OHCCPredictor: an online risk stratification model for predicting survival duration of older patients with hepatocellular carcinoma

• Published in: Hepatology international 2024-04, Vol.18 (2), p.550-567
• Main Authors: Tan, Juntao, Yu, Yue, Lin, Xiantian, He, Yuxin, Jin, Wen, Qian, Hong, Li, Ying, Xu, Xiaomei, Zhao, Yuxi, Ning, Jianwen, Zhang, Zhengyu, Chen, Jingjing, Wu, Xiaoxin
• Format: Article
• Language: English
• Subjects: Bone surgery; Calibration; Chemotherapy; Colorectal Surgery; Decision analysis; Epidemiology; Fibrosis; Health services; Hepatocellular carcinoma; Hepatology; Liver cancer; Liver transplantation; Lungs; Marital status; Medical prognosis; Medicine; Medicine & Public Health; Metastases; Metastasis; Nomograms; Older people; Original; Original Article; Patients; Prediction models; Prognosis; Regression analysis; Risk; Sex; Statistical analysis; Subgroups; Surgery; Survival; Tumors; α-Fetoprotein
• ISSN: 1936-0533; 1936-0541
• DOI: 10.1007/s12072-023-10516-x

Background Although the elderly constitute more than a third of hepatocellular carcinoma (HCC) patients, they have not been adequately represented in treatment and prognosis studies. Thus, there is not enough evidence to guide the treatment of such patients. The objective of this study is to identify the prognostic factors of older patients with HCC and to construct a new prognostic model for predicting their overall survival (OS). Methods 2,721 HCC patients aged ≥ 65 were extracted from the public database-Surveillance, Epidemiology, and End Results (SEER) and randomly divided into a training set and an internal validation set with a ratio of 7:3. 101 patients diagnosed from 2008 to 2017 in the First Affiliated Hospital of Zhejiang University School of Medicine were identified as the external validation set. Univariate cox regression analyses and multivariate cox regression analyses were adopted to identify these independent prognostic factors. A predictive nomogram-based risk stratification model was proposed and evaluated using area under the receiver operating characteristic curve (AUC), calibration curves, and a decision curve analysis (DCA). Results These attributes including age, sex, marital status, T stage, N stage, surgery, chemotherapy, tumor size, alpha-fetoprotein level, fibrosis score, bone metastasis, lung metastasis, and grade were the independent prognostic factors for older patients with HCC while predicting survival duration. We found that the nomogram provided a good assessment of OS at 1, 3, and 5 years in older patients with HCC (1-year OS: (training set: AUC = 0.823 (95%CI 0.803–0.845); internal validation set: AUC = 0.847 (95%CI 0.818–0.876); external validation set: AUC = 0.732 (95%CI 0.521–0.943)); 3-year OS: (training set: AUC = 0.813 (95%CI 0.790–0.837); internal validation set: AUC = 0.844 (95%CI 0.812–0.876); external validation set: AUC = 0.780 (95%CI 0.674–0.887)); 5-year OS: (training set: AUC = 0.839 (95%CI 0.806–0.872); internal validation set: AUC = 0.800 (95%CI 0.751–0.849); external validation set: AUC = 0.821 (95%CI 0.727–0.914)). The calibration curves showed that the nomogram was with strong calibration. The DCA indicated that the nomogram can be used as an effective tool in clinical practice. The risk stratification of all subgroups was statistically significant ( p