Accounting for Cured Patients in Cost-Effectiveness Analysis

Value Health. 2017 Apr;20(4):705-709. doi: 10.1016/j.jval.2016.04.011. Epub 2016 Jun 9.


Background: Economic evaluations often measure an intervention effect with mean overall survival (OS). Emerging types of cancer treatments offer the possibility of being "cured" in that patients can become long-term survivors whose risk of death is the same as that of a disease-free person. Describing cured and noncured patients with one shared mean value may provide a biased assessment of a therapy with a cured proportion.

Objective: The purpose of this article is to explain how to incorporate the heterogeneity from cured patients into health economic evaluation.

Methods: We analyzed clinical trial data from patients with advanced melanoma treated with ipilimumab (Ipi; n = 137) versus glycoprotein 100 (gp100; n = 136) with statistical methodology for mixture cure models. Both cured and noncured patients were subject to background mortality not related to cancer.

Results: When ignoring cured proportions, we found that patients treated with Ipi had an estimated mean OS that was 8 months longer than that of patients treated with gp100. Cure model analysis showed that the cured proportion drove this difference, with 21% cured on Ipi versus 6% cured on gp100. The mean OS among the noncured cohort patients was 10 and 9 months with Ipi and gp100, respectively. The mean OS among cured patients was 26 years on both arms. When ignoring cured proportions, we found that the incremental cost-effectiveness ratio (ICER) when comparing Ipi with gp100 was $324,000/quality-adjusted life-year (QALY) (95% confidence interval $254,000-$600,000). With a mixture cure model, the ICER when comparing Ipi with gp100 was $113,000/QALY (95% confidence interval $101,000-$154,000).

Conclusions: This analysis supports using cure modeling in health economic evaluation in advanced melanoma. When a proportion of patients may be long-term survivors, using cure models may reduce bias in OS estimates and provide more accurate estimates of health economic measures, including QALYs and ICERs.

Keywords: cure models; oncology; overall survival; survival analysis.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Antibodies, Monoclonal / adverse effects
  • Antibodies, Monoclonal / economics*
  • Antibodies, Monoclonal / therapeutic use*
  • Antineoplastic Agents / adverse effects
  • Antineoplastic Agents / economics*
  • Antineoplastic Agents / therapeutic use*
  • Bias
  • Cost-Benefit Analysis
  • Drug Costs*
  • Female
  • Glycoproteins / adverse effects
  • Glycoproteins / economics*
  • Glycoproteins / therapeutic use*
  • Humans
  • Ipilimumab
  • Kaplan-Meier Estimate
  • Male
  • Melanoma / drug therapy*
  • Melanoma / economics*
  • Melanoma / mortality
  • Middle Aged
  • Models, Economic
  • Quality-Adjusted Life Years
  • Randomized Controlled Trials as Topic
  • Remission Induction
  • Skin Neoplasms / drug therapy*
  • Skin Neoplasms / economics*
  • Skin Neoplasms / mortality
  • Survivors
  • Time Factors
  • Treatment Outcome
  • Young Adult


  • Antibodies, Monoclonal
  • Antineoplastic Agents
  • Glycoproteins
  • Ipilimumab