Validation of Three Scoring Risk-Stratification Models for Thyroid Nodules

Abstract

BACKGROUND: To minimize potential harm from overuse of fine-needle aspiration, Thyroid Imaging Reporting and Data Systems (TIRADSs) were developed for thyroid nodule risk stratification. The purpose of this study was to perform validation of three scoring risk-stratification models for thyroid nodules using ultrasonography features, a web-based malignancy risk-stratification system, and a model developed by the Korean Society of Thyroid Radiology and the American College of Radiology. METHODS: = 50.8 years; range 13-86 years) with 1112 nodules were evaluated at the authors' institute from January 2013 to December 2014. The discrimination ability of the three models was assessed by estimating the area under the receiver operating characteristic curve. Additionally, Hosmer-Lemeshow goodness-of-fit statistics (calibration ability) were used to evaluate the agreement between the observed and expected number of nodules that were benign or malignant. RESULTS: Thyroid malignancy was present in 37.2% (414/1112) of nodules. According to the 14-point web-based scoring risk-stratification system, malignancy risk ranged from 4.5% to 100.0% and was positively associated with an increase in risk scores. The areas under the receiver operating characteristic curve of the validation set were 0.884 in the web-based model, 0.891 in the Korean Society of Thyroid Radiology model, and 0.875 in the American College of Radiology model. The Hosmer-Lemeshow goodness-of-fit test indicated that the web-based scoring system showed the best-calibrated result, with a p-value of 0.078. CONCLUSION: The three scoring risk-stratification models using the ultrasonography features of thyroid nodules to stratify malignancy risk showed acceptable predictive accuracy and similar areas under the curve. The web-based scoring system demonstrated the strongest agreement in calibration ability analysis. The easily accessible automated web-based scoring risk-stratification system may overcome the complexity of the various Thyroid Imaging Reporting and Data System guidelines and provide simplified guidance on personalized and optimal management in real practice.

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