A Novel Liver Metastasis Score for Patients Undergoing Surgical Resection of Gastroenteropancreatic Neuroendocrine Tumors: A Multi-institutional Study

Qi-Xuan Zheng ¹, Jia-Hao Xu ², Fa-Ji Yang ¹

⁰Department of Hepatobiliary Surgery, Shandong Provincial Hospital, Shandong Provincial Hospital Affiliated to Shandong University, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China.

Annals of Surgical Oncology +

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October 31, 2024

View abstract on PubMed

Summary

A new Liver Metastasis Score (LMS) predicts the risk of liver metastasis after surgery for gastroenteropancreatic neuroendocrine tumors (GEP-NETs). This tool aids personalized management for high-risk patients.

Area Of Science

Oncology
Gastroenterology
Surgical Oncology

Background

Liver metastasis significantly impacts survival in patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs).
Current guidelines lack consensus on post-resection surveillance and adjuvant therapy for GEP-NETs.
A need exists for a comprehensive risk stratification tool to guide personalized management.

Purpose Of The Study

To develop and validate a predictive model for liver metastasis risk following surgical resection of GEP-NETs.
The model incorporates pathological factors and adjuvant therapy to predict liver metastasis.
To provide a tool for personalized patient management after GEP-NET resection.

Main Methods

Retrospective analysis of 724 GEP-NET patients undergoing curative intent surgery (2010-2022) across three Chinese hospitals.
Univariable and multivariable Cox regression identified independent risk factors for liver metastasis.
Development and tenfold cross-validation of the Liver Metastasis Score (LMS) based on weighted risk factors.

Main Results

Liver metastasis occurred in 9.1% of patients, associated with significantly worse 5-year overall survival.
Independent predictors of liver metastasis included Ki-67 index, vascular invasion, lymph node metastases, and lack of adjuvant therapy.
The LMS demonstrated excellent predictive accuracy (C-index 0.888), stratifying patients into low (2.9%), intermediate (20.8%), and high-risk (49.7%) groups for 5-year metastasis risk.

Conclusions

The novel Liver Metastasis Score (LMS) effectively predicts liver metastasis risk post-GEP-NET resection.
The validated LMS can guide personalized surveillance and adjuvant treatment strategies.
Implementation of the LMS may improve outcomes for high-risk GEP-NET patients.

Keywords:

Gastroenteropancreatic neuroendocrine tumors Liver metastasis Prediction model Surgery Survival