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Oncology

Cost-effectiveness analysis of nivolumab for the treatment of squamous cell carcinoma of the head and neck in the United States

, , , , , , , & show all
Pages 442-447 | Received 09 Aug 2019, Accepted 12 Dec 2019, Published online: 29 Jan 2020
 

Abstract

Aim: To assess the cost-effectiveness of nivolumab monotherapy for recurrent/metastatic (R/M) squamous cell carcinoma of the head and neck (SCCHN) in the US.

Methods: We constructed a cohort-based partitioned survival model for three health states (progression-free, progressed disease, and death). Using overall survival and progression-free survival data from the nivolumab and investigator’s choice (IC) arms of the CheckMate 141 study, the proportion of patients in each health state was estimated by parametric modeling over a 25-year period. Cost, utility, adverse event, and disease management data inputs were obtained from relevant literature and applied to patients in each health state. A scenario analysis was conducted assuming increased uptake of subsequent immunotherapies. A one-way deterministic sensitivity analysis assessed the impact of variation in multiple parameters. A probabilistic sensitivity analysis in which probabilistic distributions were applied to each input during 1,000 model iterations was also conducted.

Results: Total costs incurred were higher with nivolumab ($101,552) than with IC ($38,067). Nivolumab was associated with a higher number of life-years (LY; 1.21) and quality-adjusted life-years (QALYs; 0.89), compared with IC (0.68 and 0.42, respectively). The incremental cost-effectiveness ratio for nivolumab compared with IC was $134,438 per QALY, and this remained qualitatively similar when increased uptake of subsequent immunotherapies was assumed ($129,603 per QALY). Sensitivity analyses supported these findings.

Conclusions: These results suggest that, at a willingness-to-pay threshold of $150,000 per QALY, nivolumab is a cost-effective option for therapy of SCCHN in the US.

JEL CLASSIFICATION CODES:

Transparency

Declaration of funding

This study was sponsored by Bristol-Myers Squibb.

Declaration of financial/other relationships

Robert Haddad has received research funding and/or consulting fees from AstraZeneca, Bristol-Myers Squibb, Genentech, Glenmark, GSK, Immunomic, Kura, Loxo, Merck and Pfizer. Ezra E.W. Cohen has received research funding and/or consulting fees from Amgen, AstraZeneca, Bristol-Myers Squibb, EMD Serono, Incyte, Merck, and Pfizer. Meena Venkatachalam and Kate Young are employees of Parexel, which has received payment from Bristol-Myers Squibb for contracted analyses. Prianka Singh, James W. Shaw, Beata Korytowsky, and Pranav Abraham are employees and shareholders of Bristol-Myers Squibb. Kevin J. Harrington has received research funding and/or consulting fees from Amgen, AstraZeneca, Boehringer Ingelheim, Bristol-Myers Squibb, Merck-Serono, MSD, Oncolys, Pfizer, Replimune, Vyriad. JME peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Author contributions

All authors contributed to the study design. MV and KY developed the model. All authors reviewed the model and data, and contributed critical revisions to the manuscript. All authors agree to be held accountable for the manuscript content, and approve the final version for publication.

Acknowledgements

Under direction of the authors, Martin Bell, PhD, of Evidence Scientific Solutions, Inc., provided writing assistance for this manuscript.