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Individual survival time prediction using statistical models

¹ Department of Mathematics & Statistics, Newcastle University, Newcastle NE1 7RU, UK
² Department of Biostatistics, University of Copenhagen, Copenhagen, Denmark; N.Keiding{at}biostat.ku.dk

Correspondence to:
Professor N Keiding
Department of Biostatistics, University of Copenhagen, Øster Farimagsgade 5, entr. B, PO Box 2099, DK-1014, Copenhagen, Denmark; N.Keiding{at}biostat.ku.dk Doctors’ survival predictions for terminally ill patients have been shown to be inaccurate and there has been an argument for less guesswork and more use of carefully constructed statistical indices. As statisticians, the authors are less confident in the predictive value of statistical models and indices for individual survival times. This paper discusses and illustrates a variety of measures which can be used to summarise predictive information available from a statistical model. The authors argue that models and statistical indices can be useful at the group or population level, but that human survival is so uncertain that even the best statistical analysis cannot provide single-number predictions of real use for individual patients.

Abbreviations: AS, actual survival; CPS, clinical prediction of survival; PI, prognostic index

Keywords: prognostic index; category prediction; survival analysis; expected survival

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