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Abstract
Background:
External validation of prediction models is highly recommended and increasingly common in the literature. Review of such studies may help to identify whether an existing model is sufficiently accurate across different settings, and how it could be improved further.Objectives:
The aim of this study was to:1. provide guidance for systematically reviewing external validation studies of a prediction model;
2. discuss ‘good practice’ when summarizing validation study results, and
3. provide recommendations for interpreting meta-analysis estimates of model performance.
Here we present several key steps: preparing the study protocol, formulating the search strategy, critical appraisal and risk of bias assessment, quantitative data extraction and preparation, meta-analysis, investigating heterogeneity across studies and reporting of results.