{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T18:09:21Z","timestamp":1788804561795,"version":"build-2803163510"},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T00:00:00Z","timestamp":1782259200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T00:00:00Z","timestamp":1788739200000},"content-version":"vor","delay-in-days":75,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cost Eff Resour Alloc"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Diabetic kidney disease (DKD) accounts for 44% of new chronic kidney disease cases and is associated with significant morbidity and mortality. Although sodium-glucose co-transporter-2 inhibitors (SGLT2is) can reduce cardiorenal outcomes, current DKD staging relying on eGFR and albuminuria (KDIGO risk categories) leaves SGLT2is underutilized in clinical practice. A new biomarker-enriched, AI-enabled risk score (KidneyIntelX\u2122; Renalytix, Inc.) was developed to predict a progressive decline in kidney function in patients with early-stage DKD. KidneyIntelX categorizes patients as low, intermediate, or high risk for disease progression, which can guide resource utilization, prescribing of drugs such as SGLT2is, and improvements in efficiency of care. We report a cost-effectiveness analysis comparing DKD patient stratification with KidneyIntelX to KDIGO by generating an incremental cost effectiveness ratio (ICER).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>The model adopted a U.S. Medicare perspective and consisted of patients with DKD in stages G1-3b using KidneyIntelX or KDIGO. A 10-state Markov state transition structure was employed over a lifetime horizon which includes DKD stages 1\u20135, dialysis, kidney transplant, cardiovascular (CV) death, and non-CV death. Transition probabilities and risk group distributions for KidneyIntelX and KDIGO were sourced from a KidneyIntelX validation study. Evaluation resulting from KidneyIntelX or KDIGO informed SGLT2i use in the model. Cost inputs included testing, medications, and office visit costs, as well as annual costs for each DKD stage, dialysis, and kidney transplant. Quality of life for each disease state was captured as utility values informed by literature.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The modeled use of SGLT2i directed by KidneyIntelX led to a reduction in kidney disease progression (ESKD) and CV events, as well as dialysis starts, dialysis crashes, and kidney transplants compared to KDIGO-guided treatment. KidneyIntelX patients also spent less time in DKD stages 4 and 5 and more time in 1 through 3b. KidneyIntelX led to cost savings of about $514 per patient and quality-adjusted life year (QALY) gains of 0.028, resulting in a negative ICER. Combining SGLT2i with MRA\u2019s further increased per patient cost savings to $530 for Medicare participants.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Wide deployment of KidneyIntelX in Medicare patients with DKD G1-3b is expected to be cost-effective compared to KDIGO from the Medicare perspective, with a negative, dominant ICER.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12962-026-00775-4","type":"journal-article","created":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T01:25:18Z","timestamp":1782264318000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Cost-effectiveness analysis of a prognostic risk assessment for early-stage 1-3b diabetic kidney disease patients in the United States"],"prefix":"10.1186","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8456-7589","authenticated-orcid":false,"given":"Jacie T.","family":"Cooper","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1878-8118","authenticated-orcid":false,"given":"John