Cost effectiveness of a gene expression score and myocardial perfusion imaging for diagnosis of coronary artery disease.

Journal Article (Journal Article)

BACKGROUND: Over 3 million patients annually present with symptoms suggestive of obstructive coronary artery disease (oCAD) in the United States (US), but a cardiac etiology is found in as few as 10% of cases. Usual care may include advanced cardiac testing with myocardial perfusion imaging (MPI), with attendant radiation risks and increased costs of care. We estimated the cost effectiveness of CAD diagnostic strategies including "no test," a gene expression score (GES) test, MPI, and sequential strategies combining GES and MPI. METHODS: We developed a Markov-based decision analysis model to simulate outcomes and costs in patients presenting to clinicians with symptoms suggestive of oCAD in the US. We estimated quality-adjusted life years (QALYs), total costs, and incremental cost-effectiveness ratios (ICERs) for each strategy. RESULTS: In our base case, the 2-threshold GES strategy is the most cost-effective strategy at a threshold of $100,000 per QALY gained, with an ICER of approximately $72,000 per QALY gained relative to no testing. Myocardial perfusion imaging alone and the 1-threshold strategy are weakly dominated. In sensitivity analysis, ICERs fall as the probability of oCAD increases from the base case value of 15%. The ranking of ICERs among strategies is sensitive to test costs, including the time cost for testing. The analysis reveals ways to improve on prespecified GES thresholds. CONCLUSIONS: Diagnostic testing for oCAD with a novel GES strategy in a 2-threshold model is cost effective by conventional standards. This diagnostic approach is more efficient than usual care of MPI alone or a 1-threshold GES strategy in most scenarios.

Full Text

Duke Authors

Cited Authors

  • Phelps, CE; O'Sullivan, AK; Ladapo, JA; Weinstein, MC; Leahy, K; Douglas, PS

Published Date

  • May 2014

Published In

Volume / Issue

  • 167 / 5

Start / End Page

  • 697 - 706.e2

PubMed ID

  • 24766980

Electronic International Standard Serial Number (EISSN)

  • 1097-6744

Digital Object Identifier (DOI)

  • 10.1016/j.ahj.2014.02.005


  • eng

Conference Location

  • United States