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Ann Thorac Surg 2007;83:1264
© 2007 The Society of Thoracic Surgeons
St. Lukes Health Network, 701 Ostrum St, Suite 201, Bethlehem, PA 18015
(Email: burfeiw{at}slhn.org).
Decision-making surrounding the care of patients with locally advanced esophageal cancer remains complex. This is primarily due to the fact that the available data supporting surgery alone versus multimodal therapy are conflicting. What seems clear is that there is not an overwhelming survival advantage to either therapy and that there are few long-term survivors with this disease. In this setting it seems particularly important to consider health-related quality of life (HRQOL) when performing medical decision-making.
Graham and colleagues [1] are to be congratulated on bringing two powerful medical decision-making tools (ie, meta-analysis and decision analysis) to bear on the optimal therapy for locally advanced esophageal cancer. They used meta-analytic tools and combined the results of 14 randomized control trials to model survival in 6-month intervals for each of four therapies (surgery alone [n = 1,359], chemotherapy plus surgery [n = 737], chemoradiotherapy plus surgery [n = 372], and surgery plus chemotherapy [n = 281]). Cumulative mortality was high, reaching 67% at 36 months in the surgery alone group. Relative risks (RR) were then developed between surgery alone and the other therapies. The therapy with the lowest RR compared with surgery alone was chemoradiotherapy plus surgery, but the confidence intervals for each 6-month time period crossed unity. The probability of dying was then combined with a surrogate for utility to populate the model. A Monte Carlo simulation yielded a mean improved life expectancy of 40 days when a strategy of chemoradiotherapy plus surgery was compared with surgery alone.
Decision analysis is a formal, quantitative method for systematically comparing the benefits and harms of alternative clinical strategies under circumstances of uncertainty. Locally advanced esophageal cancer is a good example of a case scenario in which decision analysis would be valuable. As with all models, however, it must be populated with accurate information. In this article the authors are hindered by the current literature. The results of the studies used to measure survival show a striking lack of homogeneity. The survival times are drawn from studies examining differing histologies, chemotherapeutic regimens, and radiation doses. Within the chemoradiotherapy plus surgery group, less than 26% of the patients had adenocarcinoma, limiting the generalizability in this common subgroup in the United States. The estimation of utility within the model is also problematic. Ideally the HRQOL information would have been obtained from the same randomized control trials from which the survival information was obtained. In fact the estimates of utility needed to be obtained from a nonpeer reviewed source with a limited number of patients divided between the therapies. Although the "best available" evidence was used by the authors, the estimates of utility (especially for the multimodality groups) are suspect. Importantly the authors performed sensitivity analyses that varied many of these uncertain values within plausible ranges and noted that if HRQOL with multimodal therapy was significantly lower than believed, then surgery alone was favored.
This valuable study illustrates the deficiencies in our understanding about the ideal therapy for locally advanced esophageal cancer. Our knowledge about the care of these patients will only increase if they are treated on protocols. Ideally, patients would be enrolled in multi-institutional studies that have HRQOL included.
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