Guertin Jason R, Rahme Elham, Dormuth Colin R, LeLorier Jacques
Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON, Canada.
Programs for Assessment of Technology in Health, St. Joseph's Healthcare Hamilton, Hamilton, QC, Canada.
BMC Med Res Methodol. 2016 Feb 19;16:22. doi: 10.1186/s12874-016-0119-1.
Comparative performance of the traditional propensity score (PS) and high-dimensional propensity score (hdPS) methods in the adjustment for confounding by indication remains unclear. We aimed to identify which method provided the best adjustment for confounding by indication within the context of the risk of diabetes among patients exposed to moderate versus high potency statins.
A cohort of diabetes-free incident statins users was identified from the Quebec's publicly funded medico-administrative database (Full Cohort). We created two matched sub-cohorts by matching one patient initiated on a lower potency to one patient initiated on a high potency either on patients' PS or hdPS. Both methods' performance were compared by means of the absolute standardized differences (ASDD) regarding relevant characteristics and by means of the obtained measures of association.
Eight out of the 18 examined characteristics were shown to be unbalanced within the Full Cohort. Although matching on either method achieved balance within all examined characteristic, matching on patients' hdPS created the most balanced sub-cohort. Measures of associations and confidence intervals obtained within the two matched sub-cohorts overlapped.
Although ASDD suggest better matching with hdPS than with PS, measures of association were almost identical when adjusted for either method. Use of the hdPS method in adjusting for confounding by indication within future studies should be recommended due to its ability to identify confounding variables which may be unknown to the investigators.
传统倾向评分(PS)和高维倾向评分(hdPS)方法在适应证混杂因素调整中的比较性能尚不清楚。我们旨在确定在暴露于中效与高效他汀类药物的患者糖尿病风险背景下,哪种方法能对适应证混杂因素提供最佳调整。
从魁北克公共资助的医疗管理数据库(全队列)中识别出一组无糖尿病的他汀类药物初治患者。我们通过根据患者的PS或hdPS将一名开始使用低效他汀类药物的患者与一名开始使用高效他汀类药物的患者进行匹配,创建了两个匹配的亚队列。通过相关特征的绝对标准化差异(ASDD)以及获得的关联度量来比较两种方法的性能。
在全队列中,18个检查特征中有8个显示存在不平衡。尽管两种方法的匹配在所有检查特征中都实现了平衡,但根据患者的hdPS进行匹配产生了最平衡的亚队列。在两个匹配亚队列中获得的关联度量和置信区间重叠。
尽管ASDD表明hdPS比PS的匹配效果更好,但在对任何一种方法进行调整时,关联度量几乎相同。由于hdPS方法能够识别研究人员可能未知的混杂变量,因此建议在未来研究中使用hdPS方法进行适应证混杂因素的调整。