Increasing levels of restriction in pharmacoepidemiologic database studies of elderly and comparison with randomized trial results.
BACKGROUND
The goal of restricting study populations is to make patients more homogeneous regarding potential confounding factors and treatment effects and thereby achieve less biased effect estimates.


OBJECTIVE
This article describes increasing levels of restrictions for use in pharmacoepidemiology and examines to what extent they change rate ratio estimates and reduce bias in a study of statin treatment and 1-year mortality.


METHODS
: The study cohort was drawn from a population of seniors age 65 years and older enrolled in both Medicare and the Pennsylvania Pharmaceutical Assistance Contract for the Elderly (PACE) between 1995 and 2002. We identified all users of statins during the study period and assessed the time until death within 1 year. The following progressive restrictions were applied: (1) study incident drug users only, (2) choose a comparison group most similar to the intervention group, (3) exclude patients with contraindications, (4) exclude patients with low adherence, and (5) restrict to specific high-risk/low-risk subgroups represented in randomized trails (RCTs).


RESULTS
The basic cohort comprised 122,406 statin users, who were on average 78 years old and predominantly white (93%) and showed an unadjusted rate ratio of 0.32 for statin users. When all 5 restrictions were applied (N = 11,673), the unadjusted rate ratio had increased to 0.72. Multivariable Cox regression adjusted rate ratios increased from 0.62 [95% confidence interval (CI), 0.58-0.66] to 0.79 (95% CI, 0.60-1.03). However, after the first 3 restrictions the effect size changed little. The final estimate is similar to that obtained as a pooled estimate of 3 pravastatin RCTs in patients age 65 years and older. We argue that restrictions 1 through 4 compromised generalizability little.


CONCLUSIONS
In our example of a large database study, restricting to incident drug users, similar comparison groups, patients without contraindication, and to adherent patients was a practical strategy, which limited the effect of confounding, as these approaches yield results closer to those seen in RCTs.
Schneeweiss
Sebastian
S
Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA. schneeweiss@post.harvard.edu
Patrick
Amanda R
AR
Stürmer
Til
T
Brookhart
M Alan
MA
Avorn
Jerry
J
Maclure
Malcolm
M
Rothman
Kenneth J
KJ
Glynn
Robert J
RJ
D000368:Aged; D000369:Aged, 80 and over; D015986:Confounding Factors, Epidemiologic; D035061:Control Groups; D005260:Female; D006801:Humans; D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors / Q000627:therapeutic use; D008297:Male; D016555:Matched-Pair Analysis; D009026:Mortality; D015999:Multivariate Analysis; D010349:Patient Compliance; D018579:Patient Selection; D010414:Pennsylvania / Q000453:epidemiology; D017891:Pharmacoepidemiology / Q000706:statistics & numerical data*; D016016:Proportional Hazards Models; D016032:Randomized Controlled Trials as Topic; D015203:Reproducibility of Results; D012107:Research Design; D012189:Retrospective Studies; D020379:Risk Adjustment; D014481:United States / Q000453:epidemiology
D019161:Hydroxymethylglutaryl-CoA Reductase Inhibitors