Preoperative Predictors of Coexistent Papillary Thyroid Carcinoma in Noninvasive Follicular Thyroid Neoplasm with Papillary-Like Nuclear Features

Objective: To evaluate the clinical, ultrasonographic, and cytological characteristics of noninvasive follicular thyroid neoplasm with papillary-like nuclear features
(NIFTP) and to identify preoperative factors associated with coexistent papillary thyroid carcinoma (PTC).
Materials and Methods: This retrospective study included a total of 115 patients histopathologically diagnosed with NIFTP after thyroidectomy. Demographic,
ultrasonographic, cytological, and pathological data were analyzed. Nodules were classified according to the European Thyroid Imaging and Reporting Data System
(EU-TIRADS) and the Bethesda cytology categories. The patients were divided into two groups: “NIFTP without coexistent PTC” and “NIFTP with coexistent PTC”.
Comparative and logistic regression analyses were performed to identify predictors of concomitant PTC.
Results: The mean age was 46.78±13.98 years, and 74.8% were female. The mean size of NIFTP nodules was 23.15±16.70 mm. According to the EU-TIRADS classification,
44.3% of nodules were category 3, 14.8% category 4, and 37.4% category 5. Cytology results were most frequently Bethesda I (27.0%), II (32.2%), and III (24.3%).
Coexistent PTC was identified in 33 patients (28.7%). In the results of univariate analysis, smaller nodule size (OR 0.956, 95% CI 0.924-0.990, p = 0.010) was significantly
associated with coexistent PTC, while EU-TIRADS category 5 (OR 2.288, 95% CI 1.002-5.228, p = 0.050) showed borderline significance. In multivariate analysis, only
smaller nodule size remained an independent predictor (OR 0.951, 95% CI 0.909-0.995, p = 0.030).
Conclusion: Smaller nodule size was found to independently predict coexistent PTC in NIFTP, whereas suspicious sonographic features such as solid composition,
presence of a halo, or high EU-TIRADS scores were not independent predictors. Careful evaluation of smaller nodules may improve preoperative risk stratification and
guide surgical decision-making.