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基于监测、流行病学和最终结果(SEER)数据库研究:识别从新辅助化疗中获益的早期肝细胞癌患者

Identification of Patients with Early-Stage Hepatocellular Carcinoma Benefiting from Neoadjuvant Chemotherapy-A SEER-Based Study.

作者信息

Xu Shigang, Duan Liwei, Cho William C, Jin Shuai, Ma Linhao

机构信息

Department of Emergency, the Fourth People's Hospital, School of Medicine, Tongji University, Shanghai, 200434, China.

Department of Clinical Oncology, Queen Elizabeth Hospital, Hong Kong, SAR, China.

出版信息

J Gastrointest Cancer. 2025 Jun 29;56(1):144. doi: 10.1007/s12029-025-01264-2.

Abstract

BACKGROUND

The effectiveness of neoadjuvant chemotherapy (NAC) for individuals with early-stage hepatocellular carcinoma (HCC) is still a subject of controversy and uncertainty. This study sought to create a risk categorization model using a nomogram to pinpoint patients with early-stage HCC that might derive benefits from NAC.

METHODS

This retrospective cohort study was based on data from the SEER Research Plus database (April 2021 release), covering the years 2006 to 2018. The definition of NAC was chemotherapy performed prior to surgery, while that of no NAC (No-NAC) was surgery without chemotherapy before the operation. We implemented stepwise Cox regression to discover prognostic factors and utilized these factors to develop a nomogram for forecasting the 3-, 5-, and 10-year cancer-specific survival (CSS) for patients with early-stage HCC. We utilized receiver operating characteristic curves, calibration curves, and decision curve analysis to evaluate the prognostic capacity of the nomogram. Finally, prognostic stratification was performed based on the optimal boundary value of the nomogram score, and we utilized the Kaplan-Meier method to analyze the survival rate.

RESULTS

A sum of 11,721 HCC patients was incorporated in the analysis. After adjustment through propensity score matching, the baseline characteristics of the NAC and No-NAC groups were not statistically different. A total of 4030 patients, with the clinical data of their marital status, tumor number, fibrosis, alpha fetoprotein, grade, age, T stage, tumor size, race, and surgical approach (i.e., 11 variables) were employed in the building of the nomogram. The constructed nomogram exhibited good discriminatory ability and accuracy in predicting CSS in patients with early-stage HCC. Based on the nomogram, individuals can be classified into three distinct risk categories. In the group identified as high-risk, the CSS of the patients was significantly enhanced by NAC.

CONCLUSIONS

This study developed and validated a nomogram for predicting 3-, 5-, and 10-year CSS in early-stage HCC patients, incorporating demographic and clinical factors. Risk stratification identified high-risk patients who benefited significantly from NAC. These findings support personalized treatment decisions, though external validation is needed.

摘要

背景

新辅助化疗(NAC)对早期肝细胞癌(HCC)患者的有效性仍存在争议且不确定。本研究旨在使用列线图创建一个风险分类模型,以确定可能从NAC中获益的早期HCC患者。

方法

这项回顾性队列研究基于SEER Research Plus数据库(2021年4月发布)的数据,涵盖2006年至2018年。NAC的定义是术前进行的化疗,而无NAC(No-NAC)的定义是手术前未进行化疗。我们采用逐步Cox回归来发现预后因素,并利用这些因素开发一个列线图,用于预测早期HCC患者的3年、5年和10年癌症特异性生存率(CSS)。我们使用受试者工作特征曲线、校准曲线和决策曲线分析来评估列线图的预后能力。最后,根据列线图评分的最佳临界值进行预后分层,并使用Kaplan-Meier方法分析生存率。

结果

共有11721例HCC患者纳入分析。通过倾向评分匹配进行调整后,NAC组和No-NAC组的基线特征无统计学差异。共有4030例患者,其婚姻状况、肿瘤数量、纤维化、甲胎蛋白、分级、年龄、T分期、肿瘤大小、种族和手术方式(即11个变量)的临床数据用于构建列线图。构建的列线图在预测早期HCC患者的CSS方面表现出良好的鉴别能力和准确性。基于列线图,个体可分为三个不同的风险类别。在被确定为高风险的组中,NAC显著提高了患者的CSS。

结论

本研究开发并验证了一个用于预测早期HCC患者3年、5年和10年CSS的列线图,纳入了人口统计学和临床因素。风险分层确定了从NAC中显著获益的高风险患者。这些发现支持个性化治疗决策,不过需要外部验证。

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