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What do we mean by validating a prognostic model?

Statistics in Medicine · 2000 · Vol. 19(4) · pp. 453–473
Douglas G. AltmanPatrick Royston

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.

Health Systems, Economic Evaluations, Quality of LifeMeta-analysis and systematic reviewsStatistical Methods in Clinical TrialsComputer scienceOutcome (game theory)Clinical PracticeRelation (database)Model validationMedicineData miningData scienceMathematicsFamily medicine

MeSH terms

Accidental FallsAgedAsthmaDecision Support TechniquesCraniocerebral TraumaHumansMyocardial InfarctionPrognosisProspective StudiesRetrospective StudiesRisk FactorsReproducibility of Results
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