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免疫检查点抑制剂治疗的肝细胞癌患者预后评分的开发与验证:肝细胞癌改良古斯塔夫·鲁西免疫评分

Development and Validation of a Prognostic Score for Hepatocellular Carcinoma Patients in Immune Checkpoint Inhibitors Therapies: The Hepatocellular Carcinoma Modified Gustave Roussy Immune Score.

作者信息

Li Yongjiang, Pan Yangxun, Lin Ximeng, Hou Jingyu, Hu Zili, Xu Li, Zhou Zhongguo, Zhang Yaojun, Chen Minshan, Hu Dandan

机构信息

Collaborative Innovation Center for Cancer Medicine, State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China.

Department of Nuclear Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.

出版信息

Front Pharmacol. 2022 Feb 8;12:819985. doi: 10.3389/fphar.2021.819985. eCollection 2021.

DOI:10.3389/fphar.2021.819985
PMID:35237150
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8883391/
Abstract

There is not yet an effective marker in predicting the efficacy of immune checkpoint inhibitors (ICIs) in treating hepatocellular carcinoma (HCC) patients. The Gustave Roussy Immune Score (GRIm-Score) based on three objective variables, namely, neutrophil-to-lymphocyte ratio (NLR), serum albumin level (ALB), and lactate dehydrogenase (LDH), was developed as feasible prognostic indication in lung cancer patients receiving ICIs therapies. Our study aimed to adapt the GRIm-Score (HCC-GRIm-Score) in HCC patients who received ICIs therapies and thus improving the predictive ability. From January 2018 to September 2020, 261 patients who received ICIs therapy were retrospectively included and divided into training and validation groups. After determining the factors for HCC-GRIm-Score by multivariable analysis from training group, the optimized HCC-GRIm-Score was validated and compared to the original GRIm-Score and the Barcelona clinic liver cancer (BCLC) staging system. One hundred sixty-one and 80 patients were assigned into the training and validation groups, respectively. Two more factors, aspartate transaminase-to-alanine transaminase ratio [hazard ratio (HR), 1.51; 95% confidence interval (CI), 0.94-2.42] and total bilirubin (HR, 1.76; 95% CI, 1.07-2.88), were identified as independent prognostic factors for overall survival (OS) and integrated in the HCC-GRIm-Score system according to the multivariable analysis. A risk score based on the HCC-GRIm-Score indicated that patients presenting high score (>2) suffered from significantly shorter median OS of 10.3 months compared to those with a low score (not reached; HR, 2.99; 95% CI, 1.89-4.75; < 0.001). In the validation group of 80 patients, the patients presenting a high score showed an inferior OS (HR 5.62, 95% CI, 1.25-25.24; = 0.024). HCC-GRIm-Score had the highest area under curve of 0.719 (95% CI, 0.661-0.773) compared to original GRIm-Score and BCLC staging system. The present study confirmed that the modified HCC-GRIm-Score system provided superior predictive ability in identifying the HCC patients potentially benefit from ICIs therapies, compared to the original GRIm-Score and the BCLC staging system.

摘要

目前尚无有效的标志物可预测免疫检查点抑制剂(ICI)治疗肝细胞癌(HCC)患者的疗效。基于中性粒细胞与淋巴细胞比值(NLR)、血清白蛋白水平(ALB)和乳酸脱氢酶(LDH)这三个客观变量的古斯塔夫·鲁西免疫评分(GRIm-Score),被开发为接受ICI治疗的肺癌患者可行的预后指标。我们的研究旨在将GRIm-Score(HCC-GRIm-Score)应用于接受ICI治疗的HCC患者,从而提高预测能力。2018年1月至2020年9月,回顾性纳入261例接受ICI治疗的患者,并分为训练组和验证组。通过对训练组进行多变量分析确定HCC-GRIm-Score的因素后,对优化后的HCC-GRIm-Score进行验证,并与原始GRIm-Score和巴塞罗那临床肝癌(BCLC)分期系统进行比较。分别有161例和80例患者被分配到训练组和验证组。另外两个因素,天冬氨酸转氨酶与丙氨酸转氨酶比值[风险比(HR),1.51;95%置信区间(CI),0.94 - 2.42]和总胆红素(HR,1.76;95%CI,1.07 - 2.88),被确定为总生存期(OS)的独立预后因素,并根据多变量分析纳入HCC-GRIm-Score系统。基于HCC-GRIm-Score的风险评分表明,高评分(>2)患者的中位OS显著缩短,为10.3个月,而低评分患者未达到(HR,2.99;95%CI,1.89 - 4.75;P < 0.001)。在80例患者的验证组中,高评分患者的OS较差(HR 5.62,95%CI,1.25 - 25.24;P = 0.024)。与原始GRIm-Score和BCLC分期系统相比,HCC-GRIm-Score的曲线下面积最高,为0.719(95%CI,0.661 - 0.773)。本研究证实,与原始GRIm-Score和BCLC分期系统相比,改良后的HCC-GRIm-Score系统在识别可能从ICI治疗中获益的HCC患者方面具有更强的预测能力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fbc/8883391/93849c5fdb21/fphar-12-819985-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fbc/8883391/69adff88f11a/fphar-12-819985-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fbc/8883391/46150af759cc/fphar-12-819985-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fbc/8883391/49c5cb12c3c1/fphar-12-819985-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fbc/8883391/93849c5fdb21/fphar-12-819985-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fbc/8883391/69adff88f11a/fphar-12-819985-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fbc/8883391/46150af759cc/fphar-12-819985-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fbc/8883391/49c5cb12c3c1/fphar-12-819985-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fbc/8883391/93849c5fdb21/fphar-12-819985-g004.jpg

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