Li Bai-Bei, Chen Lei-Jie, Lu Shi-Liu, Lei Biao, Yu Gui-Lin, Yu Shui-Ping
Department of Hepatobiliary Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning 530021, Guangxi Zhuang Autonomous Region, China.
Key Laboratory of Early Prevention and Treatment for Regional High Frequency Tumor (Guangxi Medical University), Ministry of Education, Nanning 530021, Guangxi Zhuang Autonomous Region, China.
World J Gastrointest Oncol. 2024 Jan 15;16(1):61-78. doi: 10.4251/wjgo.v16.i1.61.
Over the years, programmed cell death-1 (PD-1) inhibitors have been routinely used for hepatocellular carcinoma (HCC) treatment and yielded improved survival outcomes. Nonetheless, significant heterogeneity surrounds the outcomes of most studies. Therefore, it is critical to search for biomarkers that predict the efficacy of PD-1 inhibitors in patients with HCC.
To investigate the role of the C-reactive protein to albumin ratio (CAR) in evaluating the efficacy of PD-1 inhibitors for HCC.
The clinical data of 160 patients with HCC treated with PD-1 inhibitors from January 2018 to November 2022 at the First Affiliated Hospital of Guangxi Medical University were retrospectively analyzed.
The optimal cut-off value for CAR based on progression-free survival (PFS) was determined to be 1.20 using x-tile software. Cox proportional risk model was used to determine the factors affecting prognosis. Eastern Cooperative Oncology Group performance status [hazard ratio (HR) = 1.754, 95% confidence interval (95%CI) = 1.045-2.944, = 0.033], CAR (HR = 2.118, 95%CI = 1.057-4.243, = 0.034) and tumor number (HR = 2.932, 95%CI = 1.246-6.897, = 0.014) were independent prognostic factors for overall survival. CAR (HR = 2.730, 95%CI = 1.502-4.961, = 0.001), tumor number (HR = 1.584, 95%CI = 1.003-2.500, = 0.048) and neutrophil to lymphocyte ratio (HR = 1.120, 95%CI = 1.022-1.228, = 0.015) were independent prognostic factors for PFS. Two nomograms were constructed based on independent prognostic factors. The C-index index and calibration plots confirmed that the nomogram is a reliable risk prediction tool. The ROC curve and decision curve analysis confirmed that the nomogram has a good predictive effect as well as a net clinical benefit.
Overall, we reveal that the CAR is a potential predictor of short- and long-term prognosis in patients with HCC treated with PD-1 inhibitors. If further verified, CAR-based nomogram may increase the number of markers that predict individualized prognosis.
多年来，程序性细胞死亡蛋白1（PD-1）抑制剂一直被常规用于肝细胞癌（HCC）的治疗，并改善了生存结果。尽管如此，大多数研究的结果仍存在显著异质性。因此，寻找预测PD-1抑制剂对HCC患者疗效的生物标志物至关重要。
探讨C反应蛋白与白蛋白比值（CAR）在评估PD-1抑制剂治疗HCC疗效中的作用。
回顾性分析2018年1月至2022年11月在广西医科大学第一附属医院接受PD-1抑制剂治疗的160例HCC患者的临床资料。
使用x-tile软件确定基于无进展生存期（PFS）的CAR最佳截断值为1.20。采用Cox比例风险模型确定影响预后的因素。东部肿瘤协作组体能状态[风险比（HR）=1.754，95%置信区间（95%CI）=1.045-2.944，P=0.033]、CAR（HR=2.118，95%CI=1.057-4.243，P=0.034）和肿瘤数量（HR=2.932，95%CI=1.246-6.897，P=0.014）是总生存期的独立预后因素。CAR（HR=2.730，95%CI=1.502-4.961，P=0.001）、肿瘤数量（HR=1.584，95%CI=1.003-2.500，P=0.048）和中性粒细胞与淋巴细胞比值（HR=1.120，95%CI=1.022-1.228，P=0.015）是PFS的独立预后因素。基于独立预后因素构建了两个列线图。C指数和校准图证实列线图是一种可靠的风险预测工具。ROC曲线和决策曲线分析证实列线图具有良好的预测效果以及净临床获益。
总体而言，我们发现CAR是接受PD-1抑制剂治疗的HCC患者短期和长期预后的潜在预测指标。如果得到进一步验证，基于CAR的列线图可能会增加预测个体化预后的标志物数量。
