Zhang Chihao, Zhao Ran, Chen Fancheng, Zhu Yiming, Chen Liubo
Department of General Surgery, Shanghai Ninth People's Hospital, School of Medicine, Shanghai Jiao Tong University, Baoshan, Shanghai, China.
Division of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China.
Transl Oncol. 2021 Jan;14(1):100875. doi: 10.1016/j.tranon.2020.100875. Epub 2020 Sep 23.
The presence of microvascular invasion (MVI) is an unfavorable prognostic factor for hepatocellular carcinoma (HCC). This study aimed to construct a nomogram-based preoperative prediction model of MVI, thereby assisting to preoperatively select proper surgical procedures.
A total of 714 non-metastatic HCC patients undergoing radical hepatectomy were retrospectively selected from Zhongshan Hospital between 2010 and 2018, followed by random assignment into training (N = 520) and validation cohorts (N = 194). Nomogram-based prediction model for MVI risk was constructed by incorporating independent risk factors of MVI presence identified from multivariate backward logistic regression analysis in the training cohort. The performance of nomogram was evaluated by calibration curve and ROC curve. Finally, decision curve analysis (DCA) was used to determine the clinical utility of the nomogram.
In total, 503 (70.4%) patients presented MVI. Multivariate analysis in the training cohort revealed that age (OR: 0.98), alpha-fetoprotein (≥400 ng/mL) (OR: 2.34), tumor size (>5 cm) (OR: 3.15), cirrhosis (OR: 2.03) and γ-glutamyl transpeptidase (OR: 1.61) were significantly associated with MVI presence. The incorporation of five risk factors into a nomogram-based preoperative estimation of MVI risk demonstrated satisfactory discriminative capacity, with C-index of 0.702 and 0.690 in training and validation cohorts, respectively. Calibration curve showed good agreement between actual and predicted MVI risks. Finally, DCA revealed the clinical utility of the nomogram.
The nomogram showed a satisfactory discriminative capacity of MVI risk in HCC patients, and could be used to preoperatively estimate MVI risk, thereby establishing more rational therapeutic strategies.
微血管侵犯(MVI)的存在是肝细胞癌(HCC)的不良预后因素。本研究旨在构建基于列线图的MVI术前预测模型,从而辅助术前选择合适的手术方式。
回顾性选取2010年至2018年期间在中山医院接受根治性肝切除术的714例非转移性HCC患者,随后随机分为训练组(N = 520)和验证组(N = 194)。通过纳入训练组多因素向后逻辑回归分析确定的MVI存在的独立危险因素,构建基于列线图的MVI风险预测模型。通过校准曲线和ROC曲线评估列线图的性能。最后,采用决策曲线分析(DCA)确定列线图的临床实用性。
共有503例(70.4%)患者存在MVI。训练组的多因素分析显示,年龄(OR:0.98)、甲胎蛋白(≥400 ng/mL)(OR:2.34)、肿瘤大小(>5 cm)(OR:3.15)、肝硬化(OR:2.03)和γ-谷氨酰转肽酶(OR:1.61)与MVI的存在显著相关。将五个危险因素纳入基于列线图的MVI风险术前评估显示出令人满意的判别能力,训练组和验证组的C指数分别为0.702和0.690。校准曲线显示实际和预测的MVI风险之间具有良好的一致性。最后,DCA揭示了列线图的临床实用性。
该列线图在HCC患者中显示出令人满意的MVI风险判别能力,可用于术前评估MVI风险,从而制定更合理的治疗策略。