Statistics in Medicine · 1999 · 72 citations · 0 references
Public HealthBiostatisticsOncologyClinical Classification SystemsSurvival AnalysisKaplan-meier EstimationPrognostic AssessmentSurvival FunctionsSurvival ModelingSurvival OutcomesSurvival PredictionPrognostic ClassificationPrognostic CriteriaPrognostic PredictionRight-censored Survival DataSurvival-based Risk Classification
Prognostic classification schemes are widely used in medicine but lack rigorous evaluation, especially for survival data where assessment methods are largely ad hoc and no common standards exist. The study reviews existing methods and introduces new inaccuracy measures that can be computed in validation studies to evaluate patient‑specific survival probability estimates from prognostic classification schemes. The authors illustrate their approach using a breast‑cancer dataset. The proposed inaccuracy measures remain informative even with misspecified probabilities, are asymptotically unaffected by random censoring, and enable calculation of R²‑type metrics for explained residual variation. © 1999 John Wiley & Sons, Ltd.
Prognostic classification schemes have often been used in medical applications, but rarely subjected to a rigorous examination of their adequacy. For survival data, the statistical methodology to assess such schemes consists mainly of a range of ad hoc approaches, and there is an alarming lack of commonly accepted standards in this field. We review these methods and develop measures of inaccuracy which may be calculated in a validation study in order to assess the usefulness of estimated patient-specific survival probabilities associated with a prognostic classification scheme. These measures are meaningful even when the estimated probabilities are misspecified, and asymptotically they are not affected by random censorship. In addition, they can be used to derive R2-type measures of explained residual variation. A breast cancer study will serve for illustration throughout the paper. Copyright © 1999 John Wiley & Sons, Ltd.