Department of Oncology, The Affiliated Hospital of Southwest Medical University, 646000 Luzhou, China.
Department of Obstetrics and Gynecology, The Affiliated Hospital of Southwest Medical University, 646000 Luzhou, China.
Ann Hepatol. 2023 Jul-Aug;28(4):101109. doi: 10.1016/j.aohep.2023.101109. Epub 2023 Apr 24.
We initiated this multicenter study to integrate important risk factors to create a nomogram for hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) for clinician decision-making.
Between April 2011 and March 2022, 2281 HCC patients with an HBV-related diagnosis were included. All patients were randomly divided into two groups in a ratio of 7:3 (training cohort, n = 1597; validation cohort, n = 684). The nomogram was built in the training cohort via Cox regression model and validated in the validation cohort.
Multivariate Cox analyses revealed that the portal vein tumor thrombus, Child-Pugh class, tumor diameter, alanine aminotransferase level, tumor number, extrahepatic metastases, and therapy were independent predictive variables impacting overall survival. We constructed a new nomogram to predict 1-, 2-, and 3-year survival rates based on these factors. The nomogram-related receiver operating characteristics (ROC) curves indicated that the area under the curve (AUC) values were 0.809, 0.806, and 0.764 in predicting 1-, 2-, and 3-year survival rates, respectively. Furthermore, the calibration curves revealed good agreement between real measurements and nomogram predictions. The decision curve analyses (DCA) curves demonstrated excellent therapeutic application potential. In addition, stratified by risk scores, low-risk groups had longer median OS than medium-high-risk groups (p < 0.001).
The nomogram we constructed showed good performance in predicting the 1-year survival rate for HBV- related HCC.
我们启动了这项多中心研究，以整合重要的风险因素，为临床医生的决策制定创建一个用于乙型肝炎病毒（HBV）相关肝细胞癌（HCC）的诺莫图。
2011 年 4 月至 2022 年 3 月期间，共纳入了 2281 例 HBV 相关 HCC 患者。所有患者按 7:3 的比例随机分为两组（训练队列，n=1597；验证队列，n=684）。通过 Cox 回归模型在训练队列中构建诺莫图，并在验证队列中进行验证。
多变量 Cox 分析显示，门静脉癌栓、Child-Pugh 分级、肿瘤直径、丙氨酸氨基转移酶水平、肿瘤数量、肝外转移和治疗是影响总生存的独立预测变量。我们根据这些因素构建了一个新的诺莫图来预测 1、2 和 3 年的生存率。诺莫图相关的接受者操作特征（ROC）曲线表明，预测 1、2 和 3 年生存率的曲线下面积（AUC）值分别为 0.809、0.806 和 0.764。此外，校准曲线显示了真实测量值与诺莫图预测值之间的良好一致性。决策曲线分析（DCA）曲线表明了该模型具有出色的治疗应用潜力。此外，根据风险评分分层，低风险组的中位 OS 明显长于中高危组（p<0.001）。
我们构建的诺莫图在预测 HBV 相关 HCC 的 1 年生存率方面表现良好。
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