E.","family":"Schneider","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4014-8073","authenticated-orcid":false,"given":"Thomas","family":"Mclain","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0928-9168","authenticated-orcid":false,"given":"Steven","family":"Coca","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0102-8684","authenticated-orcid":false,"given":"Michael J.","family":"Donovan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,6,24]]},"reference":[{"issue":"6","key":"775_CR1","doi-asserted-by":"publisher","first-page":"2089","DOI":"10.1111\/j.1523-1755.2005.00365.x","volume":"67","author":"AS Levey","year":"2005","unstructured":"Levey AS, Eckardt KU, Tsukamoto Y, Levin A, Coresh J, Rossert J, et al. Definition and classification of chronic kidney disease: a position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int. 2005;67(6):2089\u2013100.","journal-title":"Kidney Int"},{"key":"775_CR2","unstructured":"Kidney Disease statistics for the United States: National Institute of diabetes and digestive and kidney diseases. 2021 Available from: https:\/\/www.niddk.nih.gov\/health-information\/health-statistics\/kidney."},{"key":"775_CR3","unstructured":"Chronic Kidney. Disease in the United States, 2021;2021."},{"issue":"1","key":"775_CR4","first-page":"80","volume":"29","author":"H Chung","year":"2023","unstructured":"Chung H, Crowe CL, Kong SX, Singh R, Farej R, Elliott J, et al. Descriptive study of the economic burden among patients with type 2 diabetes mellitus, chronic kidney disease, and chronic kidney disease and type 2 diabetes mellitus in a large US commercially insured population. J Manag Care Spec Pharm. 2023;29(1):80\u20139.","journal-title":"J Manag Care Spec Pharm"},{"issue":"11","key":"775_CR5","doi-asserted-by":"publisher","first-page":"100532","DOI":"10.1016\/j.xkme.2022.100532","volume":"4","author":"CD Mullins","year":"2022","unstructured":"Mullins CD, Pantalone KM, Betts KA, Song J, Wu A, Chen Y, et al. CKD Progression and Economic Burden in Individuals With CKD Associated With Type 2 Diabetes. Kidney Med. 2022;4(11):100532.","journal-title":"Kidney Med"},{"key":"775_CR6","unstructured":"Physician fee schedule. Kidney national kidney foundation. 2022."},{"key":"775_CR7","doi-asserted-by":"crossref","unstructured":"Keith A, Betts P, Song J, Faust E, Yang K, Du Y, Sheldon X, Kong P, et al. Medical costs for managing chronic kidney disease and related complications in patients with chronic kidney disease and type 2 diabetes. Suppl Feat Publ. 2021;27(20).","DOI":"10.37765\/ajmc.2021.88807"},{"key":"775_CR8","doi-asserted-by":"crossref","unstructured":"Francis A, Harhay MN, Ong ACM, Tummalapalli SL, Ortiz A, Fogo AB, et al. Chronic kidney disease and the global public health agenda: an international consensus. Nat Rev Nephrol. 2024.","DOI":"10.1038\/s41581-024-00820-6"},{"key":"775_CR9","unstructured":"Diabetes and chronic kidney disease New York, NY: National kidney foundation inc. 2016 Available from: https:\/\/www.kidney.org\/news\/newsroom\/factsheets\/Diabetes."},{"issue":"1","key":"775_CR10","doi-asserted-by":"publisher","first-page":"972","DOI":"10.1080\/13696998.2021.1960714","volume":"24","author":"M Datar","year":"2021","unstructured":"Datar M, Burchenal W, Donovan MJ, Coca SG, Wang E, Goss TF. Payer budget impact of an artificial intelligence in vitro diagnostic to modify diabetic kidney disease progression. J Med Econ. 2021;24(1):972\u201382.","journal-title":"J Med Econ"},{"issue":"1","key":"775_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1159\/000520909","volume":"12","author":"K Vijay","year":"2021","unstructured":"Vijay K, Neuen BL, Lerma EV. Heart Failure in Patients with Diabetes and Chronic Kidney Disease: