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After developing a prognostic model, it is essential to evaluate the performance of the model in samples independent from those used to develop the model, which is often referred to as external validation. However, despite its importance, very little is known about the sample size requirements for conducting an external validation. Using a large real data set and resampling methods, we investigate the impact of sample size on the performance of six published prognostic models. Focussing on unbiased and precise estimation of performance measures (e.g. the c-index, D statistic and calibration), we provide guidance on sample size for investigators designing an external validation study. Our study suggests that externally validating a prognostic model requires a minimum of 100 events and ideally 200 (or more) events.

Original publication

DOI

10.1002/sim.6787

Type

Journal article

Journal

Statistics in medicine

Publication Date

01/2016

Volume

35

Pages

214 - 226

Addresses

Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Botnar Research Centre, University of Oxford, Windmill Road, Oxford, OX3 7LD, U.K.

Keywords

Humans, Cardiovascular Diseases, Diabetes Mellitus, Type 2, Prognosis, Multivariate Analysis, Models, Statistical, Risk Factors, Sample Size, Databases, Factual, Validation Studies as Topic, Biostatistics