The cost-effectiveness of biomarkers for predicting the development of oesophageal adenocarcinoma

Aliment Pharmacol Ther. 2005 Jul 15;22(2):135-46. doi: 10.1111/j.1365-2036.2005.02536.x.

Abstract

Background: The recommended surveillance strategy for oesophageal adenocarcinoma may prevent as few as 50% of cancer deaths. Tissue biomarkers have been proposed to identify high-risk patients.

Aim: To determine performance characteristics of an ideal biomarker, or panel of biomarkers, that would make its use more cost-effective than the current surveillance strategy.

Methods: We created a Markov model using data from published literature, and performed a cost-utility analysis. The population consisted of 50-year-old Caucasian men with gastro-oesophageal reflux, who were monitored until age 80. We examined strategies of observation only, current practice (dysplasia-guided surveillance), surveillance every 3 months for patients with a positive biomarker (biomarker-guided surveillance), and oesophagectomy immediately for a positive biomarker (biomarker-guided oesophagectomy). The primary outcome was the threshold cost and performance characteristics needed for a biomarker to be more cost-effective than current practice.

Results: Regardless of the cost, the biomarker needs to be at least 95% specific for biomarker-guided oesophagectomy to be cost-effective. For biomarker-guided surveillance to be cost-effective, a $100 biomarker could be 80% sensitive and specific.

Conclusions: Biomarkers predicting the development of oesophageal adenocarcinoma would need to be fairly accurate and inexpensive to be cost-effective. These results should guide the development of biomarkers for oesophageal adenocarcinoma.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adenocarcinoma / diagnosis*
  • Adenocarcinoma / economics
  • Biomarkers / blood*
  • Cost-Benefit Analysis
  • Esophageal Neoplasms / diagnosis*
  • Esophageal Neoplasms / economics
  • Humans
  • Male
  • Markov Chains
  • Middle Aged
  • Quality-Adjusted Life Years
  • Sensitivity and Specificity

Substances

  • Biomarkers