Stukel Thérèse A, Fisher Elliott S, Wennberg David E, Alter David A, Gottlieb Daniel J, Vermeulen Marian J
Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
JAMA. 2007 Jan 17;297(3):278-85. doi: 10.1001/jama.297.3.278.
Comparisons of outcomes between patients treated and untreated in observational studies may be biased due to differences in patient prognosis between groups, often because of unobserved treatment selection biases.
To compare 4 analytic methods for removing the effects of selection bias in observational studies: multivariable model risk adjustment, propensity score risk adjustment, propensity-based matching, and instrumental variable analysis.
DESIGN, SETTING, AND PATIENTS: A national cohort of 122,124 patients who were elderly (aged 65-84 years), receiving Medicare, and hospitalized with acute myocardial infarction (AMI) in 1994-1995, and who were eligible for cardiac catheterization. Baseline chart reviews were taken from the Cooperative Cardiovascular Project and linked to Medicare health administrative data to provide a rich set of prognostic variables. Patients were followed up for 7 years through December 31, 2001, to assess the association between long-term survival and cardiac catheterization within 30 days of hospital admission.
Risk-adjusted relative mortality rate using each of the analytic methods.
Patients who received cardiac catheterization (n = 73 238) were younger and had lower AMI severity than those who did not. After adjustment for prognostic factors by using standard statistical risk-adjustment methods, cardiac catheterization was associated with a 50% relative decrease in mortality (for multivariable model risk adjustment: adjusted relative risk [RR], 0.51; 95% confidence interval [CI], 0.50-0.52; for propensity score risk adjustment: adjusted RR, 0.54; 95% CI, 0.53-0.55; and for propensity-based matching: adjusted RR, 0.54; 95% CI, 0.52-0.56). Using regional catheterization rate as an instrument, instrumental variable analysis showed a 16% relative decrease in mortality (adjusted RR, 0.84; 95% CI, 0.79-0.90). The survival benefits of routine invasive care from randomized clinical trials are between 8% and 21%.
Estimates of the observational association of cardiac catheterization with long-term AMI mortality are highly sensitive to analytic method. All standard risk-adjustment methods have the same limitations regarding removal of unmeasured treatment selection biases. Compared with standard modeling, instrumental variable analysis may produce less biased estimates of treatment effects, but is more suited to answering policy questions than specific clinical questions.
在观察性研究中,接受治疗和未接受治疗的患者之间的结局比较可能会因组间患者预后的差异而产生偏差,这通常是由于未观察到的治疗选择偏差所致。
比较4种用于消除观察性研究中选择偏差影响的分析方法:多变量模型风险调整、倾向评分风险调整、基于倾向的匹配和工具变量分析。
设计、地点和患者:一项全国性队列研究,纳入了1994 - 1995年年龄在65 - 84岁、接受医疗保险且因急性心肌梗死(AMI)住院并符合心脏导管插入术条件的122124例患者。基线病历审查来自合作心血管项目,并与医疗保险健康管理数据相关联,以提供丰富的一组预后变量。对患者进行随访至2001年12月31日,为期7年,以评估住院后30天内长期生存与心脏导管插入术之间的关联。
使用每种分析方法的风险调整相对死亡率。
接受心脏导管插入术的患者(n = 73238)比未接受的患者更年轻,AMI严重程度更低。通过使用标准统计风险调整方法对预后因素进行调整后,心脏导管插入术与死亡率相对降低50%相关(多变量模型风险调整:调整后的相对风险[RR],0.51;95%置信区间[CI],0.50 - 0.52;倾向评分风险调整:调整后的RR,0.54;95% CI,0.53 - 0.55;基于倾向的匹配:调整后的RR,0.54;95% CI,0.52 - 0.56)。使用区域导管插入率作为工具,工具变量分析显示死亡率相对降低16%(调整后的RR,0.84;95% CI,0.79 - 0.90)。随机临床试验中常规侵入性治疗的生存获益在8%至21%之间。
心脏导管插入术与长期AMI死亡率的观察性关联估计对分析方法高度敏感。所有标准风险调整方法在消除未测量的治疗选择偏差方面都有相同的局限性。与标准建模相比,工具变量分析可能会产生偏差较小的治疗效果估计,但更适合回答政策问题而非特定的临床问题。