Abstract
INTRODUCTION: It is important to capture the patient experience with a diabetes treatment in clinical trials; however, use of instruments to assess patient-reported outcomes (PROs) in diabetes trials is inconsistent and results may not be reported alongside primary efficacy data. In lieu of head-to-head data, indirect comparisons can be used to compare competing interventions. In this study, we used indirect comparison methods to assess differences in PRO score changes between canagliflozin and other antihyperglycemic agents as add-on to metformin. METHODS: Literature searches were performed to identify studies that reported the same PRO instruments that were collected across four trials of canagliflozin in dual or triple therapy. Extensive searches identified only one study that was sufficiently similar in design and reported common PRO results using the Impact of Weight on Quality of Life-Lite (IWQoL-Lite): the DURATION-2 study of exenatide once-weekly (QW) versus sitagliptin and pioglitazone. This study was compared with the CANTATA-D study of canagliflozin versus sitagliptin. Bayesian indirect comparisons were performed to assess mean change in IWQoL-Lite total score. A fixed-effects model with noninformative priors was used to estimate between-treatment differences. Sensitivity analyses examined differences in trial populations. RESULTS: In the primary analysis, the probability that canagliflozin treatment results in greater improvement in IWQoL-Lite total score versus exenatide, sitagliptin, and pioglitazone was 60.0%, 89.9%, and 99.5%, respectively. When the CANTATA-D population was restricted using DURATION-2 inclusion/exclusion criteria, canagliflozin was also associated with a higher probability of having greater improvement in IWQoL-Lite than exenatide, sitagliptin, and pioglitazone. CONCLUSIONS: These findings suggest that improvements in the impact of weight on health-related quality of life may be greater with canagliflozin than exenatide, sitagliptin, and pioglitazone. This analysis also demonstrates the application of indirect comparison methodology to PRO data and provides examples of advantages and challenges associated with performing indirect comparisons of PRO data.