» Articles » PMID: 17227979

Analysis of Observational Studies in the Presence of Treatment Selection Bias: Effects of Invasive Cardiac Management on AMI Survival Using Propensity Score and Instrumental Variable Methods

Overview
Journal JAMA
Specialty General Medicine
Date 2007 Jan 18
PMID 17227979
Citations 266
Authors
Affiliations
Soon will be listed here.
Abstract

Context: 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.

Objective: 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.

Main Outcome Measure: Risk-adjusted relative mortality rate using each of the analytic methods.

Results: 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%.

Conclusions: 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.

Citing Articles

Coronary plaque characteristics quantified by artificial intelligence-enabled plaque analysis: Insights from a multi-ethnic asymptomatic US population.

Tomasino G, Park C, Grodecki K, Geers J, Han D, Lin A Am J Prev Cardiol. 2025; 21:100929.

PMID: 39896053 PMC: 11786063. DOI: 10.1016/j.ajpc.2025.100929.


Causal Relationship Between Physical Activity and Body Weight: A Maximum Likelihood Treatment Effect Model Approach Using Australian Longitudinal Data.

Doan T, Leach L, Doan N, Strazdins L Int J Behav Med. 2024; .

PMID: 39567469 DOI: 10.1007/s12529-024-10336-9.


Impact of being taken into out-of-home care: a longitudinal cohort study of First Nations and other child welfare agencies in Manitoba, Canada.

Brownell M, Nickel N, Frank K, Flaten L, Sinclair S, Sinclair S Lancet Reg Health Am. 2024; 38:100886.

PMID: 39309258 PMC: 11415857. DOI: 10.1016/j.lana.2024.100886.


The evolution of selection bias in the recent epidemiologic literature-a selective overview.

Lu H, Howe C, Zivich P, Gonsalves G, Westreich D Am J Epidemiol. 2024; 194(3):580-584.

PMID: 39136207 PMC: 11879605. DOI: 10.1093/aje/kwae282.


Genetically predicted high sex hormone binding globulin was associated with decreased risk of polycystic ovary syndrome.

Guo X, Chen L, He J, Zhang X, Xu S BMC Womens Health. 2024; 24(1):357.

PMID: 38902677 PMC: 11188236. DOI: 10.1186/s12905-024-03144-6.


References
1.
Austin P, Mamdani M, Stukel T, Anderson G, Tu J . The use of the propensity score for estimating treatment effects: administrative versus clinical data. Stat Med. 2005; 24(10):1563-78. DOI: 10.1002/sim.2053. View

2.
Shah B, Laupacis A, Hux J, Austin P . Propensity score methods gave similar results to traditional regression modeling in observational studies: a systematic review. J Clin Epidemiol. 2005; 58(6):550-9. DOI: 10.1016/j.jclinepi.2004.10.016. View

3.
Stukel T, Lucas F, Wennberg D . Long-term outcomes of regional variations in intensity of invasive vs medical management of Medicare Patients with acute myocardial infarction. JAMA. 2005; 293(11):1329-37. PMC: 1459288. DOI: 10.1001/jama.293.11.1329. View

4.
Antman E, Brooks N, Califf R, Hillis L, Hiratzka L, Rapaport E . 1999 update: ACC/AHA guidelines for the management of patients with acute myocardial infarction. A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Committee on Management of Acute Myocardial.... J Am Coll Cardiol. 1999; 34(3):890-911. DOI: 10.1016/s0735-1097(99)00351-4. View

5.
Harris K, Remler D . Who is the marginal patient? Understanding instrumental variables estimates of treatment effects. Health Serv Res. 1998; 33(5 Pt 1):1337-60. PMC: 1070319. View