Department V of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, 700 Moyu Road, Shanghai, 201805, P.R. China.
Department of Hepatic Surgery, The Second Affiliated Hospital of WenZhou Medical University, Wenzhou, 325027, China.
J Gastrointest Surg. 2022 Aug;26(8):1-9. doi: 10.1007/s11605-022-05326-9.
The present study aimed to establish a γ-glutamyl transpeptidase-to-albumin ratio (GAR)-based nomogram model to predict early recurrence of hepatocellular carcinoma (HCC) after radical surgery.
Patients enrolled in this study were randomly allocated into a train and validation cohort in a ratio of 7:3. The Least Absolute Shrinkage and Selection Operator (LASSO) proportional hazards model and cox regression model were combined to identify independent risk factors related to HCC recurrence. Based on these risk factors, a predictive nomogram was constructed and validated in both inner and outer test cohorts. The performance of the nomogram was evaluated by C-index, the area under the receiver operating characteristic curve (AUC), the calibration curve and decision curve analysis.
The tumor size, tumor number, BCLC stage, microvascular invasion (MVI) and GAR value were identified as independent risk factors related to HCC recurrence and used to construct the predictive nomogram. AUC of the nomogram showed satisfactory accuracy in predicting 1-, 3- and 5-year disease-free survival. The calibration curve showed agreement between the ideal and predicted values. The risk score more than 72 as calculated by the nomogram was related to early recurrence of HCC after radical surgery. DCA plots showed better clinical usability of the nomogram as compared with the BCLC staging system in all three included cohorts.
The nomogram based on the GAR value may provide a new option for screening of the target HCC cohort of patients who need anti-recurrence therapy after surgery.
本研究旨在建立基于γ-谷氨酰转肽酶/白蛋白比值（GAR）的列线图模型，以预测肝癌根治性手术后的早期复发。
本研究纳入的患者被随机分配到训练和验证队列中，比例为 7:3。最小绝对收缩和选择算子（LASSO）比例风险模型和 Cox 回归模型相结合，以确定与 HCC 复发相关的独立危险因素。基于这些危险因素，构建并在内部和外部测试队列中验证了预测列线图。通过 C 指数、受试者工作特征曲线（AUC）下面积、校准曲线和决策曲线分析评估列线图的性能。
肿瘤大小、肿瘤数量、BCLC 分期、微血管侵犯（MVI）和 GAR 值被确定为与 HCC 复发相关的独立危险因素，并用于构建预测列线图。列线图预测 1、3 和 5 年无病生存率的 AUC 显示出较好的准确性。校准曲线显示理想值和预测值之间具有一致性。根据列线图计算的风险评分大于 72 与肝癌根治性手术后的早期复发相关。DCA 图显示，与 BCLC 分期系统相比，该列线图在所有三个纳入的队列中均具有更好的临床实用性。
基于 GAR 值的列线图可能为术后需要抗复发治疗的目标 HCC 患者提供新的筛选选择。
