International Validation and Refinement of Oncological Borderline Resectability Criteria for Hepatocellular Carcinoma Using Tumor Burden Score to Predict Survival.

Miho Akabane, Jun Kawashima, Abdullah Altaf, Selamawit Woldesenbet, François Cauchy, Federico Aucejo, Irinel Popescu, Minoru Kitago, Guillaume Martel, Francesca Ratti, Luca Aldrighetti, George A Poultsides, Yuki Imaoka, Andrea Ruzzenente, Itaru Endo, Ana Gleisner, Hugo P Marques, Sara Oliveira, Jorge Balaia, Vincent Lam, Tom Hugh, Nazim Bhimani, Feng Shen, Timothy M Pawlik
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引用次数: 0

Abstract

Objective: The aim of this study is to externally validate the original borderline resectability (BR) category for predicting overall survival (OS) in hepatocellular carcinoma (HCC) following resection and to assess whether incorporating the tumor burden score (TBS) and other clinical factors could enhance predictive accuracy.

Background: A recent Japanese expert panel introduced a new HCC classification scheme: resectable (R), borderline resectable 1 (BR1), and borderline resectable 2 (BR2).

Methods: Patients undergoing curative-intent hepatectomy for HCC (2000-2023) were classified as R, BR1, and BR2 using the original BR and a novel TBS-BR category. The TBS-BR category replaces BR's categorical tumor morphology factors with the continuous TBS (TBS² = [maximum tumor diameter]² + [number of tumors]²). Multivariable analysis identified oncologic, morphometric, and patient-level factors associated with OS, which were incorporated into an online predictive tool.

Results: Among 1766 patients, the original BR category grouped 1504 (85.2%) as R, 249 (14.1%) as BR1, and 13 (0.7%) as BR2. Utilizing the TBS-BR category, patients were reclassified as TBS-BR R (n = 684, 38.7%), BR1 (n = 1009, 57.1%), and BR2 (n = 73, 4.1%). Both the original and TBS-BR categories correlated with 5-year OS (original: 65.1%, 48.2%, 46.4%; TBS-BR: 70.8%, 58.3%, 40.0%; P < 0.001 for both; area under the curve: 0.54 vs 0.58). On multivariable analysis, TBS-BR1 (hazard ratio [HR]: 1.59 [1.20-2.09]; P = 0.001), TBS-BR2 (HR: 2.45 [1.47-4.07]; P < 0.001, reference: TBS-BR R), American Society of Anesthesiologists (ASA) class >2 (HR: 1.40 [1.09-1.80]; P = 0.007), albumin-bilirubin (ALBI) score (HR: 1.51 [1.21-1.88]; P < 0.001), and log α-fetoprotein (AFP) (HR: 1.07 [1.03-1.11]; P < 0.001) were independently associated with OS. A TBS-BR composite model based on these factors (TBS-BR category, ASA class, ALBI score, and log AFP) was developed and made available online (https://makbn.shinyapps.io/BRHCC/). The model's area under the receiver operating characteristic at 5 years (0.70) outperformed both the original BR (0.57) and Barcelona Clinic Liver Cancer classification (0.64).

Conclusions: The TBS-BR composite model, integrating tumor morphology (TBS), tumor biology (log AFP), overall physical status (ASA class), and liver function (ALBI score) demonstrated superior predictive accuracy for OS compared with the original BR and Barcelona Clinic Liver Cancer classifications.

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使用肿瘤负荷评分预测生存的肝细胞癌肿瘤边缘可切除标准的国际验证和改进。
目的:本研究的目的是外部验证原始的边缘可切除性(BR)分类预测肝细胞癌(HCC)切除术后总生存期(OS),并评估合并肿瘤负担评分(TBS)和其他临床因素是否可以提高预测准确性。背景:最近日本专家小组介绍了一种新的HCC分类方案:可切除(R),边缘可切除1 (BR1)和边缘可切除2 (BR2)。方法:采用原始BR和一种新的TBS-BR分类,将2000-2023年接受HCC治疗目的肝切除术的患者分为R、BR1和BR2。TBS-BR分类用连续TBS (TBS²=[最大肿瘤直径]²+[肿瘤数]²)代替BR的分类肿瘤形态学因子。多变量分析确定了与OS相关的肿瘤学、形态学和患者水平因素,并将其纳入在线预测工具。结果:1766例患者中,原BR分类为R 1504例(85.2%),BR1 249例(14.1%),BR2 13例(0.7%)。利用TBS-BR分类,将患者重新分类为TBS-BR R (n = 684, 38.7%)、BR1 (n = 1009, 57.1%)和BR2 (n = 73, 4.1%)。原始分类和TBS-BR分类均与5年OS相关(原始分类:65.1%,48.2%,46.4%;Tbs-br: 70.8%, 58.3%, 40.0%;P < 0.001;曲线下面积:0.54 vs 0.58)。在多变量分析中,TBS-BR1(风险比[HR]: 1.59 [1.20-2.09];P = 0.001), tbs-br2 (hr: 2.45 [1.47-4.07];P < 0.001,参考文献:TBS-BR R),美国麻醉师学会(ASA) >2级(HR: 1.40 [1.09-1.80];P = 0.007),白蛋白-胆红素(ALBI)评分(HR: 1.51 [1.21-1.88];P < 0.001),对数α-胎蛋白(AFP) (HR: 1.07 [1.03-1.11];P < 0.001)与OS独立相关。基于这些因素(TBS-BR分类、ASA等级、ALBI评分和日志AFP)开发了TBS-BR复合模型,并在网上提供(https://makbn.shinyapps.io/BRHCC/)。该模型在5年受试者工作特征下的面积(0.70)优于原始BR(0.57)和巴塞罗那临床肝癌分类(0.64)。结论:与原始BR和巴塞罗那临床肝癌分类相比,整合肿瘤形态学(TBS)、肿瘤生物学(log AFP)、整体身体状况(ASA分类)和肝功能(ALBI评分)的TBS-BR复合模型对OS的预测准确性更高。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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