Jiang Yu, Chen Shulin, Wu Yaxian, Qu Yuanye, Jia Lina, Xu Qingxia, Dai Shuqin, Xue Ning
Department of Clinical Laboratory, Affiliated Tumor Hospital of Zhengzhou University, Henan Cancer Hospital, Zhengzhou Key Laboratory of Digestive System Tumor Marker Diagnosis, 127 Dongming Road, Zhengzhou, 450000, China.
Department of Clinical Laboratory, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, 510060, China.
Cancer Cell Int. 2022 Oct 2;22(1):300. doi: 10.1186/s12935-022-02725-5.
The incidence of non-virus-related hepatocellular carcinoma (NV-HCC) in hepatocellular carcinoma (HCC) is steadily increasing. The aim of this study was to establish a prognostic model to evaluate the overall survival (OS) of NV-HCC patients.
Overall, 261 patients with NV-HCC were enrolled in this study. A prognostic model was developed by using LASSO-Cox regression analysis. The prognostic power was appraised by the concordance index (C-index), and the time-dependent receiver operating characteristic curve (TD-ROC). Kaplan-Meier (K-M) survival analysis was used to evaluate the predictive ability in the respective subgroups stratified by the prognostic model risk score. A nomogram for survival prediction was established by integrating the prognostic model, TNM stage, and treatment.
According to the LASSO-Cox regression results, the number of nodules, lymphocyte-to-monocyte ratio (LMR), prognostic nutritional index (PNI), alkaline phosphatase (ALP), aspartate aminotransferase (AST)/alanine aminotransferase (ALT) ratio (SLR) and C-reactive protein (CRP) were included for prognostic model construction. The C-index of the prognostic model was 0.759 (95% CI 0.723-0.797) in the development cohort and 0.796 (95% CI 0.737-0.855) in the validation cohort, and its predictive ability was better than TNM stage and treatment. The TD-ROC showed similar results. K-M survival analysis showed that NV-HCC patients with low risk scores had a better prognosis (P < 0.05). A nomogram based on the prognostic model, TNM stage, and treatment was constructed with sufficient discriminatory power with C-indexes of 0.78 and 0.85 in the development and validation cohort, respectively.
For NV-HCC, this prognostic model could predict an OS benefit for patients, which may assist clinicians in designing individualized therapeutic strategies.
在肝细胞癌(HCC)中,非病毒相关性肝细胞癌(NV-HCC)的发病率正在稳步上升。本研究的目的是建立一个预后模型,以评估NV-HCC患者的总生存期(OS)。
本研究共纳入261例NV-HCC患者。采用LASSO-Cox回归分析建立预后模型。通过一致性指数(C指数)和时间依赖性受试者工作特征曲线(TD-ROC)评估预后能力。采用Kaplan-Meier(K-M)生存分析评估在根据预后模型风险评分分层的各个亚组中的预测能力。通过整合预后模型、TNM分期和治疗建立生存预测列线图。
根据LASSO-Cox回归结果,纳入结节数量、淋巴细胞与单核细胞比值(LMR)、预后营养指数(PNI)、碱性磷酸酶(ALP)、天冬氨酸氨基转移酶(AST)/丙氨酸氨基转移酶(ALT)比值(SLR)和C反应蛋白(CRP)用于构建预后模型。预后模型在开发队列中的C指数为0.759(95%CI 0.723-0.797),在验证队列中的C指数为0.796(95%CI 0.737-0.855),其预测能力优于TNM分期和治疗。TD-ROC显示了相似的结果。K-M生存分析表明,低风险评分的NV-HCC患者预后较好(P<0.05)。基于预后模型、TNM分期和治疗构建的列线图具有足够的鉴别力,在开发队列和验证队列中的C指数分别为0.78和0.85。
对于NV-HCC,该预后模型可以预测患者的OS获益,这可能有助于临床医生设计个体化的治疗策略。