# Predictive Value of Jugulo-omohyoid Lymph Nodes in Lateral Lymph Node Metastasis of Papillary Thyroid Cancer

## TL;DR

This study shows that jugulo-omohyoid lymph node metastasis can predict lateral lymph node metastasis in papillary thyroid cancer, helping guide surgery decisions.

## Contribution

The study introduces a high-performance nomogram using JOHLN metastasis and other factors to predict lateral lymph node metastasis in papillary thyroid cancer.

## Key findings

- JOHLN metastasis is a significant independent risk factor for lateral lymph node metastasis.
- A nomogram with an AUC of 0.855 was developed for individualized risk assessment of LNM.
- Nerve invasion was the most important predictor in the model, followed by JOHLN metastasis.

## Abstract

Jugulo-omohyoid lymph nodes (JOHLN) metastasis has proven to be associated with lateral lymph node metastasis (LLNM). This study aimed to reveal the clinical features and evaluate the predictive value of JOHLN in PTC to guide the extent of surgery.

A total of 550 patients pathologically diagnosed with PTC between October 2015 and January 2020, all of whom underwent thyroidectomy and lateral lymph node dissection, were included in this study.

Thyroiditis, tumor location, tumor size, extra-thyroidal extension, extra-nodal extension, central lymph node metastasis (CLNM), and LLMM were associated with JOHLN. Male, upper lobe tumor, multifocality, extra-nodal extension, CLNM, and JOHLN metastasis were independent risk factors from LLNM. A nomogram based on predictors performed well. Nerve invasion contributed the most to the prediction model, followed by JOHLN metastasis. The area under the curve (AUC) was 0.855, and the p-value of the Hosmer-Lemeshow goodness of fit test was 0.18. Decision curve analysis showed that the nomogram was clinically helpful.

JOLHN metastasis could be a clinically sensitive predictor of further LLM. A high-performance nomogram was established, which can provide an individual risk assessment of LNM and guide treatment decisions for patients.