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

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 identi

SUBMITTER: Li X 

PROVIDER: S-EPMC12274017 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature