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However, individuals with a normal uACR or low-level albuminuria were not represented in kidney outcome trials, leaving uncertainty about absolute treatment benefit in this group. To address this gap and support treatment decisions in clinical practice, we developed and validated a model to predict individual-level kidney protection benefit through the use of SGLT2 inhibitors.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      This observational cohort study used electronic health record data from UK primary care (Clinical Practice Research Datalink, 2013\u20132020) of adults with type 2 diabetes, eGFR \u226560 ml\/min per 1.73 m\n                      <jats:sup>2<\/jats:sup>\n                      and uACR &lt;30 mg\/mmol, without heart failure or atherosclerotic vascular disease, who were starting treatment with either SGLT2 inhibitors or the comparator drugs dipeptidyl peptidase-4 (DPP4) inhibitors\/sulfonylureas. First, we confirmed the real-world applicability of the relative treatment effect from a previous SGLT2 inhibitor trial meta-analysis, using overlap-weighted Cox proportional hazards models. Second, we assessed calibration of the CKD-PC risk score for kidney disease progression (\u226550% eGFR decline, end-stage kidney disease or kidney-related death). Third, we integrated the relative treatment effect with the risk score to predict 3 year individual-level absolute risk reductions for SGLT2 inhibitors, and validated the accuracy of predictions vs overlap-weighted estimates based on observed data. Finally, we compared the clinical utility of a model-based treatment strategy with that of the \u22653 mg\/mmol albuminuria threshold.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      In 53,096 initiations of SGLT2 inhibitor treatment compared with 88,404 initiations of DPP4 inhibitor\/sulfonylurea treatment, there was a 42% lower relative risk of kidney disease progression with SGLT2 inhibitors (HR 0.58; 95% CI 0.48, 0.69), consistent with a previous trial meta-analysis. The CKD-PC risk score did not require recalibration (calibration slope 1.05; 95% CI 0.94, 1.17). The median overall model-predicted absolute risk reduction with SGLT2 inhibitors was 0.37% at 3 years (IQR 0.26\u20130.55), and showed good calibration (calibration slope 1.10; 95% CI 1.09, 1.12). As an illustration of clinical utility, using the model predictions to target the same proportion of the population (\n                      <jats:italic>n<\/jats:italic>\n                      =25,303, 17.9%) as the albuminuria threshold would prevent over 10% more events over 3 years (253 vs 228) by identifying a subgroup of 6.7% of individuals with uACR &lt;3 mg\/mmol who showed significantly greater absolute risk reduction in response to SGLT2 inhibitor treatment than the remainder with uACR &lt;3 mg\/mmol (3.2% vs 1.2% in extended 5 year observational analyses,\n                      <jats:italic>p<\/jats:italic>\n                      =0.05).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions\/interpretation<\/jats:title>\n                    <jats:p>A model adapting the international CKD-PC risk score can accurately predict the individual-level kidney protection benefit from treatment with SGLT2 inhibitors in people with type 2 diabetes and no or early-stage CKD. This could guide treatment decisions in clinical practice worldwide and could target treatment more effectively than the \u22653 mg\/mmol albuminuria threshold recommended by current international guidelines.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Graphical Abstract<\/jats:title>\n                  <\/jats:sec>","DOI":"10.1007\/s00125-025-06577-2","type":"journal-article","created":{"date-parts":[[2025,11,9]],"date-time":"2025-11-09T05:53:33Z","timestamp":1762667613000},"page":"374-385","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Precision medicine in type 2 diabetes: targeting SGLT2 inhibitor treatment for kidney protection"],"prefix":"10.1007","volume":"69","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5686-5033","authenticated-orcid":false,"given":"Thijs T.","family":"Jansz","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2570-3864","authenticated-orcid":false,"given":"Katherine G.","family":"Young","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6054-3582","authenticated-orcid":false,"given":"Rhian","family":"Hopkins","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6833-9399","authenticated-orcid":false,"given":"Andrew P.","family":"McGovern","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3785-327X","authenticated-orcid":false,"given":"Beverley M.","family":"Shields","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5620-473X","authenticated-orcid":false,"given":"Andrew T.","family":"Hattersley","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0883-7599","authenticated-orcid":false,"given":"Angus G.","family":"Jones","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9237-8585","authenticated-orcid":false,"given":"Ewan R.","family":"Pearson","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7961-2262","authenticated-orcid":false,"given":"Coralie","family":"Bingham","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3581-8980","authenticated-orcid":false,"given":"Richard A.","family":"Oram","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7171-732X","authenticated-orcid":false,"given":"John M.","family":"Dennis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"on behalf of the MASTERMIND Consortium","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,11,9]]},"reference":[{"issue":"10365","key":"6577_CR1","doi-asserted-by":"publisher","first-page":"1788","DOI":"10.1016\/S0140-6736(22)02074-8","volume":"400","author":"Nuffield Department of Population Health Renal Studies Group, SGLT2 inhibitor Meta-Analysis Cardio-Renal Trialists' Consortium","year":"2022","unstructured":"Nuffield Department of Population Health Renal Studies Group, SGLT2 inhibitor Meta-Analysis Cardio-Renal Trialists\u2019 Consortium (2022) Impact of diabetes on the effects of sodium glucose co-transporter 2 inhibitors on kidney outcomes: collaborative meta-analysis of large placebo-controlled trials. 