. Studies describing the development or validation of a prediction model often do not conform to prevailing methodological standards and key details are often not reported. Meta-analysis of the predictive performance of a specific prediction model from multiple external validation studies of that model is possible, focusing on calibration and discrimination. In this chapter, we describe the types of systematic reviews that can be conducted on prediction model studies and discuss the challenges faced in identifying, appraising, and qualitatively and quantitatively synthesizing these studies.

Original publication

DOI

10.1002/9781119099369.ch18

Type

Chapter

Book title

Systematic Reviews in Health Research: Meta-Analysis in Context: Third Edition

Publication Date

01/01/2022

Pages

347 - 376