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ContextThe risk stratification of patients with differentiated thyroid cancer (DTC) is crucial in clinical decision making. The most widely accepted method to assess risk of recurrent/persistent disease is described in the 2015 American Thyroid Association (ATA) guidelines. However, recent research has focused on the inclusion of novel features or questioned the relevance of currently included features.ObjectiveTo develop a comprehensive data-driven model to predict persistent/recurrent disease that can capture all available features and determine the weight of predictors.MethodsIn a prospective cohort study, using the Italian Thyroid Cancer Observatory (ITCO) database (NCT04031339), we selected consecutive cases with DTC and at least early follow-up data (n = 4773; median follow-up 26 months; interquartile range, 12-46 months) at 40 Italian clinical centers. A decision tree was built to assign a risk index to each patient. The model allowed us to investigate the impact of different variables in risk prediction.ResultsBy ATA risk estimation, 2492 patients (52.2%) were classified as low, 1873 (39.2%) as intermediate, and 408 as high risk. The decision tree model outperformed the ATA risk stratification system: the sensitivity of high-risk classification for structural disease increased from 37% to 49%, and the negative predictive value for low-risk patients increased by 3%. Feature importance was estimated. Several variables not included in the ATA system significantly impacted the prediction of disease persistence/recurrence: age, body mass index, tumor size, sex, family history of thyroid cancer, surgical approach, presurgical cytology, and circumstances of the diagnosis.ConclusionCurrent risk stratification systems may be complemented by the inclusion of other variables in order to improve the prediction of treatment response. A complete dataset allows for more precise patient clustering.

Medullary thyroid carcinoma (MTC) management requires determination of the sporadic or familial nature of the disease. RET proto-oncogene mutation analysis in the tumor tissue obtained at surgery and in the peripheral blood identifies somatic vs. germinal mutations. We now report a case of MTC in which a RET somatic mutation at codon 918 was detected in fine-needle aspiration specimens obtained from both the thyroid nodule and two enlarged neck lymph nodes but not in peripheral blood. Therefore, a diagnosis of sporadic MTC was made before surgery. Thus, this approach, by excluding preoperatively multiple endocrine neoplasia disease, permitted immediate thyroidectomy without search for pheochromocytoma. PCR-based genetic analysis in fine-needle aspiration biopsy specimens, therefore, preoperatively identifies genetic abnormalities at an early and easily manageable stage and may well contribute to the management strategy of MTC.