What do we mean by validating a prognostic model?

Authors

  • Douglas G. Altman,

    Corresponding author
    1. ICRF Medical Statistics Group, Centre for Statistics in Medicine, Institute of Health Sciences, Old Road, Headington, Oxford OX3 7LF, U.K.
    • ICRF Medical Statistics Group, Centre for Statistics in Medicine, Institute of Health Sciences, Old Road, Headington, Oxford OX3 7LF, U.K.
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  • Patrick Royston

    1. Department of Medical Statistics and Evaluation, Imperial College School of Medicine, Hammersmith Hospital, Ducane Road, London W12 0NN, U.K.
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Abstract

Prognostic models are used in medicine for investigating patient outcome in relation to patient and disease characteristics. Such models do not always work well in practice, so it is widely recommended that they need to be validated. The idea of validating a prognostic model is generally taken to mean establishing that it works satisfactorily for patients other than those from whose data it was derived. In this paper we examine what is meant by validation and review why it is necessary. We consider how to validate a model and suggest that it is desirable to consider two rather different aspects – statistical and clinical validity – and examine some general approaches to validation. We illustrate the issues using several case studies. Copyright © 2000 John Wiley & Sons, Ltd.

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