Structural Uncertainty of Markov Models for Advanced Breast Cancer

Quang A. Le

Medical Decision Making, 2016, vol. 36, issue 5, 629-640

Abstract: Objective. To examine the impact of structural uncertainty of Markov models in modeling cost-effectiveness for the treatment of advanced breast cancer (ABC). Methods. Four common Markov models for ABC were identified and examined. Markov models 1 and 2 have 4 health states (stable-disease, responding-to-therapy, disease-progressing, and death), and Markov models 3 and 4 only have 3 health states (stable-disease, disease-progressing, and death). In models 1 and 3, the possibility of death can occur in any health state, while in models 2 and 4, the chance of dying can only occur in the disease-progressing health state. A simulation was conducted to examine the impact of using different model structures on cost-effectiveness results in the context of a combination therapy of lapatinib and capecitabine for the treatment of HER2-positive ABC. Model averaging with an assumption of equal weights in all 4 models was used to account for structural uncertainty. Results. Markov model 3 yielded the lowest incremental cost-effectiveness ratio (ICER) of $303,909 per quality-adjusted life year (QALY), while Markov model 1 produced the highest ICER ($495,800/QALY). At a willingness-to-pay threshold of $150,000/QALY, the probabilities that the combination therapy is considered to be cost-effective for Markov models 1, 2, 3, and 4 were 14.5%, 14.1%, 21.6%, and 17.0%, respectively. When using model averaging to synthesize different model structures, the resulting ICER was $389,270/QALY. Conclusions. Our study shows that modeling ABC with different Markov model structures yielded a wide range of cost-effectiveness results, suggesting the need to investigate structural uncertainty in health economic evaluation. When applied in the context of HER2-positive ABC treatment, the combination therapy with lapatinib is not cost-effective, regardless of which model was used and whether uncertainties were accounted for.

Keywords: Markov models; cost-effectiveness analysis; lapatinib; HER2-positive advanced breast cancer; simulation (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0272989X15622643 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:36:y:2016:i:5:p:629-640

DOI: 10.1177/0272989X15622643

Access Statistics for this article

More articles in Medical Decision Making
Bibliographic data for series maintained by SAGE Publications ().