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

IF 2.9 2区医学 Q2 ONCOLOGY Ejso Pub Date : 2025-05-01 Epub 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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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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预测非功能性神经内分泌肿瘤肝转移风险的nomogram：一项基于人群的研究

背景：非功能性胃肠胰神经内分泌肿瘤（GEP-NENs）是一种罕见的肿瘤，肝转移是导致其死亡的主要原因。由于难以进行大规模队列研究，目前还没有可靠的工具来预测这些患者的肝转移风险。本研究旨在建立并验证基于大量队列临床数据的nomogram模型，以准确预测非功能性GEP-NENs患者的肝转移风险。方法回顾性队列研究，纳入2009年至2023年诊断的838例非功能性GEP-NENs患者。通过单因素和多因素logistic回归分析确定肝转移的独立危险因素。基于T分期、N分期、Ki-67指数、原发肿瘤部位和BMI等重要预测因子构建nomogram。使用c指数、校准曲线和决策曲线分析（DCA）对训练和验证队列进行模型性能评估。结果nomogram具有较好的预测效果，训练集和验证集的C-index值分别为0.839和0.823。采用nomogram总分进行风险分层，有效地区分了高危患者和低危患者。Kaplan-Meier生存分析显示两组间存在显著的生存差异(P <；0.0001)。此外，校准曲线显示预测结果和观测结果之间有很强的一致性。结论所建立的形态图是预测非功能性GEP-NENs发生肝转移风险的可靠工具。它有助于早期识别高危患者，从而实现个性化治疗和及时干预。未来的研究应侧重于多中心验证和分子标记的整合，以提高模型的稳健性和临床适用性。

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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.