基于贝叶斯Cox回归模型分析耐多药肺结核患者死亡的影响因素  

Influencing factors of death in patients with MDR-TB based on Bayesian Cox regression model

作　　者：王智永 张宇琦 高文龙[2] 李宗煜 李明 罗秋霞 向媛媛 包凯 WANG Zhiyong;ZHANG Yuqi;GAO Wenlong;LI Zongyu;LI Ming;LUO Qiuxia;XIANG Yuanyuan;BAO Kai(Lanzhou Pulmonary Hospital,Lanzhou 730030;Department of Epidemiology and Health Statistics,School of Public Health,Lanzhou University,Lanzhou 730000,China)

机构地区：[1]兰州市肺科医院,兰州730030 [2]兰州大学公共卫生学院流行病与卫生统计学研究所,兰州730000

出　　处：《中南大学学报（医学版）》2023年第11期1659-1668,共10页Journal of Central South University ：Medical Science

基　　金：兰州市人才创新创业项目(2020-RC-76)。

摘　　要：目的:耐多药肺结核(multidrug-resistant tuberculosis,MDR-TB)具有较高的病死率,一直以来都是全球结核病防控工作的难点之一。分析MDR-TB患者不良结局的影响因素有助于改善MDR-TB患者的程序化管理,优化MDR-TB的治疗策略。在分析随访数据时,Cox比例风险回归模型是一种重要的多因素分析方法,但其存在较大的应用局限性,如难以处理样本量小等实际问题对模型的影响。基于此,本研究分别采用贝叶斯Cox回归模型和常规Cox回归模型,分析MDR-TB患者在抗结核治疗期间死亡的影响因素,并比较这2种方法在应用中的差异。方法:数据资料来自2017年11月1日至2021年3月31日在兰州市肺科医院接受治疗的388例MDR-TB患者。采用生存分析方法分析MDR-TB患者在治疗期间的死亡情况及其影响因素。分别构建常规Cox回归模型和贝叶斯Cox回归模型来估计MDR-TB患者死亡影响因素的风险比(hazard ratio,HR)及其95%置信区间(95%confidence interval,95%CI),模型的参数估计可靠性通过各自变量的参数标准差和HR值的95%CI来判断,参数标准差和95%CI范围越小,模型的估计结果越可靠。结果:纳入研究的388例MDR-TB患者的生存时间为10.18(4.26,18.13)个月,最长生存时间为31.90个月。观察期间共有12例因肺结核死亡,病死率为3.1%,死亡患者的生存时间为4.78(2.63,6.93)个月。50%的死亡患者出现在抗结核治疗的前5个月,最后一个死亡患者出现在治疗的第13个月。常规Cox回归模型分析结果显示:有合并症的患者死亡风险约为无合并症者的6.96倍(HR=6.96,95%CI 2.00~24.24;P=0.002);接受定期随访患者的死亡风险比未接受定期随访患者降低约81%(HR=0.19,95%CI 0.05~0.77;P=0.020)。贝叶斯Cox回归模型中,各参数的迭代历史图和BGR图(Blue/Green/Red plot)均提示模型的收敛效果良好,其参数估计结果显示:首次痰培养结果阳性的患者死亡风险低于阴性患者(HR=0.33,95%CI 0.08~0.8Objective:Multidrug-resistant tuberculosis(MDR-TB)has a high mortality and is always one of the major challenges in global TB prevention and control.Analyzing the factors that may impact the adverse outcomes of MDR-TB patients is helpful for improving the systematic management and optimizing the treatment strategies for MDR-TB patients.For follow-up data,the Cox proportional hazards regression model is an important multifactor analysis method.However,the method has significant limitations in its application,such as the fact that it is difficult to deal with the impacts of small sample sizes and other practical issues on the model.Therefore,Bayesian and conventional Cox regression models were both used in this study to analyze the influencing factors of death in MDR-TB patients during the anti-TB therapy,and compare the differences between these 2 methods in their application.Methods:Data were obtained from 388 MDR-TB patients treated at Lanzhou Pulmonary Hospital from November 1,2017 to March 31,2021.Survival analysis was employed to analyze the death of MDR-TB patients during the therapy and its influencing factors.Conventional and Bayesian Cox regression models were established to estimate the hazard ratios(HR)and their 95%confidence interval(95%CI)for the factors affecting the death of MDR-TB patients.The reliability of parameter estimation in these 2 models was assessed by comparing the parameter standard deviation and 95%CI of each variable.The smaller parameter standard deviation and narrower 95%CI range indicated the more reliable parameter estimation.Results:The median survival time(1st quartile,3rd quartile)of the 388 MDR-TB patients included in the study was 10.18(4.26,18.13)months,with the longest survival time of 31.90 months.Among these patients,a total of 12 individuals died of MDR-TB and the mortality was 3.1%.The median survival time(1st quartile,3rd quartile)for the deceased patients was 4.78(2.63,6.93)months.The majority of deceased patients,accounting for 50%,experienced death within the first

关 键 词：贝叶斯理论 COX回归模型 耐多药肺结核 风险比 影响因素 

分 类 号：R521[医药卫生—内科学]