Challenges and Opportunities. Cardiorenal Med. 2021;12(1):1\u201310.","journal-title":"Cardiorenal Med"},{"issue":"10 Suppl","key":"775_CR12","first-page":"S163","volume":"23","author":"L Golestaneh","year":"2017","unstructured":"Golestaneh L, Alvarez PJ, Reaven NL, Funk SE, McGaughey KJ, Romero A, et al. All-cause costs increase exponentially with increased chronic kidney disease stage. Am J Manag Care. 2017;23(10 Suppl):S163\u201372.","journal-title":"Am J Manag Care"},{"issue":"7","key":"775_CR13","doi-asserted-by":"publisher","first-page":"1504","DOI":"10.1007\/s00125-021-05444-0","volume":"64","author":"L Chan","year":"2021","unstructured":"Chan L, Nadkarni GN, Fleming F, McCullough JR, Connolly P, Mosoyan G, et al. Derivation and validation of a machine learning risk score using biomarker and electronic patient data to predict progression of diabetic kidney disease. Diabetologia. 2021;64(7):1504\u201315.","journal-title":"Diabetologia"},{"issue":"24","key":"775_CR14","doi-asserted-by":"publisher","first-page":"2295","DOI":"10.1056\/NEJMoa1811744","volume":"380","author":"V Perkovic","year":"2019","unstructured":"Perkovic V, Jardine MJ, Neal B, Bompoint S, Heerspink HJL, Charytan DM, et al. Canagliflozin and renal outcomes in type 2 diabetes and nephropathy. N Engl J Med. 2019;380(24):2295\u2013306.","journal-title":"N Engl J Med"},{"key":"775_CR15","unstructured":"SGLT2 Inhibitors: National Kidney foundation Inc. 2022 Available from: https:\/\/www.kidney.org\/atoz\/content\/sglt2-inhibitors."},{"issue":"12","key":"775_CR16","doi-asserted-by":"publisher","first-page":"2757","DOI":"10.1007\/s13300-020-00930-x","volume":"11","author":"DC Wheeler","year":"2020","unstructured":"Wheeler DC, James J, Patel D, Viljoen A, Ali A, Evans M, et al. SGLT2 Inhibitors: Slowing of Chronic Kidney Disease Progression in Type 2 Diabetes. Diabetes Ther. 2020;11(12):2757\u201374.","journal-title":"Diabetes Ther"},{"key":"775_CR17","unstructured":"SGLT2i use among patients with CKD and diabetes. In. In: commercial C, editor. use of medications in CKD. U.S. Centers fro disease control and prevention. 2020."},{"key":"775_CR18","unstructured":"KidneyIntelX. Renalytix, Inc. 2022: Available from: https:\/\/www.kidneyintelx.com\/kidneyintelx\/."},{"key":"775_CR19","unstructured":"Renalytix.com: Renalytix plc. 2023. Available from: https:\/\/investors.renalytix.com\/news-releases\/news-release-details\/fda-grants-de-novo-marketing-authorization-kidneyintelxdkd."},{"issue":"1","key":"775_CR20","first-page":"1","volume":"3","author":"Kidney Disease Improviding Global Outcomes","year":"2013","unstructured":"Kidney Disease Improviding Global Outcomes. KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease. Kidney Int Supp. 2013;3(1):1\u2013150.","journal-title":"Kidney Int Supp"},{"issue":"1","key":"775_CR21","doi-asserted-by":"publisher","first-page":"612","DOI":"10.1016\/j.dsx.2018.11.026","volume":"13","author":"T Wang","year":"2019","unstructured":"Wang T, Xi Y, Lubwama R, Hannanchi H, Iglay K, Koro C. Chronic kidney disease among US adults with type 2 diabetes and cardiovascular diseases: A national estimate of prevalence by KDIGO 2012 classification. Diabetes Metabolic Syndrome: Clin Res Reviews. 