Modeling the economic outcomes of immuno-oncology drugs: alternative model frameworks to capture clinical outcomes

Economic models in oncology are commonly based on the three-state partitioned survival model (PSM) distinguishing between progression-free and progressive states. However, the heterogeneity of responses observed in immuno-oncology (I-O) suggests that new approaches may be appropriate to reflect dise...

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Bibliographic Details
Published in:ClinicoEconomics and outcomes research 2018-01, Vol.10, p.139-154
Main Authors: Gibson, E J, Begum, N, Koblbauer, I, Dranitsaris, G, Liew, D, McEwan, P, Tahami Monfared, A A, Yuan, Y, Juarez-Garcia, A, Tyas, D, Lees, M
Format: Article
Language:English
Subjects:
Cancer therapies
Clinical outcomes
Clinical trials
Confidence intervals
Cost analysis
dacarbazine
Drugs
Economic models
Epidemiology
Health care
Immuno-oncology
Immunotherapy
Markov
Medical prognosis
Melanoma
Metastasis
metastatic melanoma
Monoclonal antibodies
nivolumab
Oncology
Original Research
partitioned survival
Patients
Skin cancer
Survival analysis
Targeted cancer therapy
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Summary:Economic models in oncology are commonly based on the three-state partitioned survival model (PSM) distinguishing between progression-free and progressive states. However, the heterogeneity of responses observed in immuno-oncology (I-O) suggests that new approaches may be appropriate to reflect disease dynamics meaningfully. This study explored the impact of incorporating immune-specific health states into economic models of I-O therapy. Two variants of the PSM and a Markov model were populated with data from one clinical trial in metastatic melanoma patients. Short-term modeled outcomes were benchmarked to the clinical trial data and a lifetime model horizon provided estimates of life years and quality adjusted life years (QALYs). The PSM-based models produced short-term outcomes closely matching the trial outcomes. Adding health states generated increased QALYs while providing a more granular representation of outcomes for decision making. The Markov model gave the greatest level of detail on outcomes but gave short-term results which diverged from those of the trial (overstating year 1 progression-free survival by around 60%). Increased sophistication in the representation of disease dynamics in economic models is desirable when attempting to model treatment response in I-O. However, the assumptions underlying different model structures and the availability of data for health state mapping may be important limiting factors.
ISSN:1178-6981
1178-6981
DOI:10.2147/CEOR.S144208