ORIGINAL RESEARCH article
Front. Med.
Sec. Precision Medicine
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1641266
A Cascaded Clinical-Ultrasound-Biochemical Model for Precise Prediction Before Thyroid Nodule Fine-Needle Aspiration Biopsy
Provisionally accepted
- 1First Affiliated Hospital, Dalian Medical University, Dalian, China
- 2Dalian Medical University, Dalian, China
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Objectives Determining the nature of thyroid nodules through a single fine-needle aspiration (FNA) biopsy is not feasible for approximately one-third of patients. We developed a predictive model to assist FNA decision-making and reduce unnecessary FNAs. Methods This retrospective study consecutively included patients who underwent ultrasound-guided FNA between March 2018 and March 2023. Patients were divided into a training dataset (70%) and a validation dataset (30%). Univariate analysis was performed within the training dataset using Kruskal–Wallis test for continuous variables and chi-square test or Fisher's exact test for categorical variables. Variables with significance were entered into multivariate logistic regression. The prediction model (B-Model) was constructed using a cascaded three-stage logistic regression framework: Stage I distinguished benign from non-benign nodules, Stage II differentiated malignant from non-malignant nodules, Stage III separated follicular neoplasm from indeterminate/atypia nodules. Model performance was assessed in the validation dataset using sensitivity (SEN), specificity (SPE), and accuracy (ACC). The reduction in repeat FNA facilitated by the B-Model was calculated. Results Training and validation datasets included 1,573 and 672 cases, respectively. The overall SEN, SPE and ACC of the B-Model were 84.7%, 76.7% and 60.1% in the validation dataset. The application of the B-Model reduced the number of patients requiring repeat FNA from 255 to 153, resulting in a 40.0% reduction. Conclusions The B-Model demonstrated robust predictive performance, facilitating the optimization of pre-FNA diagnostic workflows, significantly reducing unnecessary repeat FNAs, and advancing precision in thyroid nodule management.
Keywords: Fine-needle aspiration (FNA), logistic regression (LG), Ultrasound imaging (USG), Thyroid nodules (TNs), precision medicine
Received: 04 Jun 2025; Accepted: 08 Sep 2025.
Copyright: © 2025 Gao, Liu, Tong, Zhu, Wang, Du, Shi, Han and Che. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Ying Che, First Affiliated Hospital, Dalian Medical University, Dalian, China
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