- Title
- 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
- Creator
- Siriyotha, Sukanya; Lukkunaprasit, Thitiya; Looareesuwan, Panu; Kunakorntham, Patratorn; Anothaisintawee, Thunyarat; Nimitphong, Hataikarn; McKay, Gareth J.; Attia, John; Thakkinstian, Ammarin
- Relation
- Diabetes, Obesity and Metabolism Vol. 26, Issue 10, p. 4418-4428
- Publisher Link
- http://dx.doi.org/10.1111/dom.15793
- Publisher
- Wiley-Blackwell
- Resource Type
- journal article
- Date
- 2024
- Description
- Aim: To estimate individual treatment effects (ITEs) of sodium-glucose co-transporter-2 inhibitors (SGLT2is) on lowering the risk of developing chronic kidney disease (CKD) in patients with type 2 diabetes (T2D) and to identify those most probable to benefit from treatment. Methods: This study followed a T2D cohort from Ramathibodi Hospital, Thailand, from 2015 to 2022. A counterfactual model was constructed to predict factual and counterfactual risks of CKD if patients did/did not receive SGLT2is. ITEs were estimated by subtracting the factual risk from the counterfactual risk of CKD. Results: There were 1619 and 15 879 patients included in the SGLT2i and non-SGLT2i groups, respectively. The estimated ITEs varied from −1.19% to −17.51% with a median of −4.49%, that is, 50% of patients had a 4.49% or greater lower CKD risk if they received an SGLT2i. Patients who gained the greatest benefit from SGLT2is were more probable to be male, aged at least 60 years, with a history of diabetes duration of at least 3 months, hypertension, peripheral arterial disease, diabetic retinopathy and low high-density lipoprotein cholesterol. Conclusions: 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.
- Subject
- chronic kidney disease; counterfactual prediction model; diabetic kidney disease; sodium-glucose co-transporter-2 inhibitors; type 2 diabetes; SDG 3; SDG 17; Sustainable Development Goal
- Identifier
- http://hdl.handle.net/1959.13/1511771
- Identifier
- uon:56546
- Identifier
- ISSN:1462-8902
- Rights
- © 2024 The Author(s). Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
- Language
- eng
- Full Text
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