Department of Pharmacoepidemiology and Clinical Pharmacology, Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht, The Netherlands.
Eur J Epidemiol. 2013 Apr;28(4):291-9. doi: 10.1007/s10654-013-9766-2. Epub 2013 Jan 25.
Stratification and conditioning on time-varying cofounders which are also intermediates can induce collider-stratification bias and adjust-away the (indirect) effect of exposure. Similar bias could be expected when one conditions on time-dependent PS. We explored collider-stratification and confounding bias due to conditioning or stratifying on time-dependent PS using a clinical example on the effect of inhaled short- and long-acting beta2-agonist use (SABA and LABA, respectively) on coronary heart disease (CHD). In an electronic general practice database we selected a cohort of patients with an indication for SABA and/or LABA use and ascertained potential confounders and SABA/LABA use per three month intervals. Hazard ratios (HR) were estimated using PS stratification as well as covariate adjustment and compared with those of Marginal Structural Models (MSMs) in both SABA and LABA use separately. In MSMs, censoring was accounted for by including inverse probability of censoring weights.The crude HR of CHD was 0.90 [95 % CI: 0.63, 1.28] and 1.55 [95 % CI: 1.06, 2.62] in SABA and LABA users respectively. When PS stratification, covariate adjustment using PS, and MSMs were used, the HRs were 1.09 [95 % CI: 0.74, 1.61], 1.07 [95 % CI: 0.72, 1.60], and 0.86 [95 % CI: 0.55, 1.34] for SABA, and 1.09 [95 % CI: 0.74, 1.62], 1.13 [95 % CI: 0.76, 1.67], 0.77 [95 % CI: 0.45, 1.33] for LABA, respectively. Results were similar for different PS methods, but higher than those of MSMs. When treatment and confounders vary during follow-up, conditioning or stratification on time-dependent PS could induce substantial collider-stratification or confounding bias; hence, other methods such as MSMs are recommended.
分层和调整随时间变化的协变量,这些协变量也是中间变量,可能会导致混杂分层偏差,并调整暴露的(间接)效应。当对时间依赖的 PS 进行条件处理时,可能会出现类似的偏差。我们使用吸入短效和长效β2-激动剂(分别为 SABA 和 LABA)对冠心病(CHD)影响的临床示例,探讨了由于对时间依赖的 PS 进行条件处理或分层而导致的混杂分层偏差和混杂偏差。在电子全科医生数据库中,我们选择了一个有 SABA 和/或 LABA 使用指征的患者队列,并确定了潜在的混杂因素和 SABA/LABA 使用每三个月间隔。使用 PS 分层以及协变量调整来估计风险比(HR),并将其与 SABA 和 LABA 单独使用的边际结构模型(MSMs)进行比较。在 MSMs 中,通过包含倒数 censoring 权重来考虑 censoring。CHD 的粗 HR 分别为 SABA 和 LABA 使用者的 0.90 [95 % CI:0.63,1.28]和 1.55 [95 % CI:1.06,2.62]。当使用 PS 分层、使用 PS 进行协变量调整和 MSMs 时,HR 分别为 SABA 的 1.09 [95 % CI:0.74,1.61]、1.07 [95 % CI:0.72,1.60]和 0.86 [95 % CI:0.55,1.34],以及 LABA 的 1.09 [95 % CI:0.74,1.62]、1.13 [95 % CI:0.76,1.67]、0.77 [95 % CI:0.45,1.33]。对于不同的 PS 方法,结果相似,但高于 MSMs。当治疗和混杂因素在随访期间发生变化时,对时间依赖的 PS 进行条件处理或分层可能会导致严重的混杂分层或混杂偏差;因此,建议使用其他方法,如 MSMs。