@Article{info:doi/10.2196/73069,
author="Li, Xin
and Yang, Wen-yu
and Zhang, Fan
and Shan, Rui
and Mei, Fang
and Song, Shi-Bing
and Sun, Bang-Kai
and Chen, Jing
and Hu, Run-ze
and Yang, Yang
and Yang, Yi-hang
and Liu, Jing-yao
and Yuan, Chun-Hui
and Liu, Zheng",
title="Size-Specific Predictors for Malignancy Risk in Follicular Thyroid Neoplasms: Machine Learning Analysis",
journal="JMIR Cancer",
year="2025",
month="Jul",
day="11",
volume="11",
pages="e73069",
keywords="follicular thyroid neoplasm; tumor size; machine learning; malignancy; follicular thyroid cancer; follicular thyroid adenoma; random forest; XGBoost",
abstract="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. ",
issn="2369-1999",
doi="10.2196/73069",
url="https://cancer.jmir.org/2025/1/e73069",
url="https://doi.org/10.2196/73069"
}