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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.

Background: The role of minimal extrathyroidal extension (mETE) as a risk factor for persistent papillary thyroid carcinoma (PTC) is still debated. The aim of this study was to assess the clinical impact of mETE as a predictor of worse initial treatment response in PTC patients and to verify the impact of radioiodine therapy after surgery in patients with mETE. Methods: We reviewed all records in the Italian Thyroid Cancer Observatory (ITCO) database and selected 2237 consecutive patients with PTC who satisfied the inclusion criteria (PTC with no lymph node metastases and at least 1 year of follow-up). For each case, we considered initial surgery, histological variant of PTC, tumor diameter, recurrence risk class according to the American Thyroid Association (ATA) risk stratification system, use of radioiodine therapy, and initial therapy response, as suggested by ATA guidelines. Results: At 1-year follow-up, 1831 patients (81.8%) had an excellent response, 296 (13.2%) had an indeterminate response, 55 (2.5%) had a biochemical incomplete response, and 55 (2.5%) had a structural incomplete response. Statistical analysis suggested that mETE (odds ratio [OR] 1.16, p=0.65), tumor size >2 cm (OR 1.45, p=0.34), aggressive PTC histology (OR 0.55, p=0.15), and age at diagnosis (OR 0.90, p=0.32) were not significant risk factors for a worse initial therapy response. When evaluating the combination of mETE, tumor size, and aggressive PTC histology, the presence of mETE with a >2 cm tumor was significantly associated with a worse outcome (OR 5.27, 95% CI, p=0.014). The role of radioiodine ablation in patients with mETE was also evaluated. When considering radioiodine treatment, propensity score-based matching was performed, and no significant differences were found between treated and non-treated patients (p=0.24). Conclusions: This study failed to show the prognostic value of mETE in predicting initial therapy response in a large cohort of PTC patients without lymph node metastases. The study suggests that the combination of tumor diameter and mETE can be used as a reliable prognostic factor for persistence and could be easily applied in clinical practice to manage PTC patients with low-to-intermediate risk of recurrent/persistent disease.