Economic Evaluation in the <i>Journal of Clinical Oncology</i>: Past, Present, and Future
Authors: Mark N. Levine, Patricia A. Ganz, Daniel G. Haller
Journal: Journal of Clinical Oncology (2007)

There is much excitement in the oncology community with the recent emergence of molecular targeted therapies, such as rituxumab, trastuzumab, and bevacizumab. Such therapy, however, comes at considerable cost, and we know that there are many more new agents in the pipeline. All countries, irrespective of their health care system, are struggling with how to cope with the existing and further increasing financial burden caused by cancer and its treatment. Oncologists find themselves in a difficult position. On the one hand, as prescribers they can be put in a position of gatekeepers; on the other, they are advocates for their patients. Given that these competing roles occur on a daily basis, it is important that the Journal of Clinical Oncology publish studies on economic evaluation for the readership. Since 2000, the JCO has published approximately five articles per year on economic-related issues. As editors, we have considered—and sometimes struggled with—a number of issues when assessing economic articles. We would briefly like to review some of these issues, to provide some guidance to researchers on the type of manuscript in which we are interested. First, the question should be important and relevant. From time-to-time, we receive an economic analysis for a treatment that has been used for a long time and is based on high quality evidence, such as radiation after breast-conservation surgery. The results of the economic analysis are used to justify the use of the therapy (ie, it’s cheap so it is worth giving). This type of economic research is of low priority for the JCO because the treatment will be used anyways. In contrast, a research article examining resource allocation if such therapy was discontinued, thus freeing up resources for other treatments would be of interest. Second, the design of the study needs to be considered. The least rigorous in the design hierarchy is an article that merely describes the cost of an intervention without a comparator. This type of study is also of low priority for the JCO. As we move up the hierarchy we go from cost minimization, to cost effectiveness (C/ E), and to cost utility analysis. These three designs involve a comparison between two interventions— usually something new compared with a standard that provides some form of benchmark. We sometimes receive articles where decision analysis is used to compare different therapeutic strategies. We would prefer to see data from a randomized trial that addresses the question, but there are situations where a randomized trial will not be done and a decision analysis using the best available evidence can be helpful. A decision analysis can also be used to describe in a very analytic fashion the comparison of alternative therapies where there is a trade-off between efficacy and toxicity and the answer is not clear cut. Although a decision analysis can help one think through a complex problem, it might be argued that an experienced clinician presents the information on benefits and risks of treatment to a patient in every day practice to elicit a patient preference. The third issue to consider is the quality of the data used in the economic analysis. The best outcome data come from randomized trials. Usually the publications of randomized trials provide data on efficacy (mortality and recurrence) and toxicity. However, economic data (costs and consequences as measured depending on the method used; for example, utilities) are seldom collected prospectively in clinical trials because of the added cost. We would encourage that researchers try and collect economic data prospectively in trials. However, often costs and consequences are obtained from other sources. Although this may be a necessity, it is not optimal. Assumptions are often made to convert toxicity and quality of life into outcome measures such as utilities. This process needs to be data driven, but is still a best guess. For example, the limitations of utility values based on the opinions of volunteers or experts who have actually not experienced the intervention need to be recognized. Economic evaluation that uses efficacy data from nonrandomized studies can be problematic because of the potential for bias. The reader needs to be aware that the economic analysis output, such as C/E ratio, is only as good as the data that is put into the analysis. If the JCO has already published the main results on efficacy of a trial and a good companion economic study is done, we would be interested in publishing it. We also receive what we call “What if?” articles. The data on efficacy and toxicity entered into the economic analysis are based on a randomized trial with relatively short follow-up. However, the base case analysis is done by letting the model (often a Markov model) run into the future 10 or 15 years, assuming the benefit of the new therapy continues into the future. If the base case analysis was performed with the actual short follow-up, the C/E ratio is often very high and not acceptable. If the initial, very promising results hold, then with longer follow-up the C/E ratio is favorable. JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L VOLUME 25 NUMBER 6 FEBRUARY 2