Individual treatment effects of sodium‐glucose co‐transporter‐2 inhibitors on the risk of chronic kidney disease in patients with type 2 diabetes: A counterfactual prediction model based on real‐world data
Authors' conclusion
Our prediction model provides individualized information that helps target T2D patients who may benefit more from SGLT2is. This could help clinical decision making and implementation of personalized medicine in clinical practice, especially in resource-limited settings.
Study context
- Population
- Patients with T2D, Ramathibodi Hospital, Thailand, 2015–2022
- Participants
- 1,619 vs 15,879
- Exposure
- SGLT2i vs no SGLT2i
- SGLT2in = 1,619
- non-SGLT2in = 15,879reference
- Outcome
- Individual treatment effects (ITEs) of SGLT2i on CKD risk (counterfactual minus factual risk)
Methodological detailsreal-world data, single-centre
- Real-world data
- Single-centre
Main finding
As reported in the abstract
ITE of SGLT2i on CKD risk
Median ITE
−4.49%
Range of individual treatment effects (ITEs)
−1.19% to −17.51%
Observational data: associations, not effects.
Further findings
Characteristics of patients with greatest benefit
- Greatest benefit more probable in males, age ≥60 years, diabetes duration ≥3 months, hypertension, peripheral arterial disease, DR and low HDL-C
Original publication
Individual treatment effects of sodium‐glucose co‐transporter‐2 inhibitors on the risk of chronic kidney disease in patients with type 2 diabetes: A counterfactual prediction model based on real‐world data. Diabetes Obes Metab. Published 22 July 2024. doi:10.
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