Qiao Wenying, Sheng Shugui, Li Junnan, Jin Ronghua, Hu Caixia
Beijing Key Laboratory of Emerging Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, People's Republic of China.
Beijing Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing, People's Republic of China.
J Hepatocell Carcinoma. 2024 Mar 7;11:509-523. doi: 10.2147/JHC.S450825. eCollection 2024.
The aim of the study is to identify and evaluate multifaceted factors impacting the survival of elderly cirrhotic HCC patients following ablation therapy, with the goal of constructing a nomogram to predict their 3-, 5-, and 8-year overall survival (OS).
A retrospective analysis was conducted on 736 elderly cirrhotic HCC patients who underwent ablation therapy between 2014 and 2022. LASSO regression, random survival forest (RSF), and multivariate Cox analyses were employed to identify independent prognostic factors for OS, followed by the development and validation of a predictive nomogram. Harrell's concordance index (C-index), calibration plot and decision curve analysis (DCA) were used to assess the performance of the nomogram. The nomogram was finally utilized to stratify patients into low-, intermediate-, and high-risk groups, aiming to assess its efficacy in precisely discerning individuals with diverse overall survival outcomes.
Alcohol drinking, tumor number, globulin (Glob) and prealbumin (Palb) were identified and integrated to establish a novel prognostic nomogram. The nomogram exhibited strong discriminative ability with C-indices of 0.723 (training cohort) and 0.693 (validation cohort), along with significant Area Under the Curve (AUC) values for 3-year, 5-year, and 8-year OS in both cohorts (0.758, 0.770, and 0.811 for training cohort; 0.744, 0.699 and 0.737 for validation cohort). Calibration plots substantiated its consistency, while DCA curves corroborated its clinical utility. The nomogram further demonstrated exceptional effectiveness in discerning distinct risk populations, highlighting its robust applicability for prognostic stratification.
Our study successfully developed and validated a robust nomogram model based on four key clinical parameters for predicting 3-, 5- and 8-year OS among elderly cirrhotic HCC patients following ablation therapy. The nomogram exhibited a remarkable capability in identifying high-risk patients, furnishing clinicians with invaluable insights for postoperative surveillance and tailored therapeutic interventions.
本研究旨在识别和评估影响老年肝硬化肝癌患者消融治疗后生存的多方面因素，目标是构建一个列线图来预测他们3年、5年和8年的总生存率（OS）。
对2014年至2022年间接受消融治疗的736例老年肝硬化肝癌患者进行回顾性分析。采用LASSO回归、随机生存森林（RSF）和多变量Cox分析来识别OS的独立预后因素，随后开发并验证一个预测列线图。使用Harrell一致性指数（C指数）、校准图和决策曲线分析（DCA）来评估列线图的性能。最终利用列线图将患者分为低风险、中风险和高风险组，旨在评估其在准确区分具有不同总生存结果个体方面的有效性。
确定并整合饮酒、肿瘤数量、球蛋白（Glob）和前白蛋白（Palb）以建立一个新的预后列线图。该列线图显示出强大的判别能力，训练队列的C指数为0.723，验证队列的C指数为0.693，两个队列中3年、5年和8年OS的曲线下面积（AUC）值均显著（训练队列分别为0.758、0.770和0.811；验证队列分别为0.744、0.699和0.737）。校准图证实了其一致性，而DCA曲线证实了其临床实用性。列线图在区分不同风险人群方面进一步显示出卓越的有效性，突出了其在预后分层方面的强大适用性。
我们的研究成功开发并验证了一个基于四个关键临床参数的强大列线图模型，用于预测老年肝硬化肝癌患者消融治疗后的3年、5年和8年OS。该列线图在识别高风险患者方面表现出显著能力，为临床医生提供了术后监测和个性化治疗干预的宝贵见解。
