Wang Xin, Xu Jing, Jia Zhenya, Sun Guoping
Department of Oncology, the First Affiliated Hospital of Anhui Medical University, Hefei, China.
Medicine (Baltimore). 2024 Dec 13;103(50):e40889. doi: 10.1097/MD.0000000000040889.
Hepatocellular carcinoma (HCC) is among the most prevalent malignant tumors, but the current staging system has limited efficacy in predicting HCC prognosis. The authors sought to develop and validate a nomogram model for predicting overall survival (OS) in HCC patients primarily undergoing surgery or loco-regional therapy. Patients diagnosed with HCC from January 2017 to June 2023 were enrolled in the study. The data were randomly split into a training cohort and a validation cohort. Utilizing univariate and multivariate Cox regression analyses, independent risk factors for OS were identified, and a nomogram model was constructed to predict patient survival. Therapy, body mass index, portal vein tumor thrombus, leukocyte, γ-glutamyl transpeptidase to platelet ratio, monocyte to lymphocyte ratio, and prognostic nutritional index were used to build the nomogram for OS. The nomogram demonstrated strong predictive ability, with high C-index values (0.745 for the training cohort and 0.650 for the validation cohort). ROC curves, calibration plots, and DCA curves all indicated satisfactory performance of the nomogram. Kaplan-Meier curve analysis showed a significant difference in prognosis between patients in the low- and high- risk groups. This nomogram provides precise survival predictions for HCC patients and helps identify individuals with varying prognostic risks, emphasizing the need for individualized follow-up and treatment plans.
肝细胞癌(HCC)是最常见的恶性肿瘤之一,但目前的分期系统在预测HCC预后方面效果有限。作者旨在开发并验证一种列线图模型,用于预测主要接受手术或局部区域治疗的HCC患者的总生存期(OS)。研究纳入了2017年1月至2023年6月期间诊断为HCC的患者。数据被随机分为训练队列和验证队列。利用单因素和多因素Cox回归分析,确定OS的独立危险因素,并构建列线图模型来预测患者生存。治疗、体重指数、门静脉肿瘤血栓、白细胞、γ-谷氨酰转肽酶与血小板比值、单核细胞与淋巴细胞比值以及预后营养指数被用于构建OS列线图。该列线图显示出强大的预测能力,C指数值较高(训练队列为0.745,验证队列为0.650)。ROC曲线、校准图和DCA曲线均表明列线图的性能令人满意。Kaplan-Meier曲线分析显示低风险组和高风险组患者的预后存在显著差异。该列线图为HCC患者提供了精确的生存预测,并有助于识别具有不同预后风险的个体,强调了个性化随访和治疗计划的必要性。