# Size-Specific Predictors for Malignancy Risk in Follicular Thyroid Neoplasms: Machine Learning Analysis

## TL;DR

This study uses machine learning to identify predictors of malignancy in follicular thyroid tumors based on their size, helping surgeons make preoperative decisions.

## Contribution

The study introduces size-specific predictors for malignancy risk in follicular thyroid neoplasms using machine learning.

## Key findings

- Macrocalcification and peripheral calcification are significant predictors for malignancy in small-sized follicular thyroid neoplasms.
- Lower thyroid-stimulating hormone levels and larger tumor size are associated with malignancy risk in both small- and large-sized tumors.
- Nodule-in-nodule appearance is a key predictor for malignancy in large-sized follicular thyroid neoplasms.

## Abstract

Surgeons often face challenges in distinguishing between benign and malignant follicular thyroid neoplasms (FTNs), particularly small tumors, until diagnostic surgery is performed.

This study aimed to identify the size-specific predictors for the malignancy risk of FTNs preoperatively.

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.

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.

This study identified size-specific predictors for malignancy risk in FTNs, highlighting the importance of stratified prediction based on tumor size.