基于LASSO-Logistic回归的原发性肝癌靶向治疗患者预后不良风险预测模型构建与验证OA
Development and validation of a LASSO-Logistic regression-based risk prediction model for poor prognosis in patients with primary liver cancer receiving targeted therapy
背景与目的:原发性肝癌(PLC)患者接受靶向治疗后的临床结局存在明显异质性,准确识别预后不良高危人群对于优化治疗决策具有重要意义.本研究分析PLC靶向治疗患者预后不良的危险因素,并构建风险预测模型. 方法:回顾性收集2016年6月—2019年6月接受靶向治疗的160例PLC患者临床资料,并进行5年随访.依据RECIST 1.1将患者分为预后良好组(112例)和预后不良组(48例).比较两组临床病理特征及实验室指标差异,采用最小绝对收缩和选择算子(LASSO)回归筛选候选变量,并进行多因素Lo‐gistic回归分析确定独立危险因素.在此基础上构建风险预测模型,通过校准曲线、Hosmer-Lemeshow检验及受试者工作特征(ROC)曲线评价模型性能. 结果:160例患者中48例(30.0%)出现预后不良.LASSO回归筛选出10个候选变量.多因素Logistic回归分析显示,肿瘤直径>5 cm(OR=3.216,95%CI=1.582~6.537)、巴塞罗那肝癌临床分期(BCLC)C期(OR=2.779,95%CI=1.367~5.649)、门静脉癌栓程氏分型Ⅱ~Ⅳ型(OR=4.573,95%CI=2.191~9.545)、包膜不完整(OR=3.099,95%CI=1.524~6.300)、肿瘤边缘连续多结节(OR=4.121,95%CI=2.027~8.377)及甲胎蛋白(AFP)升高(OR=2.380,95%CI=1.171~4.838)为预后不良的独立危险因素(均P<0.05).基于上述因素构建预测模型,其一致性指数为 0.784,Hosmer-Lemeshow 检验显示模型拟合良好(P=0.359),ROC曲线分析显示模型曲线下面积为0.851(95%CI=0.764~0.938),敏感度为0.846,特异度为0.894. 结论:肿瘤直径增大、BCLC分期进展、门静脉癌栓侵犯范围扩大、包膜不完整、肿瘤边缘连续多结节及AFP升高是PLC靶向治疗患者预后不良的独立危险因素.基于上述因素构建的LASSO-Logistic风险预测模型具有良好的校准度和区分度,可为临床风险分层和个体化治疗提供参考.
Background and Aims:Clinical outcomes after targeted therapy vary substantially among patients with primary liver cancer(PLC).Early identification of patients at high risk of poor prognosis is essential for individualized treatment and prognostic assessment.This study aimed to identify risk factors associated with poor prognosis and develop a risk prediction model for PLC patients receiving targeted therapy. Methods:Clinical data from 160 PLC patients who underwent targeted therapy between June 2016 and June 2019 were retrospectively collected and followed for 5 years.According to RECIST 1.1,patients were classified into a favorable prognosis group(n=112)and an unfavorable prognosis group(n=48).LASSO regression was used for variable selection,followed by multivariate Logistic regression to identify independent prognostic factors.A risk prediction model was established and evaluated using calibration analysis,the Hosmer-Lemeshow goodness-of-fit test,and receiver operating characteristic(ROC)curve analysis. Results:Poor prognosis occurred in 48 patients(30.0%).Ten candidate variables were selected by LASSO regression.Multivariate Logistic regression identified tumor diameter>5 cm(OR=3.216,95%CI=1.582-6.537),BCLC stage C(OR=2.779,95%CI=1.367-5.649),Cheng's classification type Ⅱ-Ⅳ portal vein tumor thrombus(OR=4.573,95%CI=2.191-9.545),incomplete tumor capsule(OR=3.099,95%CI=1.524-6.300),multinodular confluent tumor margin(OR=4.121,95%CI=2.027-8.377),and elevated AFP level(OR=2.380,95%CI=1.171-4.838)as independent predictors of poor prognosis(all P<0.05).The model demonstrated satisfactory performance,with a C-index of 0.784 and good calibration(Hosmer-Lemeshow test,P=0.359).The AUC was 0.851(95%CI=0.764-0.938),with a sensitivity of 0.846 and a specificity of 0.894. Conclusion:Large tumor size,advanced BCLC stage,extensive portal vein tumor thrombus,incomplete capsule,multinodular confluent tumor margin,and elevated AFP level are independent risk factors for poor prognosis in PLC patients receiving targeted therapy.The LASSO-Logistic regression-based model shows good discrimination and calibration and may facilitate risk stratification and individualized clinical management.
田涛;郭伟;孙晓刚;张双卫;李宁
山西省晋城市人民医院 肝胆外科,山西 晋城 048400首都医科大学附属北京友谊医院 肝胆外科,北京 100050山西省晋城市人民医院 肝胆外科,山西 晋城 048400山西省晋城市人民医院 肝胆外科,山西 晋城 048400山西省晋城市人民医院 肝胆外科,山西 晋城 048400
医药卫生
肝肿瘤靶向治疗预后危险因素
Liver NeoplasmsTargeted TherapyPrognosisRisk Factors
《中国普通外科杂志》 2026 (7)
1336-1345,10
山西省晋城市重点科技研发基金资助项目(20210105).
评论