Association between the commercial characteristics of psychotropic drugs and their off-label use.

Abstract

Off-label prescribing, or the use of a medicine for non-Food and Drug Administration (FDA)-approved indications, is especially common for psychotropic therapies and often lacks scientific support. We quantified the association between 4 commercial characteristics of prescription medicines-product age, therapeutic class age, drug volume, and promotional expenditures-and off-label use of antidepressants, antipsychotics, and mood stabilizers from 1998 through 2009. We linked data from the IMS Health National Disease and Therapeutic Index, a nationally representative audit of office-based physicians, with data from FDA@gov and the drug compendium DrugDex, to derive information regarding off-label use. Our primary outcome was the rate (per 1000 uses) with which a drug was prescribed for non-FDA-approved indications during a given calendar year. We used mixed-effects regression models with random intercepts for each drug, adding measures of commercial characteristics as fixed effects within this model. From 1998 through 2009, the average proportion of all uses that occurred off-label was 23.3% for antidepressants, 60.7% for antipsychotics, and 54.2% for mood stabilizers. There was a positive association between the annual rate of off-label use and drug volume [incidence rate ratio (IRR), 1.41; 95% confidence intervals (CI), 1.32-1.50], although the strength of this association was not uniform across the therapeutic classes examined. There was also a small but statistically significant association between product age (IRR, 0.96; 95% CI, 0.94-0.98) and class age (IRR, 1.03; 95% CI, 1.01-1.06) and the rate of off-label use, also varying across therapeutic class. There was a statistically significant inverse association between promotional expenditures and off-label use (IRR, 0.94; 95% CI, 0.93-0.96) when controlling for our other commercial characteristics. These associations were similar when examining scientifically unsupported rather than all off-label use. Our findings suggest that drug prescription volume, rather than product age or therapeutic class age, should be scrutinized further to identify settings where the public health impact of unsupported off-label prescribing may be particularly important.