Journal
PHARMACOEPIDEMIOLOGY AND DRUG SAFETY
Volume 32, Issue 6, Pages 599-606Publisher
WILEY
DOI: 10.1002/pds.5623
Keywords
comparative effectiveness; comparative safety; healthcare databases; negative control; pharmacoepidemiology; residual confounding
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This narrative review discusses the application of negative control outcome (NCO) methods in non-randomized comparisons of drug effectiveness and safety. Two completed NCO studies are used to illustrate the use and results of these methods, and recommendations for future research are provided.
PurposeThis narrative review describes the application of negative control outcome (NCO) methods to assess potential bias due to unmeasured or mismeasured confounders in non-randomized comparisons of drug effectiveness and safety. An NCO is assumed to have no causal relationship with a treatment under study while subject to the same confounding structure as the treatment and outcome of interest; an association between treatment and NCO then reflects the potential for uncontrolled confounding between treatment and outcome. MethodsWe focus on two recently completed NCO studies that assessed the comparability of outcome risk for patients initiating different osteoporosis medications and lipid-lowering therapies, illustrating several ways in which confounding may result. In these studies, NCO methods were implemented in claims-based data sources, with the results used to guide the decision to proceed with comparative effectiveness or safety analyses. ResultsBased on this research, we provide recommendations for future NCO studies, including considerations for the identification of confounding mechanisms in the target patient population, the selection of NCOs expected to satisfy required assumptions, the interpretation of NCO effect estimates, and the mitigation of uncontrolled confounding detected in NCO analyses. We propose the use of NCO studies prior to initiating comparative effectiveness or safety research, providing information on the potential presence of uncontrolled confounding in those comparative analyses. ConclusionsGiven the increasing use of non-randomized designs for regulatory decision-making, the application of NCO methods will strengthen study design, analysis, and interpretation of real-world data and the credibility of the resulting real-world evidence.
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