Am J Epidemiol. 2014 Mar 1;179(5):648-59. doi: 10.1093/aje/kwt323. Epub 2014 Jan 23.
We compared the impact of 3 confounding adjustment procedures-covariate-adjusted regression, propensity score regression, and high-dimensional propensity score regression-to assess the effects of selected asthma controller medication use (leukotriene antagonists and inhaled corticosteroids) on the following 4 asthma-related adverse outcomes: emergency department visits, hospitalizations, oral corticosteroid use, and the composite outcome of these. We examined a cohort of 24,680 new users who were 4-17 years of age at the incident dispensing from the Population-Based Effectiveness in Asthma and Lung Diseases (PEAL) Network of 5 commercial health plans and TennCare, the Tennessee Medicaid program, during the period January 1, 2004, to December 31, 2010. The 3 methods yielded similar results, indicating that pediatric patients treated with leukotriene antagonists were no more likely than those treated with inhaled corticosteroids to experience adverse outcomes. Children in the TennCare population who had a diagnosis of allergic rhinitis and who then initiated the use of leukotriene antagonists were less likely to experience an asthma-related emergency department visit. A plausible explanation is that our data set is large enough that the 2 advanced propensity score-based analyses do not have advantages over the traditional covariate-adjusted regression approach. We provide important observations on how to correctly apply the methods in observational data analysis and suggest statistical research areas that need more work to guide implementation.
我们比较了 3 种混杂调整程序(协变量调整回归、倾向评分回归和高维倾向评分回归)的影响,以评估选定的哮喘控制药物使用(白三烯拮抗剂和吸入皮质类固醇)对以下 4 种哮喘相关不良结局的影响:急诊就诊、住院、口服皮质类固醇使用以及这些结局的综合结果。我们研究了一个队列,该队列由来自 5 个商业健康计划和 TennCare(田纳西州医疗补助计划)的人口为基础的哮喘和肺部疾病有效性网络(PEAL)中的 24680 名新使用者组成,他们在 2004 年 1 月至 2010 年 12 月 31 日期间从处方的第一个事件开始使用,年龄为 4-17 岁。这 3 种方法得出了相似的结果,表明接受白三烯拮抗剂治疗的儿科患者与接受吸入皮质类固醇治疗的患者相比,发生不良结局的可能性没有更高。在 TennCare 人群中,患有过敏性鼻炎并开始使用白三烯拮抗剂的儿童经历与哮喘相关的急诊就诊的可能性较低。一个合理的解释是,我们的数据集足够大,因此这两种先进的倾向评分基础分析在观察性数据分析中并没有比传统的协变量调整回归方法更有优势。我们提供了关于如何正确应用观察数据分析方法的重要观察结果,并提出了需要更多工作来指导实施的统计研究领域。