Royston, P; Sauerbrei, W; (2004) A new measure of prognostic separation in survival data. Statistics in Medicine , 23 (5) 723 - 748. 10.1002/sim.1621.
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Multivariable prognostic models are widely used in cancer and other disease areas, and have a range of applications in clinical medicine, clinical trials and allocation of health services resources. A well-founded and reliable measure of the prognostic ability of a model would be valuable to help define the separation between patients or prognostic groups that the model could provide, and to act as a benchmark of model performance in a validation setting. We propose such a measure for models of survival data. Its motivation derives originally from the idea of separation between Kaplan-Meier curves. We define the criteria for a successful measure and discuss them with respect to our approach. Adjustments for optimism, the tendency for a model to predict better on the data on which it was derived than on new data, are suggested. We study the properties of the measure by simulation and by example in three substantial data sets. We believe that our new measure will prove useful as a tool to evaluate the separation available-with a prognostic model.
|Title:||A new measure of prognostic separation in survival data|
|Additional information:||Imported via OAI, 7:29:01 25th Apr 2008|
|UCL classification:||UCL > School of Life and Medical Sciences > Faculty of Population Health Sciences > MRC Clinical Trials Unit at UCL|
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