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Clinicoecon Outcomes Res. 2018 Mar 8;10:139-154. doi: 10.2147/CEOR.S144208. eCollection 2018.

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

Author information

Wickenstones Ltd, Didcot, UK.
Augmentium Pharma Consulting Inc, Toronto, ON, Canada.
Department of Epidemiology and Preventive Medicine, Alfred Hospital, Monash University, Melbourne, VIC, Australia.
Health Economics and Outcomes Research Ltd, Cardiff, UK.
Bristol-Myers Squibb Canada, Saint-Laurent, QC Canada.
Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, QC, Canada.
Bristol-Myers Squibb, Princeton, NJ, USA.
Bristol-Myers Squibb, Uxbridge, UK.
Bristol-Myers Squibb, Rueil-Malmaison, France.



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.

Materials and methods:

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.


Markov; dacarbazine; immuno therapy; metastatic melanoma; nivolumab; partitioned survival

Conflict of interest statement

Disclosure A Juarez-Garcia, M Lees, AA Tahami Monfared, D Tyas, and Y Yuan were employed by BMS. N Begum, EJ Gibson, and I Koblbauer were employed by Wickenstones Ltd, who were funded by BMS to undertake the research. G Dranitsaris, D Liew, and P McEwan have received consultancy fees and have been reimbursed for travel expenses to attend advisory board meetings related to this research. The authors report no other conflicts of interest related to this work.

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