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Reply To C.A. Hudis Et Al
Published 2012 · Medicine
TO THE EDITOR: We are grateful to Hudis et al for the opportunity to clarify both the limitations and uses of observational data in the assessment of clinical questions. With regard to the benefits of dosedense chemotherapy for elderly patients with hormone-positive breast cancer, we agree that there are subsets of older patients who are hormone positive who benefit from the addition of chemotherapy to hormone therapy, and likely a subset of those who benefit from more intensive therapy and dose-dense therapy. Current studies of personalized approaches will help inform the former, but not necessarily the latter. Unfortunately, however, in the absence of clear indications for treatment, it is common to err on the side of treating many for the benefit of the few. Our paper’s intent was to look at patterns of care and dissemination of granulocyte colony-stimulating factor, not the benefit of chemotherapy or a particular therapy. When results from clinical trials are presented they are often applied to patients who do not fit the strict eligibility criteria that is required for trial participants. We found the uptake of first-cycle colony-stimulating factor was rapid in many settings, and we describe the estimated costs associated with rapid uptake. Observational data cannot substitute for randomized trials in establishing the efficacy of an intervention. But randomized trials are limited to carefully defined subject eligibility and self-selection. It is impractical and unnecessary for a randomized trial to be conducted for every treatment in every subgroup setting. However, in addition to being hypothesis generating, observational data can effectively explore how interventions are utilized in “the real world,” can provide clues and insights into how quality of care can be improved and can help explore how the costs of cancer care can be reduce. Many of the limitations of the operationalized definitions mentioned by the authors were addressed in the Discussion section of the paper. We feel it is important to weigh the costs and benefits of making difficult therapeutic decisions when the efficacy data is ambiguous, especially when treating patients that may not be well represented by the clinical trial data.