Economic simulation of canagliflozin and sitagliptin treatment outcomes in patients with type 2 diabetes mellitus with inadequate glycemic control

Abstract Objectives: This study examines the association between changes in diabetes-related quality measures (QMs) (HbA1c, systolic and diastolic blood pressure [BP], low-density lipoprotein cholesterol [LDL-C], and body weight) and healthcare costs in Type 2 diabetes mellitus (T2DM) patients. It also performs an economic simulation that evaluates the cost implications of the changes in QMs and of the incidence rates (IRs) of adverse events (AEs) associated with canagliflozin (CANA) and sitagliptin (SITA) treatments in a real-world setting. Methods: Health-insurance claims and electronic medical records from the Reliant Medical Group database (2007-2011) were used to identify adult patients with T2DM receiving metformin and sulfonylurea who did not achieve adequate glycemic control. The association between the changes in QMs and healthcare costs was evaluated using multivariate regression and non-parametric bootstrap methods. AE-related costs were taken from the literature. The cost impact of CANA and SITA outcomes was evaluated using the aforementioned costs and the changes in QMs and the IRs of AEs observed in a recent phase 3 trial comparing CANA and SITA as third oral agent (DIA3015). Results: Eight hundred and fifty-six T2DM patients were identified (mean age = 65.8; female 45.4%). The regression analysis found that increases of 1 percentage point in HbA1C and 1% in systolic and diastolic BP, LDL-C, or weight were associated with a per patient per year (PPPY) cost increase of $4476 (p = 0.028) and $566 (p = 0.006), a decrease of $362 (p = 0.070) and $7 (p = 0.817), and an increase of $241 (p = 0.481), respectively. The economic simulation showed that changes in QMs and IRs of AEs equivalent to those reported in DIA3015 would be associated with a reduction in PPPY healthcare costs of $6061 (p = 0.036) for CANA and $2190 (p = 0.098) for SITA. Conclusions: This study suggests that integrated approaches that manage to control a combination of quality measures are most successful at reducing downstream healthcare costs.