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通过评估肿瘤负荷和影像学特征来识别肝细胞癌患者接受经动脉化疗栓塞(TACE)联合微波消融(MWA)治疗的候选者。

Identification of candidates with hepatocellular carcinoma to receive TACE combined with MWA by assessing tumor burden and radiologic features.

作者信息

An Chao, Shen Lujun, Chen Qifeng, Jiang Yiquan, Li Chen, Ren He, Wu Peihong, Liu Xi

机构信息

Department of Ultrasound Diagnostics, Air Force Medical Center, Air Force Medical University, Beijing, P.R. China.

Department of Minimal Invasive Intervention, State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, P.R. China.

出版信息

Ther Adv Med Oncol. 2025 Mar 15;17:17588359251324052. doi: 10.1177/17588359251324052. eCollection 2025.

DOI:10.1177/17588359251324052
PMID:40093979
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11909676/
Abstract

BACKGROUND

There is still no noninvasive, automated, and accurate model for guiding physicians in the decision-making of transarterial chemoembolization combined with microwave ablation (TACE-MWA) in intermediate-stage hepatocellular carcinoma (HCC).

OBJECTIVES

To develop a prognostic score based on the tumor burden and radiomic features for the prediction of the long-term survival of patients with intermediate-stage HCC after TACE-MWA.

METHODS

From June 2008 to October 2022, a total of 2189 consecutive patients from seven tertiary-care hospitals with intermediate-stage HCC who received initial TACE combined with MWA were enrolled. Among them, 2189 were divided into training cohort ( = 1753), and internal test cohort ( = 436) in a single center, and 316 patients were assigned to external test cohort in another 6 centers. A prognostic scoring system was constructed using tumor burden and radiologic features (TBR) and compared with conventional predicting systems.

RESULTS

In training cohort, multivariate Cox regression analysis suggested that tumor burden (hazard ratio (HR), 0.693; 95% confidence interval (CI): 0.505, 0.814; 1 point per 1.0 increase,  = 0.024), radiologic features (HR, 0.349; 95% CI: 0.236, 0.517;  < 0.001), and alpha-fetoprotein (HR, 1.629; 95% CI: 1.280, 2.073;  < 0.001) were independent prognostic factors for OS. A prognostic model that comprises TBR was built, which showed significantly higher AUC values than other clinical stagings in all three cohorts. Moreover, the TBR score provided greater net benefit across the range of reasonable threshold probabilities than other models. Based on cutoff values of 32 and 74 centiles of the TBR score, the cohort was divided into low-, middle-, and high-risk strata, which provide consistent performance in survival discrimination across different patient subgroups.

CONCLUSION

The TBR score serves as an efficient instrument for risk stratification, guiding the course of adjuvant targeted and immunotherapies for HCC patients undergoing TACE-MWA combined treatment.

DESIGN

A retrospective, multi-institutional study.

摘要

背景

目前仍没有一种非侵入性、自动化且准确的模型来指导医生对中期肝细胞癌(HCC)进行经动脉化疗栓塞联合微波消融(TACE-MWA)治疗的决策。

目的

基于肿瘤负荷和影像组学特征开发一种预后评分系统,以预测中期HCC患者接受TACE-MWA治疗后的长期生存情况。

方法

2008年6月至2022年10月,连续纳入来自7家三级医院的2189例接受初次TACE联合MWA治疗的中期HCC患者。其中,2189例患者被分为单中心的训练队列(n = 1753)和内部测试队列(n = 436),另外316例患者被分配到另外6个中心的外部测试队列。使用肿瘤负荷和放射学特征构建了一个预后评分系统(TBR),并与传统预测系统进行比较。

结果

在训练队列中,多因素Cox回归分析表明,肿瘤负荷(风险比(HR),0.693;95%置信区间(CI):0.505,0.814;每增加1.0计1分,P = 0.024)、放射学特征(HR,0.349;95% CI:0.236,0.517;P < 0.001)和甲胎蛋白(HR,1.629;95% CI:1.280,2.073;P < 0.001)是总生存期的独立预后因素。构建了一个包含TBR的预后模型,该模型在所有三个队列中的AUC值均显著高于其他临床分期。此外,在合理的阈值概率范围内,TBR评分比其他模型提供了更大的净效益。根据TBR评分的第32和74百分位数的临界值,将队列分为低、中、高风险层,其在不同患者亚组的生存判别中表现一致。

结论

TBR评分是一种有效的风险分层工具,可指导接受TACE-MWA联合治疗的HCC患者的辅助靶向和免疫治疗进程。

设计

一项回顾性、多机构研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6f1/11909676/0aae24085e2f/10.1177_17588359251324052-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6f1/11909676/6e6b36d33af4/10.1177_17588359251324052-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6f1/11909676/6b563bb82c65/10.1177_17588359251324052-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6f1/11909676/761d55d4376f/10.1177_17588359251324052-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6f1/11909676/0cca02c2896a/10.1177_17588359251324052-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6f1/11909676/0aae24085e2f/10.1177_17588359251324052-fig5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6f1/11909676/6e6b36d33af4/10.1177_17588359251324052-fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6f1/11909676/6b563bb82c65/10.1177_17588359251324052-fig2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6f1/11909676/761d55d4376f/10.1177_17588359251324052-fig3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6f1/11909676/0cca02c2896a/10.1177_17588359251324052-fig4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c6f1/11909676/0aae24085e2f/10.1177_17588359251324052-fig5.jpg

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