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作 者:陆辉荣 邓恋[1] 卢美君 刘少兵[1] 陈熙[1] LU Huirong;DENG Lian;LU Meijun;LIU Shaobing;CHEN Xi(Nanxishan Hospital of Guangxi Zhuang Autonomous Region,Guangxi Guilin 541001,China)
机构地区:[1]广西壮族自治区南溪山医院,广西桂林541001
出 处:《现代肿瘤医学》2025年第1期73-80,共8页Journal of Modern Oncology
基 金:广西桂林市自筹经费科技项目(编号:20220122z)。
摘 要:目的:旨在建立并验证一种新的列线图模型,以预测接受仑伐替尼治疗的不可手术切除肝细胞癌(unresectable hepatocellular carcinoma,uHCC)患者的生存结果。方法:回顾性纳入接受仑伐替尼治疗的170例uHCC患者的临床资料并随机分为两个队列(训练队列:n=118;验证队列:n=52)。采用单因素分析筛选可能影响总生存期(OS)的潜在因素,使用多变量Cox回归评估影响预后的独立因子并构建列线图模型,通过一致性指数(C-index)、校准曲线和决策曲线分析(DCA)以评估模型性能和预测准确性。结果:最终选择6个影响预后的因素来构建列线图模型。列线图在训练队列和验证队列的C指数分别为0.763、0.784,校准曲线显示预测概率与实际结果之间具有良好的一致性。根据列线图得分将整个队列分为低、高危组,两组的中位总生存期(mOS)分别为15.5个月和12.1个月(P=0.000)。结论:本研究中的列线图模型展现出了良好的预测性能,能较准确地预测接受仑伐替尼治疗的uHCC患者的生存结局。Objective:To develop and validate a nomogram model for predicting the survival outcomes of unresectable hepatocellular carcinoma(uHCC)patients treated with lenvatinib.Methods:We retrospectively included 170 uHCC patients treated with lenvatinib(training cohort:n=118,validation cohort:n=52).Univariate Cox regression was used to screen for potential factors affecting OS,and multivariate Cox analysis was used to assess independent prognostic factors and construct the nomogram model.The model's performance and predictive accuracy were evaluated using the concordance index(C-index),calibration curves,and decision curve analysis(DCA).Results:The final model was built using six factors that affect prognosis.The C-index of the nomogram in the training cohort and validation cohort was 0.763 and 0.784 respectively.Calibration curve showed good agreement between predicted probabilities and actual outcomes.Based on the nomogram scores,the mOS for low and high-risk groups was 15.5 and 12.1 months,respectively(P=0.000).Conclusion:The nomogram model in this study demonstrated favorable predictive performance,capable of accurately predicting the survival outcomes of uHCC patients receiving lenvatinib treatment.
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