title: Estimation of time-shift models with application to survival calibration in health technology assessment.
abstract: The incremental life expectancy, defined as the difference in mean survival times between two treatment groups, is a crucial quantity of interest in cost-effectiveness analyses. Usually, this quantity is very difficult to estimate from censored survival data with a limited follow-up period. The paper develops estimation procedures for a time-shift survival model that, provided model assumptions are met, gives a reliable estimate of incremental life expectancy without extrapolation beyond the study period. Methods for inference are developed both for individual patient data and when only published Kaplan-Meier curves are available. Through simulation, the estimators are shown to be close to unbiased and constructed confidence intervals are shown to have close to nominal coverage for small to moderate sample sizes. Copyright © 2016 John Wiley & Sons, Ltd.
authors.affiliation: Department of Mathematics and Statistics, Fylde College, Lancaster University, Lancaster, LA1 4DJ, U.K.
authors.forename: Andrew C
authors.identifier: 0000-0003-2084-0720
authors.initials: AC
authors.lastname: Titman
mesh_terms: D002138:Calibration; D003362:Cost-Benefit Analysis; D006801:Humans; D008017:Life Expectancy; D015996:Survival Rate; D013673:Technology Assessment, Biomedical
keywords: cost-effectiveness analysis; health technology assessment; survival analysis; survival extrapolation