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Estimating survival gain for economic evaluations with survival time as principal endpoint: A cost‐effectiveness analysis of adding early hormonal therapy to radiotherapy in patients with locally advanced prostate cancer

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  • N. Neymark
  • I. Adriaenssen
  • T. Gorlia
  • S. Caleo
  • M. Bolla

Abstract

The problem of estimating expected outcomes for the economic evaluation of treatments for which the outcome of principal interest is (quality adjusted) survival time has so far not received sufficient attention in the literature. The best estimate of expected survival is mean survival time, but with censored survival data, the true survival time for all the subjects is not known, so the mean is not defined. A possible solution to this estimation problem is illustrated by a retrospective cost‐effectiveness analysis of the addition of hormonal therapy to standard radiotherapy for patients with locally advanced prostate cancer. A recently proposed method is used to approach the problem caused by censored cost data, and the impact of uncertainty is assessed by bootstrap resampling techniques. Mean survival time is estimated by a restricted means analysis with the time point of restriction determined by statistical criteria. When average total costs and mean survival time is evaluated at this time point of restriction, the result is that the combined therapy (radiotherapy plus hormonal therapy) increases mean survival time by about 1 year, while reducing the costs per patient for the French health insurance system by 12 700 FF. The time point of restriction may also be determined by other criteria and mean survival time may be estimated by extrapolating the survival curves by means of various parametric survival distributions. We show that the exact results of the economic evaluation are decisively determined by the restriction time point chosen and the approach taken to estimate mean survival time. Copyright © 2002 John Wiley & Sons, Ltd.

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  • N. Neymark & I. Adriaenssen & T. Gorlia & S. Caleo & M. Bolla, 2002. "Estimating survival gain for economic evaluations with survival time as principal endpoint: A cost‐effectiveness analysis of adding early hormonal therapy to radiotherapy in patients with locally adva," Health Economics, John Wiley & Sons, Ltd., vol. 11(3), pages 233-248, April.
  • Handle: RePEc:wly:hlthec:v:11:y:2002:i:3:p:233-248
    DOI: 10.1002/hec.662
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    References listed on IDEAS

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    1. Andrew Briggs & Paul Fenn, 1998. "Confidence intervals or surfaces? Uncertainty on the cost‐effectiveness plane," Health Economics, John Wiley & Sons, Ltd., vol. 7(8), pages 723-740, December.
    2. Andrew H. Briggs, 1999. "A Bayesian approach to stochastic cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 257-261, May.
    3. Daniel F. Heitjan & Alan J. Moskowitz & William Whang, 1999. "Bayesian estimation of cost‐effectiveness ratios from clinical trials," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 191-201, May.
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    1. M. Barbieri & H. Weatherly & R. Ara & H. Basarir & M. Sculpher & R. Adams & H. Ahmed & C. Coles & T. Guerrero-Urbano & C. Nutting & M. Powell, 2014. "What is the Quality of Economic Evaluations of Non-Drug Therapies? A Systematic Review and Critical Appraisal of Economic Evaluations of Radiotherapy for Cancer," Applied Health Economics and Health Policy, Springer, vol. 12(5), pages 497-510, October.
    2. Luis Mendonça & Julian Perelman & Vanessa Rodrigues & José Fragata, 2014. "Cost-effectiveness of lung transplantation and its evolution: the Portuguese case," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(7), pages 767-772, September.
    3. Nicola J. Cooper & Alex J. Sutton & Keith R. Abrams & David Turner & Allan Wailoo, 2004. "Comprehensive decision analytical modelling in economic evaluation: a Bayesian approach," Health Economics, John Wiley & Sons, Ltd., vol. 13(3), pages 203-226, March.

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