Evaluating the role of confounding in pharmacoeconomic studies.
Confounding may be present in nonrandomized etiological research involving human populations. It can result in erroneous conclusions about the effect of exposure on a disease outcome or about any form of causality between predictors and outcomes. Confounding can wholly or partially account for the apparent effect of the risk factor under consideration or mask the underlying, true association. Not controlling for the effects of confounding can lead to biased results, thus compromising the validity of study conclusions. The three goals of this article are: (1) to define a confounder or a confounding variable, (2) to discuss strategies for controlling the effects of confounding, and (3) to illustrate the perverse effects of confounding with the help of an example.
Joish
Vijay N
VN
Pharmacotherapy, Outcomes Research Center, Salt Lake City, USA. vijay.joish@pharm.utah.edu
Sahai
Ashok
A
D000328:Adult; D000700:Analgesics / Q000627:therapeutic use; D015986:Confounding Factors, Epidemiologic; D004341:Drug Evaluation / Q000379:methods* / Q000706:statistics & numerical data; D017850:Economics, Pharmaceutical; D004636:Emergency Service, Hospital / Q000706:statistics & numerical data; D006302:Health Services Research / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D016555:Matched-Pair Analysis; D008881:Migraine Disorders / Q000188:drug therapy; D015999:Multivariate Analysis; D015203:Reproducibility of Results; D012107:Research Design; D020379:Risk Adjustment
D000700:Analgesics