Difference in restricted mean survival time for cost-effectiveness analysis using individual patient data meta-analysis: Evidence from a case study

MAR-LC Collaborative Group

Research output: Contribution to journalArticle

7 Scopus citations

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 metaanalysis is likely to influence the results of cost-effectiveness analyses.

Original languageEnglish (US)
Article numbere0150032
JournalPloS one
Volume11
Issue number3
DOIs
StatePublished - Mar 2016

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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