Evaluating the Potential of Prevalent New User Design as an Alternative When New User Design is Impractical.

Purpose: The New User Design can be applied if the target drug has not been administered for a specified period. Therefore, comparisons between drugs administered alone are easier to undertake than comparisons of drugs used in combination. Thus, assessing concomitant medications may be associated with several challenges, including limitations to the New User Design. One such limitation is performing analyses that consider the history of administration of drugs of the same class. In the present study, we considered the limitations of the New User Design and proposed solutions based on the potential of the Prevalent New User Design.

Patients and methods: Using the Japan Medical Data Center database (JMDC), patients diagnosed with diabetes mellitus who received sulfonylureas (SUs) between December 2009 and December 2010 with subsequent addition or switch to dipeptidyl peptidase-4 inhibitors (DPP4Is) were categorized into the SU+DPP4I group. The odds ratio (OR) was estimated using conditional logistic regression analysis. Using the "elapsed time" and "number of prescriptions" axes of the Prevalent New User Design, records from 1,426 and 1,342 individuals, respectively, were analyzed.

Results: The hypoglycemia risk ORs were 1.50 (95% confidence interval [CI] 0.25-9.00) for the "elapsed time" axis and 1.67 (95% CI 0.40-7.00) for the "number of prescriptions" axis. These findings are consistent with the results of a meta-analysis of previous randomized controlled trials.

Conclusion: Our findings suggest that the Prevalent New User Design can be effectively applied for real-world risk assessment scenarios; this design constitutes a potential alternative design to the New User Design. We adopted a Prevalent New User Design considering the patients' treatment history. However, there was a limitation in that we could not obtain information regarding the patients' perceptions of treatment prior to initiating therapy.