A predictive model to distinguish malignant and benign thyroid nodules based on age, gender and ultrasonographic features.

INTRODUCTION: A discussion in literature about a standardized decision support tool for the management of thyroid nodules remains. OBJECTIVE: The purpose of this study was to create a statistical prediction model for thyroid nodules management. METHODS: Two hundred and four benign and 57 malignant thyroid nodules were selected for a retrospective study. The variables age, gender and ultrasonographic features were examined using univariate and multivariate models. A statistical formula was used to calculate the risk of cancer of each case. RESULTS: In multivariate analysis, irregular shape, absence of halo, lower mean age, homogeneous echotexture, microcalcifications and solid content were associated with cancer. After applying the formula, 20 cases (7.6%) with a calculated risk for malignancy ≤3.0% were found, all of them benign. Setting the calculated risk in ≥80%, 21 (8.0%) cases were selected, and in 85.7% of them cancer was confirmed in histopathology. Internal accuracy of the prediction formula was 92.5%. CONCLUSIONS: The prediction formula reached high accuracy and may be an alternative to other decision support tools for thyroid nodule management.