2019;13(1):612\u20135.","journal-title":"Diabetes Metabolic Syndrome: Clin Res Reviews"},{"issue":"3","key":"775_CR22","doi-asserted-by":"publisher","first-page":"e1002532","DOI":"10.1371\/journal.pmed.1002532","volume":"15","author":"E Lin","year":"2018","unstructured":"Lin E, Chertow GM, Yan B, Malcolm E, Goldhaber-Fiebert JD. Cost-effectiveness of multidisciplinary care in mild to moderate chronic kidney disease in the United States: A modeling study. PLoS Med. 2018;15(3):e1002532\u2013e.","journal-title":"PLoS Med"},{"key":"775_CR23","doi-asserted-by":"crossref","unstructured":"Ravaghi H, Ebrahimnia M, Farzaneh A, Rostami Z, Madani M. Cost-effectiveness analysis of screening chronic kidney disease in Iran. J Clin Diagn Res. 2019;13.","DOI":"10.7860\/JCDR\/2019\/42446.13295"},{"issue":"10","key":"775_CR24","doi-asserted-by":"publisher","first-page":"e0140138","DOI":"10.1371\/journal.pone.0140138","volume":"10","author":"S Borrelli","year":"2015","unstructured":"Borrelli S, Leonardis D, Minutolo R, Chiodini P, De Nicola L, Esposito C, et al. Epidemiology of CKD Regression in Patients under Nephrology Care. PLoS ONE. 2015;10(10):e0140138.","journal-title":"PLoS ONE"},{"issue":"10","key":"775_CR25","doi-asserted-by":"publisher","first-page":"e0140063","DOI":"10.1371\/journal.pone.0140063","volume":"10","author":"AJ Sutton","year":"2015","unstructured":"Sutton AJ, Breheny K, Deeks J, Khunti K, Sharpe C, Ottridge RS, et al. Methods Used in Economic Evaluations of Chronic Kidney Disease Testing - A Systematic Review. PLoS ONE. 2015;10(10):e0140063\u2013e.","journal-title":"PLoS ONE"},{"issue":"12","key":"775_CR26","doi-asserted-by":"publisher","first-page":"1451","DOI":"10.1007\/s40273-019-00835-z","volume":"37","author":"DM Sugrue","year":"2019","unstructured":"Sugrue DM, Ward T, Rai S, McEwan P, van Haalen HGM. Economic Modelling of Chronic Kidney Disease: A Systematic Literature Review to Inform Conceptual Model Design. PharmacoEconomics. 2019;37(12):1451\u201368.","journal-title":"PharmacoEconomics"},{"key":"775_CR27","unstructured":"Affairs UDoV. Budget impact analysis 2021 Available from: https:\/\/www.herc.research.va.gov\/include\/page.asp?id=budget-impact-analysis."},{"key":"775_CR28","doi-asserted-by":"publisher","first-page":"1585","DOI":"10.2147\/DMSO.S450370","volume":"17","author":"K Kim","year":"2024","unstructured":"Kim K, Crook J, Lu CC, Nyman H, Abdelaziz A, LaFleur J. Epidemiology of Diabetic Kidney Disease among US Veterans. Diabetes Metab Syndr Obes. 2024;17:1585\u201396.","journal-title":"Diabetes Metab Syndr Obes"},{"issue":"1","key":"775_CR29","doi-asserted-by":"publisher","first-page":"117","DOI":"10.1186\/s13643-016-0297-2","volume":"5","author":"AO Molnar","year":"2016","unstructured":"Molnar AO, Hiremath S, Brown PA, Akbari A. Risk factors for unplanned and crash dialysis starts: a protocol for a systematic review and meta-analysis. Syst Rev. 2016;5(1):117.","journal-title":"Syst Rev"},{"issue":"12","key":"775_CR30","doi-asserted-by":"publisher","first-page":"1763","DOI":"10.2215\/CJN.05910519","volume":"14","author":"CE Sloan","year":"2019","unstructured":"Sloan CE, Coffman CJ, Sanders LL, Maciejewski ML, Lee S-YD, Hirth RA, et al. Trends in Peritoneal Dialysis Use in the United States after Medicare Payment Reform. Clin J Am Soc Nephrol. 2019;14(12):1763\u201372.","journal-title":"Clin J Am Soc Nephrol"},{"key":"775_CR31","unstructured":"Arias E, Xu J, United states life, table 2019. Hyattsville, MD: National center for health statistics. 2022;19."},{"key":"775_CR32","doi-asserted-by":"crossref","unstructured":"Harding JL, Morton JI, Shaw JE, Patzer RE, McDonald SP, Magliano DJ. Changes in excess mortality among adults with diabetes-related end-stage kidney disease: a comparison between the USA and Australia. Nephrol Dial Transpl. 2021.","DOI":"10.2337\/db21-1022-P"},{"key":"775_CR33","unstructured":"System USRD. 2018 USRDS Annual Data Report: Epidemiology of kidney disease in the United States. In: National Institutes of Health NIoDaDaKD, editor. Bethesda, MD. 2018."