To develop and validate a nomogram model for predicting high volume (>5) central lymph node metastasis in papillary...

To develop a nomogram model for predicting the risk of high volume (>5) of central lymph node metastasis (CLNM) in patients with papillary thyroid microcarcinoma and to evaluate its effectiveness. The model aims to assist in intraoperative or postoperative risk stratification, guide decisions on the extent of surgery and adjuvant therapy, and reduce the need for secondary surgery in patients with PTMC.

We conducted a retrospective analysis using data from the SEER database (2016-2020) as a training cohort and from Hebei General Hospital (2021-2023) as a validation cohort. Clinicopathological characteristics were analyzed using univariate and multivariate logistic regression to identify independent risk factors for high-volume CLNM and to construct a nomogram. It is important to note that all variables in the nomogram (tumor size, extrathyroidal invasion, multifocality) were derived from postoperative pathology. Therefore, the model is primarily intended for intraoperative (when frozen section analysis is available) or postoperative risk assessment.

Male sex, larger tumor size (>5 mm), multifocality, and extra-thyroidal invasion were independent risk factors for high-volume CLNM. In contrast, age ≥55 years at diagnosis was a protective factor. Based on these factors, a nomogram was constructed.

The established nomogram, based on key pathological features, has good predictive value for high-volume CLNM. It serves as a useful tool for intraoperative and postoperative clinical decision-making, helping surgeons personalize management strategies for PTMC patients after pathological confirmation.