老年人脉压变化与全因死亡关联的贝叶斯联合模型应用研究  

Application of a bayesian joint model for the association of changes in pulse pressure and all-cause mortality in the elderly

作　　者：谢纬华 余小金[1] 戴品远 孙金芳[1] 王莉娜[1] 覃玉[2] 武鸣[2] 赵健 XIE Wei-hua;YU Xiao-jin;DAI Pin-yuan;SUN Jin-fang;WANG Li-na;QIN Yu;WU Ming;ZHAO Jian(Department of Epidemiology and Health Statistics,School of Public Health,Southeast University,Nanjing 210009,China;Department of Chronic Non-Communicable Disease Control and Prevention,Jiangsu Provincial Center for Disease Control and Prevention,Nanjing 210009,China)

机构地区：[1]东南大学公共卫生学院流行病与卫生统计学系,南京210009 [2]江苏省疾病预防控制中心慢性非传染病防制所,南京210009

出　　处：《中华疾病控制杂志》2021年第1期72-77,共6页Chinese Journal of Disease Control & Prevention

基　　金：国家自然科学基金(81673274)。

摘　　要：目的以老年人脉压变化与全因死亡的关联研究为背景,探讨贝叶斯联合模型拟合相互关联的纵向结局与生存结局时的应用策略和统计性能,为类似特征资料的分析提供方法学指导。方法本研究以自然三次样条函数拟合纵向测量脉压的非线性混合效应模型,并采用B样条法构建全死因生存结局的基线风险函数,通过共享的随机效应关联两个过程建立贝叶斯联合模型,运用Gibbs抽样进行模型参数计算,并将贝叶斯联合模型结果与经典两步法联合模型进行比较。结果贝叶斯联合模型结果显示基线脉压越高(α1=0.72, 95%CI:0.43~1.13),第0~3年、3~6年、6~9年脉压升高越快(α21=0.34, 95%CI:0.20~0.45;α22=0.45, 95%CI:0.10~0.75;α23=0.42, 95%CI:0.24~0.62),老年人全因死亡风险越高。贝叶斯法和两步法联合模型在参数点估计方向上具有一致性,贝叶斯法的区间宽度大于两步法。结论当纵向与生存数据存在关联时,贝叶斯联合模型是对纵向与生存数据联合分析合理有效的统计方法。研究显示,老年人基线脉压过高和脉压升高过快均会造成更高的死亡风险。Objective To explore application strategies and statistical performance when fitting Bayesian joint models to interrelate longitudinal and survival outcomes, and provide methodological guidance for the analysis of similar data. Methods A nonlinear mixed-effects model of longitudinally measured pulse pressure was fitted with a natural cubic spline function, and a B-spline method was used to construct the baseline hazard function for all-cause survival data. A Bayesian joint model was established by associating two processes through shared random effects and Gibbs sampling was used to calculate model parameters. The results of Bayesian joint model were compared with the classical two-stage joint model. Results The Bayesian joint model showed a higher baseline pulse pressure(α1=0.72, 95% CI: 0.43-1.13) and faster rise in pulse pressure in years 0 to 3, 3 to 6, and 6 to 9(α21=0.34, 95% CI: 0.20-0.45;α22= 0.45, 95% CI: 0.10-0.75;α23=0.42, 95% CI: 0.24-0.62), which may contribute to a higher risk of all-cause death in the elderly. Bayesian and two-stage joint models were consistent in the direction of parameter point estimates, with Bayesian interval widths greater than two-stage methods. Conclusions Bayesian joint model is a reasonably valid statistical method for joint analysis of longitudinal and survival data when there is an association between them. This study has shown that both high baseline pulse pressure and rapid increases in pulse pressure in older adults are associated with higher all-cause mortality.

关 键 词：纵向数据 生存数据 老年人脉压 全因死亡 贝叶斯联合模型 两步法联合模型 

分 类 号：R181[医药卫生—流行病学]