Current Challenges in Health Economic Modeling of Cancer Therapies: A Research Inquiry

Cancer is the second most common cause of death in the United States, currently accounting for nearly 1 of every 4 deaths annually.1 Not surprising, the development of innovative cancer treatments is an important focus of pharmaceutical drug development. The payoff has been meaningful, with new treatments helping to significantly increase cancer survival among men and women and in nearly all racial and ethnic groups.2,3 This improvement, however, has come at a considerable expense; the total direct medical spending on cancer care in the United States is estimated to have cost as much as $124.5 billion in 2010, with estimated expenditures of almost $160 billion by 2020.4 The cost of new cancer therapies has garnered the attention of a diverse constituency of patients, clinicians, healthcare payers, and public policymakers.5 As decision makers struggle for ways to better manage their budgets while providing the best care possible to patients with cancer, there is a pressing need to assess the value of cancer treatments in a rigorous and robust manner. Of course, the question about what constitutes “value” in cancer care is a topic of ongoing discussion at all levels. Fundamentally, value is defined as the health outcomes achieved per dollar spent, but there is no universally accepted definition of what good value—or even acceptable value—means in cancer care.6,7 Value means something different to each stakeholder, whether a patient with cancer or a caregiver, a physician treating patients with cancer, a healthcare payer, or another medical decision maker. KEY POINTS ▸ As innovative, high-cost cancer therapies continue to come to market, economic modeling is needed to provide better insight into the meaning of value. ▸ Despite the refining of modeling the cost-effectiveness and budget impact of cancer therapies, serious methodologic and policy challenges remain concerning the adequacy of modeling as a sound decision-making tool in oncology. ▸ This article is a call to action, addressing 4 key concerns related to economic modeling in oncology. ▸ Some oncology model outcomes lack practical meaning, and model developers need to focus on informing practical decision-making. ▸ Cost analyses should emphasize clinically meaningful rather than statistically significant outcomes. ▸ Appropriate and robust biologic, epidemiologic, and economic data from larger trials are needed to provide meaningful parameters for oncology economic modeling. ▸ Oncology economic models must keep pace with changing treatment paradigms, and must reflect real-world value. ▸ Models should also address the off-label use of cancer treatments vis-a-vis personalized medicine. ▸ As personalized medicine in oncology changes, models will need to connect economic outcomes more directly with patient outcomes. As innovative new cancer therapies come to market bearing high price tags, the need for economic modeling to help provide better insight into what constitutes “value” is of paramount importance. Yet, after nearly 2 decades of cultivating and refining techniques for the modeling of cost-effectiveness and budget impact of cancer therapies—the 2 main economic models used for evaluating cancer therapies (Table 1)—serious methodologic and policy challenges have emerged that bring into question the adequacy of economic modeling, as it currently stands, as a sound decision-making tool in oncology. Table 1 The 2 Health Economic Models Primarily Used in the Evaluation of Cancer Therapies As an ongoing research endeavor, in this article we are exploring some of the contentious issues in the development and use of oncology economic models as informative tools in current healthcare decision-making. Our goal is to draw attention to these complex pharmacoeconomic concerns and to promote discussion among the various stakeholders regarding the need for improvements in, and the best practices for, oncology economic modeling.