Clinical judgment to estimate pretest probability in the diagnosis of Cushing's syndrome under a Bayesian perspective

Objective: To estimate the pretest probability of Cushing's syndrome (CS) diagnosis by a Bayesian approach using intuitive clinical judgment. Materials and methods: Physicians were requested, in seven endocrinology meetings, to answer three questions: Based on your personal expertise, after obtaining clinical history and physical examination, without using laboratorial tests, what is your probability of diagnosing Cushing's Syndrome?; For how long have you been practicing Endocrinology?; and Where do you work?. A Bayesian beta regression, using the WinBugs software was employed. Results: We obtained 294 questionnaires. The mean pretest probability of CS diagnosis was 51.6% (95% CI: 48.7-54.3). The probability was directly related to experience in endocrinology, but not with the place of work. Conclusion: Pretest probability of CS diagnosis was estimated using a Bayesian methodology. Although pretest likelihood can be context-dependent, experience based on years of practice may help the practitioner to diagnosis CS. Arq Bras Endocrinol Metab. 2012; 56(9):633-7