Work

Ultrasound-based nomogram for predicting central lymph node metastasis in papillary thyroid microcarcinoma

Year: 2026

Type: article

Abstract: BACKGROUND: This study aimed to develop a nomogram based on Ultrasound features for predicting the probability of central lymph node metastases (CLNM) in patients diagnosed with papillary thyroid microcarcinoma (PTMC). METHODS: A total of 670 patients with histologically confirmed PTMC between 2021 and 2024 were included in this retrospective study and divided into the training (n = 469) and validation (n = 201) cohorts. Through least absolute shrinkage and selection operator (LASSO) regression analysis on the training cohort, we identified the most effective predictors. These predictors were then used to construct a nomogram. We evaluated the nomogram’s discrimination, calibration, and clinical usefulness in the validation cohort using receiver operating characteristic (ROC) analysis, calibration plots, and decision curve analysis. RESULTS: After applying LASSO and logistic regression screening with criteria for retaining non-zero coefficients, several factors were found to be independently linked to CLNM in PTMC patients. A nomogram model was subsequently developed to predict the risk of CLNM in PTMC patients based on the predictors. The AUC (C-statistic) of the nomogram was 0.73 (95% CI: 0.68–0.77) for the training cohort and 0.77 (95% CI: 0.70–0.83) for the validation cohort. Decision curve analysis (DCA) demonstrated that the model achieved a higher net benefit than the baseline strategy within the threshold probability ranges of 17%–88% in the training cohort and 10%–76% in the validation cohort. CONCLUSIONS: This ultrasound-based nomogram, incorporating relevant clinical characteristics, holds promise as a valuable clinical instrument capable of furnishing essential information to guide treatment decisions. TRIAL REGISTRATION: Not applicable.

Source: BMC Endocrine Disorders

DOI: 10.1186/s12902-026-02283-1

Authors: Hong Huang, Lina Hu, Xuan Chen, Hui Luo

Institutions: Jinan University, Southern University of Science and Technology, ShenZhen People’s Hospital, Shantou University Medical College

Language: English

Topic: Thyroid Cancer Diagnosis and Treatment

Subfield: Endocrinology, Diabetes and Metabolism

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,190