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

Abstract 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.