Anticholinergics for overactive bladder: Temporal trends in prescription and treatment persistence
<p><strong>Introduction:</strong> We sought to understand the contemporary pharmacologic management of overactive bladder (OAB) in a single-payer system. We examined temporal trends in the use of anticholinergic<br />medications and assessed whether the likelihood of patients changing their anticholinergic therapy was predicted by their current therapy.</p><p><strong>Methods:</strong> We conducted a retrospective, population-based analysis of prescription records from the PharmaNet database in BC, Canada. We identified patients treated with one or more anticholinergic<br />prescriptions between 2001 and 2009. We characterized temporal trends in the use of anticholinergic medications. We used generalized estimating equations with a logit wing to assess the relationship between the type of anticholinergic medication and the change in prescription.</p><p><strong>Results:</strong> The 114 325 included patients filled 1 140 296 anticholinergic prescriptions. The number of prescriptions each year increased over the study, both in aggregate and for each individual medication. While oxybutynin was the most commonly prescribed medication (68% of all prescriptions), the proportion of newer anticholinergics (solifenacin, darifenacin, and trospium) prescribed increased over time (p<0.0001). Patients taking tolterodine (odds ratio [OR] 1.03; p=0.01) and darifenacin (OR 1.12; p=0.0006) were significantly more likely to change their prescription than those taking oxybutynin. There was no association seen for patients taking solifenacin (p=0.6) and trospium (p=0.9).</p><p><strong>Conclusions:</strong> There are an increasing number of anticholinergic prescriptions being filled annually. Patients taking newer anticholinergics are at least as likely to change therapy as those taking<br />oxybutynin. The reimbursement environment in BC likely affects these results. Restrictions in the available data limit assessment of other relevant predictors.</p>