A nomogram for enhanced risk stratification for predicting cervical lymph node metastasis in papillary thyroid carcinoma patients.

ABSTRACT:

Background

Cervical lymph node metastasis (CLNM) significantly impacts the prognosis of papillary thyroid carcinoma (PTC) patients. Accurate CLNM prediction is crucial for surgical planning and patient outcomes. This study aimed to develop and validate a nomogram-based risk stratification system to predict CLNM in PTC patients.

Methods

This retrospective study included 1069 patients from Zhongshan Hospital and 253 from the Qingpu Branch of Zhongshan Hospital. Preoperative ultrasound (US) data and various nodule characteristics were documented. Patients underwent lobectomy with central lymph node dissection and lateral dissection if suspicious. Multivariate logistic regression, least absolute shrinkage and selection operator (LASSO) regression, and the random forest algorithm

SUBMITTER: Deng L 

PROVIDER: S-EPMC11436574 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature