Guo Dandan, Li Jianjun, Zhao Peng, Mei Tingting, Li Kang, Zhang Yonghong
Interventional Therapy Center for Oncology, Beijing You'An Hospital, Capital Medical University, Beijing, China.
Biomedical Information Center, Beijing You'An Hospital, Capital Medical University, Beijing, China.
Front Oncol. 2024 May 16;14:1398968. doi: 10.3389/fonc.2024.1398968. eCollection 2024.
The study aimed to build and validate a competitive risk nomogram to predict the cumulative incidence of hepatocellular carcinoma (HCC) for patients with hepatitis B virus (HBV)-related cirrhosis.
A total of 1401 HBV-related cirrhosis patients were retrospectively enrolled from January 1, 2011 to December 31, 2014. Application of 20 times imputation dealt with missing data using multiple imputation by chained equations (MICE). The patients were randomly divided into a training set ( = 1017) and a validation set ( = 384) at a ratio of 3:1. A prediction study was carried out using a competing risk model, where the event of interest was HCC and the competing events were death and liver transplantation, and subdistribution hazard ratios (sHRs) with 95% CIs were reported. The multivariate competing risk model was constructed and validated.
There was a negligible difference between the original database and the 20 imputed datasets. At the end of follow-up, the median follow-up time was 69.9 months (interquartile range: 43.8-86.6). There were 31.5% (442/1401) of the patients who developed HCC, with a 5-year cumulative incidence of 22.9 (95%CI, 20.8%-25.2%). The univariate and multivariate competing risk regression and construction of the nomogram were performed in 20 imputed training datasets. Age, sex, antiviral therapy history, hepatitis B e antigen, alcohol drinking history, and alpha-fetoprotein levels were included in the nomogram. The area under receiver operating characteristic curve values at 12, 24, 36, 60, and 96 months were 0.68, 0.69, 0.70, 0.68, and 0.80, and the Brier scores were 0.30, 0.25, 0.23, 0.21, and 0.20 in the validation set. According to the cumulative incidence function, the nomogram effectively screened out high-risk HCC patients from low-risk patients in the presence of competing events (Fine-Gray test < 0.001).
The competitive risk nomogram was allowed to be used for predicting HCC risk in individual patients with liver cirrhosis, taking into account both the association between risk factors and HCC and the modifying effect of competition events on this association.
本研究旨在构建并验证一种竞争风险列线图，以预测乙型肝炎病毒（HBV）相关肝硬化患者肝细胞癌（HCC）的累积发病率。
回顾性纳入2011年1月1日至2014年12月31日期间共1401例HBV相关肝硬化患者。采用链式方程多重填补法（MICE）进行20次填补以处理缺失数据。患者按3:1的比例随机分为训练集（n = 1017）和验证集（n = 384）。使用竞争风险模型进行预测研究，其中感兴趣的事件是HCC，竞争事件是死亡和肝移植，并报告了95%置信区间的亚分布风险比（sHRs）。构建并验证了多变量竞争风险模型。
原始数据库与20个填补数据集之间的差异可忽略不计。随访结束时，中位随访时间为69.9个月（四分位间距：43.8 - 86.6）。有31.5%（442/1401）的患者发生了HCC，5年累积发病率为22.9（95%CI，20.8% - 25.2%）。在20个填补后的训练数据集中进行了单变量和多变量竞争风险回归以及列线图的构建。列线图纳入了年龄、性别、抗病毒治疗史、乙肝e抗原、饮酒史和甲胎蛋白水平。验证集中12、24、36、60和96个月时的受试者操作特征曲线下面积值分别为0.68、0.69、0.70、0.68和0.80，Brier评分分别为0.
