%0 Journal Article
%@ 2369-1999
%I JMIR Publications
%V 11
%N 
%P e73069
%T Size-Specific Predictors for Malignancy Risk in Follicular Thyroid Neoplasms: Machine Learning Analysis
%A Li,Xin
%A Yang,Wen-yu
%A Zhang,Fan
%A Shan,Rui
%A Mei,Fang
%A Song,Shi-Bing
%A Sun,Bang-Kai
%A Chen,Jing
%A Hu,Run-ze
%A Yang,Yang
%A Yang,Yi-hang
%A Liu,Jing-yao
%A Yuan,Chun-Hui
%A Liu,Zheng
%K follicular thyroid neoplasm
%K tumor size
%K machine learning
%K malignancy
%K follicular thyroid cancer
%K follicular thyroid adenoma
%K random forest
%K XGBoost
%D 2025
%7 11.7.2025
%9 
%J JMIR Cancer
%G English
%X Background: Surgeons often face challenges in distinguishing between benign and malignant follicular thyroid neoplasms (FTNs), particularly small tumors, until diagnostic surgery is performed. Objective: This study aimed to identify the size-specific predictors for the malignancy risk of FTNs preoperatively. Methods: A retrospective cohort study was conducted at Peking University Third Hospital in Beijing, China, from 2012 to 2023. Patients with a postoperative pathological diagnosis of follicular thyroid adenoma (FTA) or follicular thyroid carcinoma (FTC) were included. FTNs were classified into small- and large-sized categories based on the cutoff value of the tumor diameter derived from spline regression, which indicated the turning point of malignancy risk. We identified the 5 most important predictors from 22 variables including demography, sonography, and hormones, using machine learning methods. We also calculated the odds ratios (OR) with 95% CI for these predictors in both small- and large-sized FTNs. Results: Altogether, we included 1494 FTNs, comprising 1266 FTAs and 228 FTCs. FTNs with a maximum diameter less than 3.0 cm were grouped as small-sized tumors (n=715), while those with larger diameters were categorized as large-sized tumors (n=779). In the small-sized group, tumors with macrocalcification (OR 2.90, 95% CI 1.50-5.60), those with peripheral calcification (OR 4.50, 95% CI 1.50-13.00), and those in younger patients (OR 1.33, 95% CI 1.05-1.69) showed a higher malignancy risk. In the large-sized group, tumors presenting with a nodule-in-nodule appearance (OR 3.30, 95% CI 1.30-7.90) exhibited a higher malignancy risk. In both groups, lower thyroid-stimulating hormone levels (OR 1.49, 95% CI 1.20-1.85 for small-sized FTNs; OR 1.61, 95% CI 1.37-1.96 for large-sized FTNs) and a larger mean diameter (OR 1.40, 95% CI 1.10-1.70 for small-sized FTNs; OR 1.50 95% CI 1.20-1.70 for large-sized FTNs) were associated with the malignancy risk of FTNs. Conclusion: This study identified size-specific predictors for malignancy risk in FTNs, highlighting the importance of stratified prediction based on tumor size. 
%R 10.2196/73069
%U https://cancer.jmir.org/2025/1/e73069
%U https://doi.org/10.2196/73069