From the Kaiser Permanente Division of Research, Oakland, CA.
Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, Boston, MA.
Epidemiology. 2020 Nov;31(6):806-814. doi: 10.1097/EDE.0000000000001246.
We use simulated data to examine the consequences of depletion of susceptibles for hazard ratio (HR) estimators based on a propensity score (PS). First, we show that the depletion of susceptibles attenuates marginal HRs toward the null by amounts that increase with the incidence of the outcome, the variance of susceptibility, and the impact of susceptibility on the outcome. If susceptibility is binary then the Bross bias multiplier, originally intended to quantify bias in a risk ratio from a binary confounder, also quantifies the ratio of the instantaneous marginal HR to the conditional HR as susceptibles are depleted differentially. Second, we show how HR estimates that are conditioned on a PS tend to be between the true conditional and marginal HRs, closer to the conditional HR if treatment status is strongly associated with susceptibility and closer to the marginal HR if treatment status is weakly associated with susceptibility. We show that associations of susceptibility with the PS matter to the marginal HR in the treated (ATT) though not to the marginal HR in the entire cohort (ATE). Third, we show how the PS can be updated periodically to reduce depletion-of-susceptibles bias in conditional estimators. Although marginal estimators can hit their ATE or ATT targets consistently without updating the PS, we show how their targets themselves can be misleading as they are attenuated toward the null. Finally, we discuss implications for the interpretation of HRs and their relevance to underlying scientific and clinical questions. See video Abstract: http://links.lww.com/EDE/B727.
我们使用模拟数据来检验基于倾向评分(PS)的危害比(HR)估计值因易感人群减少而产生的后果。首先,我们表明,易感人群的减少会使边缘 HR 向零值衰减,其衰减程度随结局的发生率、易感性的方差以及易感性对结局的影响而增加。如果易感性是二分类的,那么最初用于量化二分类混杂因素对风险比的偏差的 Bross 偏倚乘数,也可以量化随着易感人群的差异消耗,瞬时边缘 HR 与条件 HR 的比值。其次,我们展示了如何在 PS 条件下进行 HR 估计,这些估计通常介于真实条件 HR 和边缘 HR 之间,如果治疗状态与易感性强烈相关,则更接近条件 HR,如果治疗状态与易感性弱相关,则更接近边缘 HR。我们表明,易感性与 PS 的关联对处理组的边缘 HR(ATT)很重要,但对整个队列的边缘 HR(ATE)不重要。第三,我们展示了如何定期更新 PS 以减少条件估计中的易感人群消耗偏差。尽管边际估计器可以在不更新 PS 的情况下持续达到 ATE 或 ATT 目标,但我们展示了它们的目标本身是如何产生误导的,因为它们向零值衰减。最后,我们讨论了对 HR 解释的影响及其与潜在科学和临床问题的相关性。请观看视频摘要:http://links.lww.com/EDE/B727。