Skeletal muscle quality predicts overall survival in advanced liver hepatocellular carcinoma treated with SIRT and sorafenib: A subanalysis of the SORAMIC trial.

IF 5.8 2区医学 Q1 GASTROENTEROLOGY & HEPATOLOGY

United European Gastroenterology Journal Pub Date : 2024-10-01 Epub Date: 2024-07-15 DOI:10.1002/ueg2.12627

Alexey Surov, Andreas Wienke, Jan Borggrefe, Mattes Hinnerichs, Ricarda Seidensticker, Osman Öcal, Kerstin Schütte, Christoph J Zech, Christian Loewe, Otto van Delden, Vincent Vandecaveye, Chris Verslype, Bernhard Gebauer, Christian Sengel, Irene Bargellini, Roberto Iezzi, Peter Malfertheiner, Thomas Berg, Heinz J Klümpen, Julia Benckert, Antonio Gasbarrini, Holger Amthauer, Bruno Sangro, Jens Ricke, Max Seidensticker

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引用次数: 0

Abstract

Background and aims: Our purpose was to assess the impact of muscle quality on overall survival (OS) in patients with advanced HCC.

Methods: This is a subanalysis of the SORAMIC trial. Overall, 363 patients were included. The SIRT/Sorafenib treatment group comprised 182 patients and the sorafenib group 181 patients. Myosteatosis was defined as skeletal muscle density (SMD) < 41 HU for patients with a body mass index up to 24.9 kg/m² and <33 HU for patients with a body mass index ≥25 kg/m². Albumin-gauge score was calculated as follows: serum albumin (g/dL) × SMD (HU). To assess the impact of muscle quality on clinical variables and OS, a Cox regression model was used. Hazard ratios are presented together with 95 % confidence intervals (95 % CI). Kaplan-Meier curves were used for survival analysis.

Results: In the SIRT/sorafenib cohort, low albumin-gauge score was an independent predictor of worse OS, HR = 1.74, CI 95% (1.16-2.62), p = 0.01. In the sorafenib cohort, muscle quality parameters did not predict OS. In alcohol-induced HCC (n = 129), myosteatosis independently predicted OS, HR = 1.85, CI 95% (1.10; 3.12), p = 0.02. In viral-induced HCC (n = 99), parameters of muscle quality did not predict OS. In patients with NASH/Non-alcoholic fatty liver disease (NAFLD) induced HCC, albumin-gauge score was a strong independent predictor of worse OS in the subgroup undergoing combined treatment with SIRT and sorafenib, HR = 9.86, CI 95% (1.12; 86.5), p = 0.04.

Conclusions: Myosteatosis predicts independently worse OS in patients with alcohol-induced HCC undergoing combined treatment with SIRT and sorafenib. In patients with NASH/NAFLD induced HCC undergoing treatment with SIRT and sorafenib, albumin-gauge score predicts independently worse OS.

Impact and implications: Associations between parameters of muscle quality and OS are different in accordance to the treatment strategy and etiology of HCC. These findings highlight the prognostic potential of skeletal muscle quality in patients with advanced HCC.

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骨骼肌质量可预测接受 SIRT 和索拉非尼治疗的晚期肝癌患者的总生存期：SORAMIC试验的子分析。

背景和目的我们的目的是评估肌肉质量对晚期 HCC 患者总生存期（OS）的影响：这是 SORAMIC 试验的一项子分析。总共纳入了 363 例患者。SIRT/索拉非尼治疗组有182名患者，索拉非尼治疗组有181名患者。骨质疏松症定义为骨骼肌密度（SMD）2和2。白蛋白计分的计算方法如下：血清白蛋白（g/dL）×SMD（HU）。为评估肌肉质量对临床变量和 OS 的影响，采用了 Cox 回归模型。危险比与 95 % 置信区间 (95 % CI) 一并列出。Kaplan-Meier曲线用于生存分析：结果：在SIRT/索拉非尼队列中，低白蛋白量表评分是较差OS的独立预测因子，HR = 1.74，CI 95% (1.16-2.62)，P = 0.01。在索拉非尼队列中，肌肉质量参数不能预测OS。在酒精诱导的HCC（n = 129）中，肌骨软化症可独立预测OS，HR = 1.85，CI 95% (1.10; 3.12)，p = 0.02。在病毒引起的HCC（n = 99）中，肌肉质量参数不能预测OS。在NASH/非酒精性脂肪肝（NAFLD）诱发的HCC患者中，在接受SIRT和索拉非尼联合治疗的亚组中，白蛋白计分是较差OS的强独立预测因子，HR = 9.86，CI 95% (1.12; 86.5)，P = 0.04：在接受SIRT和索拉非尼联合治疗的酒精所致HCC患者中，肌营养不良可独立预测较差的OS。在接受SIRT和索拉非尼治疗的NASH/NAFLD诱发的HCC患者中，白蛋白计分可独立预测较差的OS：肌肉质量参数与OS之间的关系因HCC的治疗策略和病因而异。这些发现凸显了骨骼肌质量对晚期HCC患者预后的潜在影响。

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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来源期刊

United European Gastroenterology Journal GASTROENTEROLOGY & HEPATOLOGY-

CiteScore

10.50

自引率

13.30%

发文量

147

期刊介绍： United European Gastroenterology Journal (UEG Journal) is the official Journal of the United European Gastroenterology (UEG), a professional non-profit organisation combining all the leading European societies concerned with digestive disease. UEG’s member societies represent over 22,000 specialists working across medicine, surgery, paediatrics, GI oncology and endoscopy, which makes UEG a unique platform for collaboration and the exchange of knowledge.