| Literature DB >> 35845354 |
Sarah Glover1, Matthew E Borrego1, Gretchen M Ray1, Melissa H Roberts1.
Abstract
Background: Type 2 diabetes (T2D) patients face increased risk of heart failure (HF) as they age. Sodium-glucose cotransporter 2 inhibitors (SGLT-2i) have demonstrated effectiveness in reducing HF hospitalizations in patients with T2D and HF with reduced ejection fraction (HFrEF). Diabetes guidelines recommend SGLT-2i therapy for patients with HFrEF; however, SGLT-2i cost is high. Objective: Study objectives were to assess SGLT-2i utilization and HF hospitalization rates in commercially insured adults (age <65) with T2D and heart failure with reduced ejection fraction (HFrEF) taking metformin with/without SGLT-2i use and conduct a cost-benefit analysis of SGLT-2i use from payer and societal perspectives.Entities:
Keywords: cardiovascular disease; cost benefit; economic impact; heart failure; net benefit; type 2 diabetes
Year: 2022 PMID: 35845354 PMCID: PMC9278724 DOI: 10.2147/CEOR.S361886
Source DB: PubMed Journal: Clinicoecon Outcomes Res ISSN: 1178-6981
Event Estimates by Age Group
| Event | Estimate | Source |
|---|---|---|
| Any Primary HF Age 30–64 | 15.5% | [ |
| Any Primary HF Age 30–44 | 16.4% | [ |
| Any Primary HF Age 45–54 | 17.3% | [ |
| Any Primary HF Age 54–64 | 14.7% | [ |
| Any Primary HF Age 30–64 | 11.0% (0.70) | [ |
| Any Primary HF Age 30–44 | 13.0% (0.79) | [ |
| Any Primary HF Age 45–54 | 8.8% (0.51) | [ |
| Any Primary HF Age 54–64 | 11.8% (0.80) | [ |
| Age 30–64 | 21.0% | [ |
| CANVAS | 0.51 | [ |
| DECLARE-TIMI | 0.64 | [ |
| EMPA-REG | 0.65 | [ |
| CANVAS | 0.72 | [ |
| DECLARE-TIMI | 0.55 | [ |
| EMPA-REG | 0.62 | [ |
| Age 30–44 | 3.5% | [ |
| Age 45–64 | 7.8% | [ |
| Age 30–44 | 74.1% | [ |
| Age 45–64 | 66.9% | [ |
| Age 30–44 w/Home Healthcare | 11.2% | [ |
| Age 45–64 w/Home Healthcare | 14.7% | [ |
| Inpatient | 3.6% | [ |
| One-year post-discharge | 22% | [ |
| Mean LOS HF Hosp (days) | 5.36 | [ |
| Mean LOS NF (days) | 180 | [ |
| Mean LOS Home (days) | 90 | [ |
| UTI Average | 5.05% | [ |
| GMI Average | 6.31% | [ |
| DKA Average | 0.25% | [ |
Abbreviations: CV, cardiovascular; DKA, diabetic keto acidosis; GMI, genital mycotic infection; HF, heart failure; HR, hazard ratio; LOS, length-of-stay; NF, nursing facility SGLT-2i, sodium glucose cotransporter-2 inhibitor; T2D, type 2 diabetes; UTI, urinary tract infection.
Inventory of Cost Estimates
| Estimate | Source | |
|---|---|---|
| Age 18–44 | $22,411.88 | [ |
| Age 45–64 | $17,500.94 | [ |
| Canagliflozin | $5450.47 | [ |
| Dapagliflozin | $5329.58 | [ |
| Empagliflozin | $5765.83 | [ |
| Average Cost | $5515.30 | |
| UTI Standard Treatment | $ 1.10 | [ |
| UTI Hospitalization | $11,132.37 | [ |
| GMI Standard Treatment | $4.15 | [ |
| GMI Hospitalization | $9459.77 | [ |
| DKA Hospitalization | $8262.97 | [ |
| SNF | $47,556.47 | [ |
| Home Healthcare | $3446.76 | [ |
| Age 35–44 | $309.26 | [ |
| Age 45–54 | $264.92 | [ |
| Age 55–64 | $210.51 | [ |
| Deceased Age 35–44 | $1,254,143.42 | [ |
| Deceased Age 45–54 | $845,044.94 | [ |
| Deceased Age 55–64 | $376,562.35 | [ |
Abbreviations: DKA, diabetic keto acidosis; GMI, genital mycotic infection; HF, heart failure; SGLT-2i, sodium glucose cotransporter-2 inhibitor; UTI, urinary tract infection; SNF, skilled nursing facility.
Figure 1Base case direct net-benefit results by age category. Net-benefit for base case scenario from health care payer perspective. Real-world (RW) and trial model results are reported for ages 30–64. Real-World – solid black, CANVAS – vertical stripe, DELCARE-TIMI – horizontal strip, EMPA-REG – diagonal stripe.
Figure 2Base case societal net-benefit results by age category. Net-benefit for base case scenario from societal perspective. Real-world (RW) and trial model results are reported for respective age categories and for ages 30–64 combined. Real-World – Grey, CANVAS – purple, DELCARE-TIMI – pink, EMPA-REG – light blue.
Figure 3MarketScan ages 30–64 societal net-benefit (per person). Results of the one-way sensitivity analysis for CBA societal perspective model using real-world data.