Development and validation of a prognostic model for survival time data: application to prognosis of HIV positive patients treated with antiretroviral therapy
- 9 July 2004
- journal article
- research article
- Published by Wiley in Statistics in Medicine
- Vol. 23 (15), 2375-2398
- https://doi.org/10.1002/sim.1825
Abstract
The process of developing and validating a prognostic model for survival time data has been much discussed in the literature. Assessment of the performance of candidate prognostic models on data other than that used to fit the models is essential for choosing a model that will generalize well to independent data. However, there remain difficulties in current methods of measuring the accuracy of predictions of prognostic models for censored survival time data. In this paper, flexible parametric models based on the Weibull, loglogistic and lognormal distributions with spline smoothing of the baseline log cumulative hazard function are used to fit a set of candidate prognostic models across k data sets. The model that generalizes best to new data is chosen using a cross‐validation scheme which fits the model on k–1 data sets and tests the predictive accuracy on the omitted data set. The procedure is repeated, omitting each data set in turn. The quality of the predictions is measured using three different methods: two commonly proposed validation methods, Harrell's concordance statistic and the Brier statistic, and a novel method using deviance differences. The results show that the deviance statistic is able to discriminate between quite similar models and can be used to choose a prognostic model that generalizes well to new data. The methods are illustrated by using a model developed to predict progression to a new AIDS event or death in HIV‐1 positive patients starting antiretroviral therapy. Copyright © 2004 John Wiley & Sons, Ltd.This publication has 39 references indexed in Scilit:
- Construction and validation of a prognostic model across several studies, with an application in superficial bladder cancerStatistics in Medicine, 2004
- A new measure of prognostic separation in survival dataStatistics in Medicine, 2004
- Predictive accuracy and explained variationStatistics in Medicine, 2003
- Bayesian Measures of Model Complexity and FitJournal of the Royal Statistical Society Series B: Statistical Methodology, 2002
- Flexible parametric proportional‐hazards and proportional‐odds models for censored survival data, with application to prognostic modelling and estimation of treatment effectsStatistics in Medicine, 2002
- Insights into the reasons for discontinuation of the first highly active antiretroviral therapy (HAART) regimen in a cohort of antiretroviral naïve patientsAIDS, 2000
- The changing pattern of admissions to a London hospital of patients with HIV: 1988-1997AIDS, 1999
- How Biased is the Apparent Error Rate of a Prediction Rule?Journal of the American Statistical Association, 1986
- A new look at the statistical model identificationIEEE Transactions on Automatic Control, 1974
- VERIFICATION OF FORECASTS EXPRESSED IN TERMS OF PROBABILITYMonthly Weather Review, 1950