Study objective: To develop a prioritized list of individual drugs for which future research regarding off-label uses is warranted.
Design: Retrospective, cross-sectional study.
Data sources: Commercial database that provides ongoing estimates of drug prescribing practices of office-based physicians in the United States and an Internet database of comprehensive evidence-based drug information.
Measurements and main results: The base analyses incorporated three key factors based on the theory of value of information: volume of off-label use with inadequate evidence, drug safety, and cost and market considerations. Nationally representative prescribing data were used to estimate the number of off-label drug uses by indication from January 1, 2005-June 30, 2007, in the United States, and these indications were then categorized according to the adequacy of scientific support. Black-box warnings and safety alerts, drug cost, date of market entry, and marketing expenditures were also incorporated into the final model to produce a priority score. Sensitivity analyses were conducted by varying key model parameters. Our findings identified a high volume of off-label prescribing in the absence of good evidence for a substantial number of drugs, particularly antidepressants, antipsychotics, and anxiolytic-sedatives. Drugs that consistently ranked high in both our base model and sensitivity analyses were quetiapine, warfarin, escitalopram, risperidone, montelukast, bupropion, sertraline, venlafaxine, celecoxib, lisinopril, duloxetine, trazodone, olanzapine, and epoetin alfa.
Conclusion: Future research into off-label drug use should focus on drugs used frequently with inadequate supporting evidence, particularly if further concerns are raised by known safety issues, high drug cost, recent market entry, and extensive marketing. Our quantitative analysis identified particular concerns with the off-label use of antipsychotic and antidepressant drugs. Targeted research and policy activities on our list of prioritized drugs have high potential value.