A nomogram for predicting the risk of liver metastasis in non-functional neuroendocrine neoplasms: A population-based study

IF 3.5 2区医学 Q2 ONCOLOGY

Ejso Pub Date : 2025-02-21 DOI:10.1016/j.ejso.2025.109708

Zhipeng Liu , Faji Yang , Yijie Hao , Qirong Jiang, Yupeng Jiang, Shizhe Zhang, Yisu Zhang, Qixuan Zheng, Zheyu Niu, Huaqiang Zhu, Xu Zhou, Jun Lu, Hengjun Gao

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引用次数: 0

Abstract

Background

Non-functional gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are rare tumors, and liver metastasis is the leading cause of death in patients with GEP-NENs. Due to the difficulty in conducting large cohort studies, no reliable tool currently exists to predict the risk of liver metastasis in these patients. This study aimed to develop and validate a nomogram model based on large cohort clinical data to accurately predict the risk of liver metastasis in patients with non-functional GEP-NENs.

Methods

A retrospective cohort study was conducted, encompassing 838 patients with non-functional GEP-NENs diagnosed between 2009 and 2023. Independent risk factors for liver metastasis were identified through univariate and multivariate logistic regression analyses. A nomogram was constructed based on significant predictors, including T stage, N stage, Ki-67 index, primary tumor site, and BMI. The model's performance was evaluated using the C-index, calibration curves, and decision curve analysis (DCA) for both training and validation cohorts.

Results

The nomogram demonstrated excellent predictive performance, with C-index values of 0.839 and 0.823 for the training and validation sets, respectively. Risk stratification using the nomogram's total score effectively differentiated high-risk from low-risk patients. Kaplan-Meier survival analysis revealed significant survival differences between these groups (P < 0.0001). Moreover, the calibration curves indicated strong agreement between predicted and observed outcomes.

Conclusions

The developed nomogram is a reliable tool for predicting the risk of liver metastasis in non-functional GEP-NENs. It facilitates early identification of high-risk patients, thereby enabling personalized treatment and timely intervention. Future research should focus on multicenter validation and the integration of molecular markers to enhance the robustness and clinical applicability of the model.

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来源期刊

Ejso 医学-外科

CiteScore

6.40

自引率

2.60%

发文量

1148

审稿时长

41 days

期刊介绍： JSO - European Journal of Surgical Oncology ("the Journal of Cancer Surgery") is the Official Journal of the European Society of Surgical Oncology and BASO ~ the Association for Cancer Surgery. The EJSO aims to advance surgical oncology research and practice through the publication of original research articles, review articles, editorials, debates and correspondence.