Predictors of lymph node metastasis in resectable pancreatic neuroendocrine neoplasms: a single-center retrospective study

TL;DR

This study identifies tumor size as the main predictor of lymph node metastasis in pancreatic neuroendocrine tumors, with other factors like MLR and nerve invasion also being relevant.

Contribution

The study identifies tumor size as the only independent risk factor for lymph node metastasis in resectable pancreatic neuroendocrine neoplasms.

Findings

15 out of 64 patients had lymph node metastasis.

Tumor size was the only independent risk factor for LNM in multivariate analysis.

Multivariate ROC analysis showed better predictive performance than univariate analysis.

Abstract

Pancreatic neuroendocrine neoplasms (pNENs) present great heterogeneity in biological behavior, histological characteristics and clinical manifestations. Monocyte-to-lymphocyte ratio (MLR) is a noninvasive and easy-to-obtain indicator, that can reflect disease severity in multiple tumors. Lymph node metastasis (LNM) strongly affects the patient’s surgical approach and prognosis. Predicting LNM before surgery has significance for the guidance of clinical treatment. We aimed to evaluate the predictive factors, including MLR associated with LNM of patients with resectable pNENs in our center.

A total of 64 patients who underwent pNEN resection and lymph node dissection in our hospital from July 2014 until June 2023 were included in this study. Univariate and multivariate analyses were performed to identify predictive factors for LNM by analyzing clinical data, inflammatory markers, and pathological features.

Among the 64 patients, 15 (23.4%) were node positive. Univariate analysis revealed that vascular invasion, peripheral nerve invasion, bilirubin level, tumor grade, tumor size and MLR (p<0.05 for all) were risk factors for LNM. Multivariate logistic analysis demonstrated that tumor size was the only independent risk factor for LNM in our study. Multivariate ROC analysis had better predictive performance than univariate analysis did.

The preoperative MLR, vascular invasion, peripheral nerve invasion, bilirubin level, tumor grade and tumor size are potential predictors of LNM, especially during the initial diagnosis of resectable pNENs. Multivariate ROC analysis demonstrated superior performance by incorporating variables significant in univariate analysis. These factors combined can assist in clinical decision-making, such as more aggressive early intervention or intensive follow-up.

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