摘要
目的分析程序性死亡受体1(PD-1)单抗是否提高冷冻消融联合仑伐替尼治疗不可切除性肝细胞癌(uHCC)患者的疗效和安全性。方法回顾性收集2018年1月—2022年12月在解放军总医院第五医学中心治疗的uHCC患者232例,其中128例接受冷冻消融联合仑伐替尼(二联)治疗,104例接受冷冻消融联合仑伐替尼和PD-1单抗(三联)治疗,用倾向性评分匹配方法(PSM)以1∶1进行匹配,经匹配后两组各86例。评估匹配后的2组患者客观缓解率(ORR)和疾病控制率(DCR)、总生存期(OS)、无进展生存期(PFS)和不良事件发生情况。定量资料若符合正态分布2组间比较采用成组t检验;非正态分布2组间比较采用Mann-Whitney U检验。定性资料采用χ^(2)检验进行2组间比较。绘制生存曲线,运用KaplanMeier法计算2组患者的生存率,并利用Log-rank检验比较2组差异。通过Cox回归模型计算风险比(HR)和95%置信区间(95%CI),实现预后影响因素的单因素及多因素分析。结果中位随访时间为28个月,三联组死亡33例(38.0%),二联组死亡40例(46.0%)。三联治疗组的ORR和DCR较二联组明显增高(ORR:35.6%vs 14.5%,P=0.008;DCR:86.1%vs64.1%,P=0.003)。三联组的OS和PFS较二联组均显著提高(P值分别为0.045、0.026)。单因素和多因素Cox风险比例模型分析显示治疗方案(HR=0.60,P=0.038)、AFP水平(HR=2.37,P=0.001)是影响OS的独立危险因素;治疗方案(HR=0.65,P=0.025)、糖尿病(HR=1.94,P=0.005)、之前是否接受过局部治疗(HR=0.63,P=0.014)、远处转移(HR=0.58,P=0.009)是影响PFS的独立危险因素。两组患者不良反应发生率相当,无明显差异(P值均>0.05)。结论对于uHCC患者,冷冻消融联合仑伐替尼和PD-1单抗三联治疗较冷冻消融联合仑伐替尼二联治疗显著提高了疗效,改善患者生存情况,而且不增加不良反应事件,为优化不可切除性肝癌的治疗方案提供了临床依据。
Objective To investigate whether anti-PD-1 monoclonal antibody can improve the efficacy and safety of cryoablation combined with lenvatinib in the treatment of unresectable hepatocellular carcinoma(HCC).Methods A retrospective analysis was performed for 232 patients with unresectable HCC who were treated at The Fifth Medical Center of Chinese PLA General Hospital from January 2018 to December 2022,among whom 128 received cryoablation combined with lenvatinib(double combination)and 104 received cryoablation combined with lenvatinib and anti-PD-1 monoclonal antibody(triple combination).Propensity score matching was performed at a ratio of 1∶1,and finally there were 86 patients in each group.The two groups were evaluated in terms of objective response rate(ORR),disease control rate(DCR),overall survival(OS),progression-free survival(PFS),and adverse events(AEs).The independent-samples t test was used for comparison of normally distributed continuous data between two groups,and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups;the chi-square test was used for comparison of categorical data between two groups.Survival curves were plotted,and the Kaplan-Meier method was used to calculate the survival rate of patients in both groups,while the log-rank test was used for comparison between the two groups.The Cox regression model was used to calculate hazard ratio(HR)and 95%confidence interval(CI)and perform the univariate and multivariate analyses of influencing factors for prognosis.Results The median follow-up time was 28 months,and there were 33 deaths(38.0%)in the triple combination group and 40 deaths(46.0%)in the double combination group.Compared with the double combination group,the triple combination group had significantly higher ORR(35.6%vs 14.5%,P=0.008)and DCR(86.1%vs 64.1%,P=0.003).OS and PFS in the triple combination group were significantly higher than those in the double combination group(P=0.045 and 0.026).The univariate and multivariate Cox proportional-hazards regression model analyses showed that treatment regimen(HR=0.60,P=0.038)and alpha-fetoprotein level(HR=2.37,P=0.001)were independent risk factors for OS,and treatment regimen(HR=0.65,P=0.025),diabetes mellitus(HR=1.94,P=0.005),whether or not to have received local treatment(HR=0.63,P=0.014),and distant metastasis(HR=0.58,P=0.009)were independent risk factors for PFS.There was no significant difference in the incidence rate of AEs between the two groups(P>0.05).Conclusion For patients with unresectable HCC,the triple combination of cryoablation,lenvatinib,and anti-PD-1 monoclonal antibody significantly improves the treatment outcome and survival of patients compared with the double combination of cryoablation and lenvatinib,without increasing AEs,which provides a clinical basis for optimizing the treatment regimen for unresectable HCC.
作者
刘腾
常秀娟
何权威
徐然
杨永平
LIU Teng;CHANG Xiujuan;HE Quanwei;XU Ran;YANG Yongping(Division of Liver Diseases,The Fifth Medical Center of Chinese PLA General Hospital,Beijing 100039,China)
出处
《临床肝胆病杂志》
CAS
北大核心
2024年第3期539-549,共11页
Journal of Clinical Hepatology
基金
国家“十三五”科技重大专项(2018ZX10725506)
北京市自然科学基金(7212101)。