针对胃肠胰神经内分泌肿瘤手术切除患者的新型肝转移评分:一项多机构研究

IF 3.4 2区 医学 Q2 ONCOLOGY Annals of Surgical Oncology Pub Date : 2025-02-01 Epub Date: 2024-10-31 DOI:10.1245/s10434-024-16389-0
Qi-Xuan Zheng, Jia-Hao Xu, Fa-Ji Yang, Zhi-Peng Liu, Ming-Da Wang, Yi-Jie Hao, Chao Li, Zhe-Yu Niu, Xin-Fei Xu, Heng-Jun Gao, Yi-Fan Li, Jin-Bo Gong, Zhong Chen, Timothy M Pawlik, Feng Shen, Jun Lu, Tian Yang
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引用次数: 0

摘要

背景:肝转移影响胃肠胰神经内分泌肿瘤(GEP-NET)患者的生存;然而,目前的指南对切除术后监测和辅助治疗缺乏共识。需要一种全面的风险分层工具来指导个性化治疗:我们的目的是开发并验证一个预测GEP-NET手术切除后肝转移风险的模型,该模型结合了病理因素和辅助治疗:方法:研究对象为在中国三家大型医院接受手术切除治疗的GEP-NET患者(2010-2022年)。单变量和多变量Cox回归分析确定了肝转移的独立风险因素。利用加权风险因素制定了肝转移评分(LMS),并通过十倍交叉验证进行了验证:结果:在纳入分析队列的724名患者中,66名患者(9.1%)在中位36个月时发生了肝转移;肝转移患者的5年总生存率较低(无肝转移63.6% vs. 肝转移95.8%;P 20%, vs. LMS)。 结论:新型LMS能有效预测肝转移的风险因素:新型 LMS 能有效预测 GEP-NET 手术切除后发生肝转移的风险。这一经过验证的模型有助于指导个性化监测和辅助治疗策略,从而改善高危患者的预后。
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A Novel Liver Metastasis Score for Patients Undergoing Surgical Resection of Gastroenteropancreatic Neuroendocrine Tumors: A Multi-institutional Study.

Background: Liver metastasis impacts survival in patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs); however, current guidelines lack consensus on post-resection surveillance and adjuvant therapy. A comprehensive risk stratification tool is needed to guide personalized management.

Objective: We aimed to develop and validate a predictive model for liver metastasis risk after surgical resection of GEP-NETs that incorporates pathological factors and adjuvant therapy.

Methods: Patients with GEP-NETs who underwent surgical resection with curative intent at three major Chinese hospitals (2010-2022) were identified. Univariable and multivariable Cox regression analysis identified independent risk factors of liver metastasis. The liver metastasis score (LMS) was developed using weighted risk factors and validated by tenfold cross-validation.

Results: Among the 724 patients included in the analytic cohort, liver metastasis occurred in 66 patients (9.1%) at a median of 36 months; patients with liver metastasis had a worse 5-year overall survival (no liver metastasis 63.6% vs. liver metastasis 95.8%; p < 0.001). Independent predictors were Ki-67 index (hazard ratio [HR] 10.36 for Ki-67 3-20%, HR 18.30 for Ki-67 >20%, vs. <3%), vascular invasion (HR 5.03), lymph node metastases (HR 2.24), and lack of adjuvant therapy (HR 3.03). The LMS demonstrated excellent discrimination (C-index 0.888) and stratified patients into low, intermediate, and high-risk relative to 5-year risk of liver metastasis: 2.9%, 20.8%, and 49.7%, respectively (p < 0.001).

Conclusions: The novel LMS effectively predicted the risk of liver metastasis after surgical resection of GEP-NETs. This validated model can help guide personalized surveillance and adjuvant treatment strategies, potentially improving outcomes for high-risk patients.

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来源期刊
CiteScore
5.90
自引率
10.80%
发文量
1698
审稿时长
2.8 months
期刊介绍: The Annals of Surgical Oncology is the official journal of The Society of Surgical Oncology and is published for the Society by Springer. The Annals publishes original and educational manuscripts about oncology for surgeons from all specialities in academic and community settings.
期刊最新文献
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