Objective: to develop a predictive model based on clinical data for patients with suspected upper digestive tract disease.
Patients and methods: forty-seven clinical data were obtained before endoscopy from 283 patients with suspected upper digestive disease (153 men; mean age 55 years, limits 17-92 years). A clinical prediction of diagnosis was made before endoscopy. On the basis of the endoscopic findings, the patients were divided into three diagnostic groups: absence of significant disease (group I), significant benign disease (group II) and malignant disease (group III). The probability rate of belonging to each one of the three groups was obtained for each patient by using Bayes' theorem.
Results: the endoscopic findings were classified according to their clinical importance: 121 patients (43%) belonged to group I, 137 (48%) were included in group II; and 25 (9%) in group III. The clinical prediction correctly classified 61% of the patients (group I: 56%, group II: 62% and group III: 76%) The coincidence between prediction obtained using Bayes' theorem and the actual diagnosis was 61% (group I: 65%, group II: 51%, group III: 92%). The predictive model was useful to confirm or not the clinical prediction.
Conclusion: objective analysis of clinical data can be useful to support clinical judgment, mainly in patients with neoplasia. However, the model is not adequate to improve indication of upper endoscopy since many patients are misclassified.