Surgical Optimization in Preoperatively Low-risk cN1a PTC: A Predictive Model for High-Volume Central Lymph Node...

Area of Science:

• Endocrinology
• Surgical Oncology
• Diagnostic Imaging

Background:

• Accurate preoperative identification of high-volume central lymph node metastasis (hv-CLNM) is crucial for surgical decisions in papillary thyroid carcinoma (PTC) with cN1a staging.
• Distinguishing between lobectomy and total thyroidectomy depends on metastasis volume, with hv-CLNM often necessitating total thyroidectomy.

Purpose of the Study:

• To identify predictors of hv-CLNM in preoperatively low-risk cN1a PTC patients.
• To develop a predictive model for estimating hv-CLNM risk and optimize surgical planning.

Main Methods:

• Retrospective analysis of 707 PTC patients classified as preoperatively low-risk cN1a.
• Variable selection using LASSO regression, followed by multivariate logistic regression to build a predictive model.
• Internal validation and comparison of recurrence-free survival between lobectomy and total thyroidectomy groups using propensity score matching.

Main Results:

• Hv-CLNM was present in 13.4% of patients.
• Independent predictors for hv-CLNM included age, sex, tumor size, tumor location, and lymph node calcification.
• The developed nomogram showed good predictive performance (AUC = 0.75).

Conclusions:

• A nomogram utilizing clinical and ultrasound features effectively predicts hv-CLNM risk in preoperatively low-risk cN1a PTC.
• This tool can aid in personalized surgical planning, with lobectomy appearing safe for most patients in this subgroup.