title: Individual survival time prediction using statistical models.
abstract: 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.
authors.affiliation: Department of Biostatistics, University of Copenhagen, Øster Farimagsgade 5, entr. B, PO Box 2099, DK-1014, Copenhagen, Denmark.
authors.forename: R
authors.initials: R
authors.lastname: Henderson
authors.forename: N
authors.initials: N
authors.lastname: Keiding
mesh_terms: D002289:Carcinoma, Non-Small-Cell Lung / Q000401:mortality; D005260:Female; D006801:Humans; D008017:Life Expectancy; D008175:Lung Neoplasms / Q000401:mortality; D008297:Male; D011379:Prognosis; D016016:Proportional Hazards Models; D012307:Risk Factors; D019452:Terminally Ill; D013997:Time Factors