Two recent articles in the Archives proposed mathematical models for a rational diagnostic and therapeutic approach to patients with diseases of the head and neck. In the first article,1 decision analysis was used to analyze choices of treatment for patients who have American Joint Committee on Cancer stage I floor-of-mouth carcinoma. In the second article,2 Bayes’ theorem was used to construct a diagnostic algorithm for patients who were suspected of having cervical tuberculous lymphadenitis. In both studies, the clinical problem was approached with various computations obtained from a mathematical model, and the recommendations in each report diverged from current clinical practice.

In this report, we describe decision analysis and Bayes’ theorem, present alternative interpretations of the two analyses, and suggest what clinicians can do to improve the quality of the data generated in clinical research as used in these models. The goal of this study review is to


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