Department of Hepatobiliary Surgery, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, 350025, China.
Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, Fujian, China.
Sci Rep. 2024 Nov 15;14(1):28103. doi: 10.1038/s41598-024-79760-x.
Narrow resection margin hepatocellular carcinoma (NRM-HCC) has a high incidence of early recurrence. Our study was designed to identify prognostic factors in patients with NRM-HCC, establish and validate a nomogram model to predict early recurrence of NRM-HCC patients.
We retrospectively analyzed data from 2957 NRM-HCC patients who underwent radical hepatectomy at three medical centers between December 2009 and January 2015. Patients were randomly assigned to a training cohort (n = 2069) and a validation cohort (n = 888). Using univariate and multivariate COX regression to determine early relapse factors in NRM-HCC patients, and used these factors to construct a nomogram. The accuracy of the prediction was evaluated using the C-index, receiver operating characteristic (ROC) and calibration curve. Decision curve analysis (DCA) assessed the predictive value of the models. Finally, the recurrence-free survival of different risks was analyzed using Kaplan-Meier (K-M) method.
The nomogram of NRM model contains alpha-fetoprotein (AFP), alkaline phosphatase (ALP), tumor size, tumor number, microvascular invasion (MVI), tumor capsular, and satellite nodules. The model shows good discrimination with C-indexes of 0.71 (95% CI: 0.69-0.72) and 0.72 (95% CI: 0.70-0.75) in the train cohort and test cohort respectively. Decision curve analysis demonstrated that the model is clinically useful and the calibration of our model was favorable. Our model stratified patients into two different risk groups, which exhibited significantly different early recurrence. The web-based tools are convenient for clinical practice.
NRM model demonstrated favorable performance in predicting early recurrence in NRM-HCC patients. This novel model will be helpful to guide postoperative follow-up and adjuvant therapy.
窄切缘肝癌（NRM-HCC）的早期复发率较高。本研究旨在确定 NRM-HCC 患者的预后因素，建立并验证预测 NRM-HCC 患者早期复发的列线图模型。
我们回顾性分析了 2009 年 12 月至 2015 年 1 月在三家医疗机构接受根治性肝切除术的 2957 例 NRM-HCC 患者的数据。患者被随机分配到训练队列（n=2069）和验证队列（n=888）。使用单因素和多因素 COX 回归确定 NRM-HCC 患者的早期复发因素，并使用这些因素构建列线图。使用 C 指数、接受者操作特征（ROC）曲线和校准曲线评估预测的准确性。决策曲线分析（DCA）评估模型的预测价值。最后，使用 Kaplan-Meier（K-M）法分析不同风险的无复发生存率。
NRM 模型的列线图包含甲胎蛋白（AFP）、碱性磷酸酶（ALP）、肿瘤大小、肿瘤数量、微血管侵犯（MVI）、肿瘤包膜和卫星结节。该模型在训练队列和验证队列中的 C 指数分别为 0.71（95%CI：0.69-0.72）和 0.72（95%CI：0.70-0.75），具有良好的区分度。决策曲线分析表明该模型具有临床应用价值，且校准效果良好。我们的模型将患者分为两个不同的风险组，两组的早期复发率有显著差异。该网络工具方便临床实践。
NRM 模型在预测 NRM-HCC 患者的早期复发方面表现出良好的性能。该新型模型将有助于指导术后随访和辅助治疗。
