Ex ante economic evaluation of genetic testing for the ARG389 beta1-adrenergic receptor polymorphism to support bucindolol treatment decisions in Stage III/IV heart failure

Research output: Contribution to journalArticle

Abstract

Background: Sub-analyses from the BEST trial in heart failure (HF) indicated that Arg389 homozygote patients may respond to bucindolol. Bucindolol is currently being evaluated in Arg389 genotype patients in the GENETIC-AF trial. Our aim is to conduct ex ante economic evaluations of Arg389 genetic testing to support β-blocker treatment in HF. Methods: Using survival results from two BEST sub-analyses, we constructed a decision-tree model (time-horizon 18 months, divided into three 6-month cycles) to estimate the cost-effectiveness/utility of Arg389 genetic testing with bucindolol or carvedilol versus no testing and empirical bucindolol. Costs of bucindolol and genetic testing were set conservatively at 1.5x carvedilol cost and $250, respectively. Incremental cost-effectiveness (ICER) and cost-utility ratios (ICUR) were estimated. Results: Per one BEST sub-analysis, Arg389 genetic testing was associated with incremental gains of 0.29 life-years (LYs) and 0.27 quality-adjusted life years (QALYs) at incremental costs of $726; yielding ICER of US$2,503/LY and ICUR of US$2,688/QALY gained. Per a different BEST sub-analysis, Arg-389 genetic testing was associated with incremental gains of 0.35LYs and 0.32QALYs at savings of (US$1,081); for ICER of (US$3,089)/LY and ICUR of (US$3,378)/QALY gained. Conclusions: Assuming conservative cost estimates, Arg389 genetic testing to inform bucindolol versus carvedilol treatment decisions prevailed economically over bucindolol treatment without genetic testing.

Original languageEnglish (US)
JournalExpert Review of Precision Medicine and Drug Development
DOIs
StateAccepted/In press - Jan 1 2018

Keywords

  • Arg389
  • beta-blockers
  • cost-effectiveness
  • cost-utility
  • heart failure
  • precision medicine

ASJC Scopus subject areas

  • Pharmacology
  • Drug Discovery
  • Molecular Medicine
  • Genetics

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