Web-Based Malignancy Risk Estimation for Thyroid Nodules Using Ultrasonography Characteristics: Development and Validation of a Predictive Model

Background: To establish a practical and simplified method for analyzing thyroid nodules in a clinical setting, the development of a new practical prediction model was required. This study aimed to construct and validate a simple and reliable web-based predictive model using the ultrasonography characteristics of thyroid nodules to stratify the risk of malignancy. Methods: To analyze ultrasonography images, radiologists were asked to assess thyroid nodules according to the following criteria: internal content, echogenicity of the solid portion, shape, margin, and calcifications. Multivariate logistic regression was performed to predict whether nodules were diagnosed as malignant or benign. The developmental data set included 849 nodules (January-June 2003). The validation set included different data (n=453, June 2008-February 2009). Results: Ultrasonography features, including solid content, taller-than-wide shape, spiculated margin, ill-defined margin, hypoechogenicity, marked hypoechogenicity, microcalicifications, and rim calcifications, were selected as predictors for malignant nodules in the development set. A 14-point risk scoring system was developed. Malignancy risk ranged from 3.8% to 97.4%, and the risk of malignancy was positively associated with increases in risk scores. The areas under the receiver operating characteristic curve of the development and validation sets were 0.903 and 0.897, respectively. Conclusion: A simple and reliable web-based predictive model was designed using ultrasonography characteristics to stratify thyroid nodules according to the probability of malignancy.