{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T02:11:40Z","timestamp":1792721500814,"version":"4.5.0"},"reference-count":39,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2024,7,22]],"date-time":"2024-07-22T00:00:00Z","timestamp":1721606400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004704","name":"National Research Council of Thailand","doi-asserted-by":"publisher","award":["N42A640323"],"award-info":[{"award-number":["N42A640323"]}],"id":[{"id":"10.13039\/501100004704","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dom-pubs.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Diabetes Obesity Metabolism"],"published-print":{"date-parts":[[2024,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aim<\/jats:title>\n                    <jats:p>To estimate individual treatment effects (ITEs) of sodium\u2010glucose co\u2010transporter\u20102 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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>There were 1619 and 15\u2009879 patients included in the SGLT2i and non\u2010SGLT2i groups, respectively. The estimated ITEs varied from \u22121.19% to \u221217.51% with a median of \u22124.49%, 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\u2009years, with a history of diabetes duration of at least 3\u2009months, hypertension, peripheral arterial disease, diabetic retinopathy and low high\u2010density lipoprotein cholesterol.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>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\u2010limited settings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/dom.15793","type":"journal-article","created":{"date-parts":[[2024,7,23]],"date-time":"2024-07-23T00:44:42Z","timestamp":1721695482000},"page":"4418-4428","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Individual treatment effects of sodium\u2010glucose co\u2010transporter\u20102 inhibitors on the risk of chronic kidney disease in patients with type 2 diabetes: A counterfactual prediction model based on real\u2010world data"],"prefix":"10.1111","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7402-8776","authenticated-orcid":false,"given":"Sukanya","family":"Siriyotha","sequence":"first","affiliation":[{"name":"Department of Clinical Epidemiology and Biostatistics Faculty of Medicine 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