Ding Dong-Yang, Liu Lei, Li He-Lin, Gan Xiao-Jie, Ding Wen-Bin, Gu Fang-Ming, Sun Da-Peng, Li Wen, Pan Ze-Ya, Yuan Sheng-Xian, Zhou Wei-Ping
Third Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai 200438, China.
Department of Radiodiagnosis, Eastern Hepatobiliary Surgery Hospital, Naval Medical University, Shanghai 200438, China.
Hepatobiliary Pancreat Dis Int. 2023 Feb;22(1):72-80. doi: 10.1016/j.hbpd.2022.04.002. Epub 2022 Apr 6.
Early singular nodular hepatocellular carcinoma (HCC) is an ideal surgical indication in clinical practice. However, almost half of the patients have tumor recurrence, and there is no reliable prognostic prediction tool. Besides, it is unclear whether preoperative neoadjuvant therapy is necessary for patients with early singular nodular HCC and which patient needs it. It is critical to identify the patients with high risk of recurrence and to treat these patients preoperatively with neoadjuvant therapy and thus, to improve the outcomes of these patients. The present study aimed to develop two prognostic models to preoperatively predict the recurrence-free survival (RFS) and overall survival (OS) in patients with singular nodular HCC by integrating the clinical data and radiological features.
We retrospective recruited 211 patients with singular nodular HCC from December 2009 to January 2019 at Eastern Hepatobiliary Surgery Hospital (EHBH). They all met the surgical indications and underwent radical resection. We randomly divided the patients into the training cohort (n =132) and the validation cohort (n = 79). We established and validated multivariate Cox proportional hazard models by the preoperative clinicopathologic factors and radiological features for association with RFS and OS. By analyzing the receiver operating characteristic (ROC) curve, the discrimination accuracy of the models was compared with that of the traditional predictive models.
Our RFS model was based on HBV-DNA score, cirrhosis, tumor diameter and tumor capsule in imaging. RFS nomogram had fine calibration and discrimination capabilities, with a C-index of 0.74 (95% CI: 0.68-0.80). The OS nomogram, based on cirrhosis, tumor diameter and tumor capsule in imaging, had fine calibration and discrimination capabilities, with a C-index of 0.81 (95% CI: 0.74-0.87). The area under the receiver operating characteristic curve (AUC) of our model was larger than that of traditional liver cancer staging system, Korea model and Nomograms in Hepatectomy Patients with Hepatitis B Virus-Related Hepatocellular Carcinoma, indicating better discrimination capability. According to the models, we fitted the linear prediction equations. These results were validated in the validation cohort.
Compared with previous radiography model, the new-developed predictive model was concise and applicable to predict the postoperative survival of patients with singular nodular HCC. Our models may preoperatively identify patients with high risk of recurrence. These patients may benefit from neoadjuvant therapy which may improve the patients' outcomes.
早期单发性结节性肝细胞癌（HCC）是临床实践中理想的手术指征。然而，几乎一半的患者会出现肿瘤复发，且尚无可靠的预后预测工具。此外，对于早期单发性结节性HCC患者是否需要术前新辅助治疗以及哪些患者需要这种治疗尚不清楚。识别复发高危患者并对这些患者进行术前新辅助治疗从而改善其预后至关重要。本研究旨在通过整合临床数据和影像学特征，建立两个预后模型以术前预测单发性结节性HCC患者的无复发生存期（RFS）和总生存期（OS）。
我们回顾性纳入了2009年12月至2019年1月在东方肝胆外科医院（EHBH）就诊的211例单发性结节性HCC患者。他们均符合手术指征并接受了根治性切除术。我们将患者随机分为训练队列（n = 132）和验证队列（n = 79）。我们通过术前临床病理因素和影像学特征建立并验证了多因素Cox比例风险模型，以分析其与RFS和OS的相关性。通过分析受试者工作特征（ROC）曲线，将模型的判别准确性与传统预测模型进行比较。
我们的RFS模型基于HBV-DNA评分、肝硬化、肿瘤直径和影像学上的肿瘤包膜。RFS列线图具有良好的校准和判别能力，C指数为0.74（95%CI：0.68 - 0.80）。基于肝硬化、肿瘤直径和影像学上的肿瘤包膜的OS列线图具有良好的校准和判别能力，C指数为0.81（95%CI：0.74 - 0.87）。我们模型的受试者工作特征曲线（AUC）下面积大于传统肝癌分期系统、韩国模型以及《乙型肝炎病毒相关肝细胞癌肝切除患者列线图》，表明判别能力更好。根据模型，我们拟合了线性预测方程。这些结果在验证队列中得到了验证。
与先前的影像学模型相比，新开发的预测模型简洁且适用于预测单发性结节性HCC患者的术后生存情况。我们的模型可在术前识别复发高危患者。这些患者可能从新辅助治疗中获益，这可能改善患者的预后。