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PLoS Med 10(7):e1001491. https:\/\/doi.org\/10.1371\/journal.pmed.1001491","journal-title":"PLoS Med"}],"container-title":["Diabetologia"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00125-025-06577-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00125-025-06577-2","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00125-025-06577-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,7]],"date-time":"2026-01-07T22:01:37Z","timestamp":1767823297000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00125-025-06577-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,9]]},"references-count":32,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,2]]}},"alternative-id":["6577"],"URL":"https:\/\/doi.org\/10.1007\/s00125-025-06577-2","relation":{},"ISSN":["0012-186X","1432-0428"],"issn-type":[{"value":"0012-186X","type":"print"},{"value":"1432-0428","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,9]]},"assertion":[{"value":"13 May 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 November 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"This article is based in part on data from the Clinical Practice Research Datalink (CPRD) Aurum obtained under licence from the UK Medicines and Healthcare Products Regulatory Agency. CPRD data are provided and collected by the UK National Health Service as part of patient care and support. This research was carried out at the National Institute for Health and Care Research (NIHR) Exeter Biomedical Research Centre (BRC). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. A list of MASTERMIND Consortium members is included in the\n                      \n                      .","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Acknowledgements"}},{"value":"All CPRD data are available by application to the CPRD Independent Scientific Advisory Committee (\n                      \n                      ).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Data availability"}},{"value":"All code to develop the CPRD cohort used in this study is available at\n                      \n                      . Code to reproduce the analyses in this article is available at\n                      \n                      .","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Code availability"}},{"value":"This research was supported by the Medical Research Council (UK) (MR\/N00633X\/1) and the European Foundation for the Study of Diabetes. The funders had no role in the study design, data collection, data analysis, data interpretation, writing of the article, or the decision to submit for publication.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Funding"}},{"value":"JMD is supported by a Wellcome Trust Early Career award (227070\/Z\/23\/Z). ATH and BMS are supported by the NIHR Exeter Clinical Research Facility; the views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. AGJ declares research funding to his university from the UK Medical Research Council, NIHR, Diabetes UK, Breakthrough T1D, the Novo Nordisk Foundation and European Foundation for the Study of Diabetes. ERP has received honoraria for speaking from Lilly, Novo Nordisk and Illumina. RAO declares consulting income from Sanofi and honoraria from Sanofi and Novo Nordisk, in addition to research funding from NIDDK, Breakthrough T1D, The Leona M. and Larry B. Helmsley Charitable Trust and Randox Ltd. No industry representatives were involved in the writing of the manuscript or analysis of data. For all authors, these relationships are outside the submitted work; there are no other relationships or activities that might bias, or be perceived to bias, their work.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Authors\u2019 relationships and activities"}},{"value":"The study concept and design were conceived and developed by TTJ, KGY, BMS, ATH, AGJ, RAO and JMD. TTJ, KGY, RH, BMS and JMD had access to all the raw datasets used for the study. TTJ directly accessed the Clinical Practice Research Datalink (CPRD), with support from KGY, RH, BMS and JMD. TTJ, KGY and JMD accessed and verified the underlying data used in the study. TTJ developed the kidney protection benefit model online calculator. All authors had full access to the complete results of the analysis of the CPRD dataset. All authors provided support for the analysis and interpretation of results, critically revised the article, and read and approved the final article. TTJ and JMD attest that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. TTJ is responsible for the integrity of the work as a whole. All authors had final responsibility for the decision to submit for publication.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Contribution statement"}}]}}