Stone R A, Obrosky D S, Singer D E, Kapoor W N, Fine M J
Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, PA 15261, USA.
Med Care. 1995 Apr;33(4 Suppl):AS56-66.
A primary goal of the Pneumonia Patient Outcomes Research Team (PORT) multicenter cohort study is to identify a subgroup of patients with community-acquired pneumonia (CAP) who could be safely treated on an ambulatory basis. The medical outcomes of inpatients and outpatients are to be compared. Propensity score adjustment provides a unified way to control for pretreatment differences in the analysis of all the outcomes in this nonrandomized study by defining "comparable" patients as those with the same propensity score (i.e., the same probability of hospitalization). Data for 747 patients (35.5% hospitalized) with CAP in the Pneumonia PORT study illustrate the development and assessment of a propensity score adjustment. A classification tree algorithm defined seven propensity score strata with hospitalization probabilities ranging from 6.5% to 76.5%. Statistically significant pretreatment imbalances favoring the outpatients were found for 29 of 44 baseline variables considered; after stratification on the propensity score, only 13 of the 29 imbalances remained statistically significant at the 0.05 level. Post hoc stratification on the estimated propensity score consistently reduced, but did not completely eliminate, systematic baseline differences between ambulatory and hospitalized patients with CAP. Regression adjustment can be used in conjunction with propensity score stratification to adjust further for the remaining identified imbalances.
肺炎患者预后研究团队(PORT)多中心队列研究的一个主要目标是确定一组社区获得性肺炎(CAP)患者,他们可以在门诊接受安全治疗。将比较住院患者和门诊患者的医疗结局。倾向评分调整通过将“可比”患者定义为具有相同倾向评分(即相同住院概率)的患者,为在这项非随机研究中分析所有结局时控制治疗前差异提供了一种统一方法。肺炎PORT研究中747例CAP患者(35.5%住院)的数据说明了倾向评分调整的开发和评估。一种分类树算法定义了七个倾向评分层,住院概率从6.5%到76.5%不等。在所考虑的44个基线变量中,有29个发现了有利于门诊患者的具有统计学意义的治疗前失衡;在按倾向评分分层后,29个失衡中只有13个在0.05水平上仍具有统计学意义。根据估计的倾向评分进行事后分层持续减少,但并未完全消除CAP门诊患者和住院患者之间的系统性基线差异。回归调整可与倾向评分分层结合使用,以进一步调整剩余的已识别失衡。