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Difference in Restricted Mean Survival Time for Cost-Effectiveness Analysis Using Individual Patient Data Meta-Analysis: Evidence from a Case Study

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  • Béranger Lueza
  • Audrey Mauguen
  • Jean-Pierre Pignon
  • Oliver Rivero-Arias
  • Julia Bonastre
  • MAR-LC Collaborative Group

Abstract

Objective: In economic evaluation, a commonly used outcome measure for the treatment effect is the between-arm difference in restricted mean survival time (rmstD). This study illustrates how different survival analysis methods can be used to estimate the rmstD for economic evaluation using individual patient data (IPD) meta-analysis. Our aim was to study if/how the choice of a method impacts on cost-effectiveness results. Methods: We used IPD from the Meta-Analysis of Radiotherapy in Lung Cancer concerning 2,000 patients with locally advanced non-small cell lung cancer, included in ten trials. We considered methods either used in the field of meta-analysis or in economic evaluation but never applied to assess the rmstD for economic evaluation using IPD meta-analysis. Methods were classified into two approaches. With the first approach, the rmstD is estimated directly as the area between the two pooled survival curves. With the second approach, the rmstD is based on the aggregation of the rmstDs estimated in each trial. Results: The average incremental cost-effectiveness ratio (ICER) and acceptability curves were sensitive to the method used to estimate the rmstD. The estimated rmstDs ranged from 1.7 month to 2.5 months, and mean ICERs ranged from € 24,299 to € 34,934 per life-year gained depending on the chosen method. At a ceiling ratio of € 25,000 per life year-gained, the probability of the experimental treatment being cost-effective ranged from 31% to 68%. Conclusions: This case study suggests that the method chosen to estimate the rmstD from IPD meta-analysis is likely to influence the results of cost-effectiveness analyses.

Suggested Citation

  • Béranger Lueza & Audrey Mauguen & Jean-Pierre Pignon & Oliver Rivero-Arias & Julia Bonastre & MAR-LC Collaborative Group, 2016. "Difference in Restricted Mean Survival Time for Cost-Effectiveness Analysis Using Individual Patient Data Meta-Analysis: Evidence from a Case Study," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-12, March.
    • Handle: RePEc:plo:pone00:0150032
    DOI: 10.1371/journal.pone.0150032
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    References listed on IDEAS

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    1. Jackson Christopher H & Sharples Linda D & Thompson Simon G, 2010. "Survival Models in Health Economic Evaluations: Balancing Fit and Parsimony to Improve Prediction," The International Journal of Biostatistics, De Gruyter, vol. 6(1), pages 1-31, October.
    2. Craig C. Earle & George A. Wells, 2000. "An Assessment of Methods to Combine Published Survival Curves," Medical Decision Making, , vol. 20(1), pages 104-111, January.
    3. Anell, Anders & Norinder, Anna, 2000. "Health outcome measures used in cost-effectiveness studies: a review of original articles published between 1986 and 1996," Health Policy, Elsevier, vol. 51(2), pages 87-99, March.
    4. Gavin B Stewart & Douglas G Altman & Lisa M Askie & Lelia Duley & Mark C Simmonds & Lesley A Stewart, 2012. "Statistical Analysis of Individual Participant Data Meta-Analyses: A Comparison of Methods and Recommendations for Practice," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-8, October.
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