Abstract: TH-PO860
Simulated Impact of SGLT2 Inhibitors on US Dialysis Census
Session Information
- CKD: Epidemiology, Risk Factors, Prevention - I
November 03, 2022 | Location: Exhibit Hall, Orange County Convention Center‚ West Building
Abstract Time: 10:00 AM - 12:00 PM
Category: CKD (Non-Dialysis)
- 2201 CKD (Non-Dialysis): Epidemiology‚ Risk Factors‚ and Prevention
Authors
- Cherif, Alhaji, Renal Research Institute, New York, New York, United States
- Kotanko, Peter, Renal Research Institute, New York, New York, United States
- Muellers, Nina L., Fresenius Medical Care AG & Co KGaA, Bad Homburg, Hessen, Germany
- Cerman, Zdenek, Fresenius Medical Care AG & Co KGaA, Bad Homburg, Hessen, Germany
- Dreismeier, Julian, Fresenius Medical Care AG & Co KGaA, Bad Homburg, Hessen, Germany
- Kossmann, Robert J., Fresenius Medical Care North America, Waltham, Massachusetts, United States
- Maddux, Franklin W., Fresenius Medical Care North America, Waltham, Massachusetts, United States
Background
Diabetes (DM) is common in CKD patients and associated with excess cardiovascular (CV) mortality. Sodium-glucose cotransporter 2 inhibitors (SGLT2i) have beneficial effects on morbidity and mortality of patients with DM, CV, and CKD. This study aims to predict the impact of SGLT2i use on dialysis census.
Methods
The patient population was divided into 5 groups: (1) non-CKD (nCKDi) and (2) CKD patients with indications for SGLT2i use (CKDi); (3) CKD patients without SGLT2i indication (CKDo); (4) incident and (5) prevalent dialysis patients. The model describes the transitions between different groups with the respective influx/efflux rates, e.g., mortality and CKD-to-dialysis progression (Fig.1a). The model was validated using Fresenius Kidney Care data from 1/2018 to 1/2020.
Results
The model predicted dialysis census between 1/2019 and 1/2020 (Fig.1b). Sensitivity analysis identified 4 SGLT2i-related parameters that affect dialysis census: mortality rate of CKD patients and CKD-to-dialysis progression exert a significant effect, while nCKDi mortality rates and progression to CKD have marginal impacts. Figs .1c-d show the forecasted dialysis census over 40 months when CKDi mortality and CKD-to-dialysis progression rates are reduced by 30%. Table 1 shows that a 20% SGLT2i take-on rate among CKDi reduces the dialysis census from 1.280 to 1.269 -fold change at year 5. Within ≤9 years, SGLT2i reduces the dialysis census based on the drug take-on rate. But, this trend is reversed after 10 years, resulting in a rising dialysis census.
Conclusion
SGLT2i use affects dialysis census dynamically. In the first 9 years, the dialysis census is reduced; then followed by an increase. Further research is needed to understand the effect of time-varying SGLT2i take-on rates on dialysis census.