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The American Journal of Managed Care May 2019
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Cost-Effectiveness of DPP-4 Inhibitor and SGLT2 Inhibitor Combination Therapy for Type 2 Diabetes
Manjiri Pawaskar, PhD; S. Pinar Bilir, MS; Stacey Kowal, MS; Claudio Gonzalez, MD; Swapnil Rajpathak, MD; and Glenn Davies, DrPH
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Cost-Effectiveness of DPP-4 Inhibitor and SGLT2 Inhibitor Combination Therapy for Type 2 Diabetes

Manjiri Pawaskar, PhD; S. Pinar Bilir, MS; Stacey Kowal, MS; Claudio Gonzalez, MD; Swapnil Rajpathak, MD; and Glenn Davies, DrPH
This study evaluates the long-term cost-effectiveness of treatment involving combination therapy with dipeptidyl peptidase 4 (DPP-4) inhibitors and sodium-glucose cotransporter 2 (SGLT2) inhibitors compared with an alternative with sulfonyureas prior to insulin initiation on a background of metformin.

IQVIA CORE Diabetes Model Summary Description

This study utilized the IQVIA CORE Diabetes Model (CDM) v9.0, a well-validated model that has been published previously in detail.24-26 This simulation model, which is programmed in C++, cycles a cohort of patients annually through a series of diabetes complication–related Markov modules over a lifetime. Treatment efficacy and safety data are used to project the impact of different therapeutic choices on major micro- and macrovascular diabetes complications, survival, quality of life, and medical costs. Efficacy benefits (eg, A1C decline) occur in the initial year of treatment, whereas safety effects (eg, hypoglycemic event rates) are applied throughout the years of therapy in the model. In addition to intervention-specific inputs, the model tracks patient profiles (eg, current blood glucose, blood pressure, weight) and comorbidity status (eg, history of CVD, renal disease) to adjust risk of diabetes-related events. Key risk equations are derived from large cohort studies. A1C progression and A1C-dependent adjustments in T2D analyses reflect the United Kingdom Prospective Diabetes Study risk engine.3,27-29 Early A1C levels indirectly affect downstream events, as the initial value affects downstream A1C. Other physiological parameters projections reflect findings from the Framingham Heart Study.30

Model outputs include differences in life expectancy, quality-adjusted life-years (QALYs), costs, cumulative incidences of complication events due to intervention effects on diabetes-related adverse events, and A1C levels and other physiological parameters that affect risks of major diabetes complications. Incremental costs and QALYs are then used to estimate an incremental cost-effectiveness ratio (ICER) in terms of dollar amount per QALY.

Although there is no official threshold that specifies what makes an intervention a good value in the United States, a 2008 study summarizing the cost-effectiveness of interventions that have been approved and reimbursed found that the implicit US threshold ranges from $109,000 to $294,000 per QALY.31 Historical cited values, such as $50,000 and $100,000 per QALY, are currently thought to be low given available evidence about true reimbursement and societal preferences.32

Analyses were run with 1000 patients for 1000 iterations each over a lifetime time horizon of 40 years from a US payer perspective, using a discount rate of 3% for costs and outcomes as recommended for cost-effectiveness analyses in the United States.33

Model Inputs

The model cohort was designed to represent patients not at A1C goal on metformin and who have intensified to dual therapy; thus, they are the appropriate target population for this type of therapy intensification in the United States. Patient characteristics were derived from the GE Centricity electronic medical record database, with supplemental data provided to align with clinical trial data (key inputs shown in Table 134-39; the eAppendix [available at] shows the full set of cohort inputs). The mean baseline age for this group is 57.9 years, with 3 years duration of diabetes and a baseline A1C level of 8.37%.

Intervention effects. Full pathways under consideration are depicted in Figure 1. In pathway 1, intensification following failure with metformin monotherapy includes DPP-4 inhibitors followed by the addition of SGLT2 inhibitors prior to insulin; whereas pathway 2, which is more generic, follows intensification with SU followed by the addition of insulin(s). Clinical inputs for each therapeutic step in each pathway were obtained from randomized clinical trials or large meta-analyses (Table 240-43). Treatments were assumed to have no impact on any clinical parameters not specified in Table 2,40-43 reflecting an interpretation that values not reported are not significantly different. Patients moved from one therapeutic line to the next when their A1C level exceeded 7.5%, as an indication of failing to meet their A1C goal. However, as this threshold is considered aggressive for some patients (eg, older patients, for whom consequences of hypoglycemic events may be more severe), this value was tested in scenario analysis (described in the Analyses section).

Regimen details. With the exception of insulin, treatment dosing reflects official prescribing information. For basal insulin, the dose reflects consumption as quantified in the metformin + sitagliptin + insulin glargine arm of the recently completed PN845 study (Merck, unpublished data [PN845 trial], 2018),23 although costs are assumed to reflect a weighted average of available forms including glargine, detemir, and degludec (Merck, unpublished data, 2018). Bolus insulin (insulin aspart) dosing reflects published daily average consumption of 0.2 units per kg weight (average weight, 84.9 kg).34

Estimates of additional resource use, such as test strips for self-monitoring of blood glucose, lancets, and needles for insulin, were based on literature or assumptions about typical usage (2.7 test strips daily,44 daily replacement of lancets, and 2 needles per day with bolus insulin; note that basal insulin is provided in an injection pen or other prefilled syringe format).

Unit costs. Key cost inputs for the analyses are shown in Table 1.34-39 Costs are reported in 2017 US$ and reflect published values from MediSpan PriceRx for drugs35 or a combination of literature and Medicare fee schedules45 for complications and events. The full list of cost inputs and references is housed in the eAppendix.

Quality of life. Quality of life is captured via adjusting total life-years with utilities and disutilities associated with health status and health events. Utility and disutility input values reflect IQVIA CDM defaults for a T2D population (Table 134-39).36-39

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