Rights statement: This is the peer reviewed version of the following article: Titman, A. C. (2016) Estimation of time-shift models with application to survival calibration in health technology assessment. Statist. Med., 35: 3645–3656. doi: 10.1002/sim.6951. which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/sim.6951/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Estimation of time-shift models with application to survival calibration in health technology assessment
AU - Titman, Andrew Charles
N1 - This is the peer reviewed version of the following article: Titman, A. C. (2016) Estimation of time-shift models with application to survival calibration in health technology assessment. Statist. Med., 35: 3645–3656. doi: 10.1002/sim.6951. which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/sim.6951/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.
PY - 2016/9/10
Y1 - 2016/9/10
N2 - 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 smallto moderate sample sizes.
AB - 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 smallto moderate sample sizes.
KW - survival analysis
KW - Health technology assessment
KW - survival extrapolation
KW - cost-effectiveness analysis
U2 - 10.1002/sim.6951
DO - 10.1002/sim.6951
M3 - Journal article
VL - 35
SP - 3645
EP - 3656
JO - Statistics in Medicine
JF - Statistics in Medicine
SN - 0277-6715
IS - 20
ER -