Lu Shao-Long, Zhang Qing-Yuan, Zhao Yuan-Quan, Wu Hua-Lin, Lin Jie, Zhu Peng, Qin Zheng-Jun, Wang Xiao-Bo, Chen Jie
Department of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, China.
BMC Cancer. 2025 Apr 26;25(1):784. doi: 10.1186/s12885-025-14163-3.
Many prognostic scores based on systemic inflammation have been developed. Most of these prognostic scores have been shown to influence the prognosis of hepatocellular carcinoma (HCC) patients. This research aims to develop a novel prognostic system based on inflammatory markers for patients with HCC.
This research encompassed 920 HCC patients who underwent potentially radical surgical resection. We employed receiver-operating characteristic (ROC) curve analysis to determine the optimal cutoff value for the preoperative inflammatory prognostic score. Univariate and multivariate Cox regression analyses were conducted to pinpoint features that significantly influence outcomes for patients with HCC. We employed a calibration curve and decision curve analysis (DCA) to appraise the application of the nomogram.
The multivariate Cox regression identified that systemic immunoinflammatory response index (SIRI), C-reactive protein-albumin ratio (CAR), tumor size, hepatitis B virus (HBV)-DNA, prothrombin time, microvascular invasion, macroscopic vascular invasion, and Edmondson-Steiner grade were all independent predictors of overall survival (OS). The predictive accuracy of the nomogram for estimating 1-, 3-, and 5-year OS was measured by the area under the receiver operating characteristic curve (AUC). In the training cohort, the AUC scores for the 1-, 3-, and 5-year OS were 0.815, 0.805, and 0.776. For the validation cohort, the respective AUC scores were 0.814, 0.737, and 0.730. Additionally, our nomogram shows a high capacity for distinguishing between different risk groups and is practical for clinical use.
The nomogram demonstrates strong predictive performance for the 1-, 3-, and 5-year OS of HCC patients undergoing radical surgery. The combination of related markers (SIRI, CAR, etc.) makes it more reliable and beneficial in predicting prognosis in HCC patients.
已经开发了许多基于全身炎症的预后评分系统。这些预后评分中的大多数已被证明会影响肝细胞癌(HCC)患者的预后。本研究旨在为HCC患者开发一种基于炎症标志物的新型预后系统。
本研究纳入了920例行潜在根治性手术切除的HCC患者。我们采用受试者操作特征(ROC)曲线分析来确定术前炎症预后评分的最佳临界值。进行单因素和多因素Cox回归分析以确定对HCC患者预后有显著影响的特征。我们采用校准曲线和决策曲线分析(DCA)来评估列线图的应用。
多因素Cox回归分析确定,全身免疫炎症反应指数(SIRI)、C反应蛋白-白蛋白比值(CAR)、肿瘤大小、乙型肝炎病毒(HBV)-DNA、凝血酶原时间、微血管侵犯、宏观血管侵犯和Edmondson-Steiner分级均为总生存期(OS)的独立预测因素。通过受试者操作特征曲线(AUC)下面积来衡量列线图预测1年、3年和5年OS的预测准确性。在训练队列中,1年、3年和5年OS的AUC分数分别为0.815、0.805和0.776。在验证队列中,相应的AUC分数分别为0.814、0.737和0.730。此外,我们的列线图显示出区分不同风险组的能力很强,并且在临床应用中很实用。
该列线图对接受根治性手术的HCC患者的1年、3年和5年OS具有很强的预测性能。相关标志物(SIRI、CAR等)的组合使其在预测HCC患者预后方面更可靠且有益。