Objectives
With the development of high priced new targeted treatment for cancer, there is a need to know as soon as possible if these treatments are likely to be cost-effective. The objective of this study was to develop a model with global parameters to estimate the cost-effectiveness of targeted treatments using companion diagnostics in advanced/metastatic cancer treatment.
Methods
The model was developed to take into account parameters usually considered in conventional economic models in cancer (treatment costs, costs of cancer care, target population characteristics, survival data, utilities, disutilities and costs associated with adverse events (AEs), etc. ), and also parameters specific to the companion diagnostic itself (mutation prevalence, test specificity and sensitivity, and cost). The model had to allow performing cost-utility analyses from both a Health Ministry and a societal perspective and for most common cancers (lung, breast, colorectal, prostate, cervical/endometrial, bladder, and non-Hodgkin’s lymphoma).
Results
The global model comprises a decision tree and a lifetime Markov model. The decision tree takes into account the sensitivity and specificity and cost of the companion diagnosis, and the prevalence of the biomarker/mutation in the eligible population. The Markov model with monthly cycles includes the following 3 health states: progression-free, progressive disease and death. Intrisic parameters of the model comprise the mean characteristics of the target population, utilities associated with health states, disutilities and costs associated with AEs, and costs associated with drug administration, cancer care, end-of-life care, follow-up visits, productivity losses, and informal care. Specific parameters to be entered by users are the prevalence of the mutation, treatment costs, specificity/sensitivity and cost of the test, survival data and the incidence of AEs.
Conclusions
The proposed global model for the economic evaluation of targeted treatments using companion diagnostics in advanced/metastatic cancer treatment can, with minimal input, quickly generate cost-effectiveness analyses of targeted cancer treatment.
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© 2014 Published by Elsevier Inc.
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