No conflict of interest is found in this paper.
Confounder summary scores when comparing the effects of multiple drug exposures†
Article first published online: 15 SEP 2009
Copyright © 2009 John Wiley & Sons, Ltd.
Pharmacoepidemiology and Drug Safety
Volume 19, Issue 1, pages 2–9, January 2010
How to Cite
Cadarette, S. M., Gagne, J. J., Solomon, D. H., Katz, J. N. and Stürmer, T. (2010), Confounder summary scores when comparing the effects of multiple drug exposures. Pharmacoepidem. Drug Safe., 19: 2–9. doi: 10.1002/pds.1845
- Issue published online: 24 DEC 2009
- Article first published online: 15 SEP 2009
- Manuscript Accepted: 6 AUG 2009
- Manuscript Revised: 3 AUG 2009
- Manuscript Received: 6 FEB 2009
- drug evaluation;
- epidemiological methods;
- population studies
Little information is available comparing methods to adjust for confounding when considering multiple drug exposures. We compared three analytic strategies to control for confounding based on measured variables: conventional multivariable, exposure propensity score (EPS), and disease risk score (DRS).
Each method was applied to a dataset (2000–2006) recently used to examine the comparative effectiveness of four drugs. The relative effectiveness of risedronate, nasal calcitonin, and raloxifene in preventing non-vertebral fracture, were each compared to alendronate. EPSs were derived both by using multinomial logistic regression (single model EPS) and by three separate logistic regression models (separate model EPS). DRSs were derived and event rates compared using Cox proportional hazard models. DRSs derived among the entire cohort (full cohort DRS) was compared to DRSs derived only among the referent alendronate (unexposed cohort DRS).
Less than 8% deviation from the base estimate (conventional multivariable) was observed applying single model EPS, separate model EPS or full cohort DRS. Applying the unexposed cohort DRS when background risk for fracture differed between comparison drug exposure cohorts resulted in −7 to + 13% deviation from our base estimate.
With sufficient numbers of exposed and outcomes, either conventional multivariable, EPS or full cohort DRS may be used to adjust for confounding to compare the effects of multiple drug exposures. However, our data also suggest that unexposed cohort DRS may be problematic when background risks differ between referent and exposed groups. Further empirical and simulation studies will help to clarify the generalizability of our findings. Copyright © 2009 John Wiley & Sons, Ltd.