},{"issue":"4","key":"775_CR34","doi-asserted-by":"publisher","first-page":"353","DOI":"10.1001\/jamacardio.2019.0375","volume":"4","author":"ZJ Modi","year":"2019","unstructured":"Modi ZJ, Lu Y, Ji N, Kapke A, Selewski DT, Dietrich X, et al. Risk of Cardiovascular Disease and Mortality in Young Adults With End-stage Renal Disease: An Analysis of the US Renal Data System. JAMA Cardiol. 2019;4(4):353\u201362.","journal-title":"JAMA Cardiol"},{"issue":"6","key":"775_CR35","doi-asserted-by":"publisher","first-page":"450","DOI":"10.1161\/CIRCULATIONAHA.123.067584","volume":"149","author":"BL Neuen","year":"2024","unstructured":"Neuen BL, Heerspink HJL, Vart P, Claggett BL, Fletcher RA, Arnott C, et al. Estimated Lifetime Cardiovascular, Kidney, and Mortality Benefits of Combination Treatment With SGLT2 Inhibitors, GLP-1 Receptor Agonists, and Nonsteroidal MRA Compared With Conventional Care in Patients With Type 2 Diabetes and Albuminuria. Circulation. 2024;149(6):450\u201362.","journal-title":"Circulation"},{"issue":"4","key":"775_CR36","doi-asserted-by":"publisher","first-page":"e216139","DOI":"10.1001\/jamanetworkopen.2021.6139","volume":"4","author":"LA Eberly","year":"2021","unstructured":"Eberly LA, Yang L, Eneanya ND, Essien U, Julien H, Nathan AS, et al. Association of Race\/Ethnicity, Gender, and Socioeconomic Status With Sodium-Glucose Cotransporter 2 Inhibitor Use Among Patients With Diabetes in the US. JAMA Netw Open. 2021;4(4):e216139.","journal-title":"JAMA Netw Open"},{"issue":"1","key":"775_CR37","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1053\/j.ajkd.2022.11.017","volume":"82","author":"LP Gregg","year":"2023","unstructured":"Gregg LP, Ramsey DJ, Akeroyd JM, Jafry SA, Matheny ME, Virani SS, et al. Predictors, Disparities, and Facility-Level Variation: SGLT2 Inhibitor Prescription Among US Veterans With CKD. Am J Kidney Dis. 2023;82(1):53\u2013e621.","journal-title":"Am J Kidney Dis"},{"issue":"3","key":"775_CR38","doi-asserted-by":"publisher","first-page":"455","DOI":"10.34067\/KID.0007862021","volume":"3","author":"M Zhuo","year":"2022","unstructured":"Zhuo M, Li J, Buckley LF, Tummalapalli SL, Mount DB, Steele DJR, et al. Prescribing Patterns of Sodium-Glucose Cotransporter-2 Inhibitors in Patients with CKD: A Cross-Sectional Registry Analysis. Kidney360. 2022;3(3):455\u201364.","journal-title":"Kidney360"},{"issue":"7","key":"775_CR39","doi-asserted-by":"publisher","first-page":"1317","DOI":"10.1080\/03007995.2017.1320277","volume":"33","author":"J Cai","year":"2017","unstructured":"Cai J, Divino V, Burudpakdee C. Adherence and persistence in patients with type 2 diabetes mellitus newly initiating canagliflozin, dapagliflozin, dpp-4s, or glp-1s in the United States. Curr Med Res Opin. 2017;33(7):1317\u201328.","journal-title":"Curr Med Res Opin"},{"issue":"6","key":"775_CR40","doi-asserted-by":"publisher","first-page":"474","DOI":"10.1093\/eurheartj\/ehab777","volume":"43","author":"R Agarwal","year":"2021","unstructured":"Agarwal R, Filippatos G, Pitt B, Anker SD, Rossing P, Joseph A, et al. Cardiovascular and kidney outcomes with finerenone in patients with type 2 diabetes and chronic kidney disease: the FIDELITY pooled analysis. Eur Heart J. 2021;43(6):474\u201384.","journal-title":"Eur Heart J"},{"issue":"2","key":"775_CR41","doi-asserted-by":"publisher","first-page":"84","DOI":"10.17925\/EE.2021.17.2.84","volume":"17","author":"L D\u2019Marco","year":"2021","unstructured":"D\u2019Marco L, Puchades MJ, Gand\u00eda L, Forquet C, Gim\u00e9nez-Civera E, Panizo N, et al. Finerenone: A Potential Treatment for Patients with Chronic Kidney Disease and Type 2 Diabetes Mellitus. touchREV Endocrinol. 2021;17(2):84\u20137.","journal-title":"touchREV Endocrinol"},{"issue":"9","key":"775_CR42","doi-asserted-by":"publisher","first-page":"1478","DOI":"10.1681\/ASN.2012040392","volume":"24","author":"AA Honeycutt","year":"2013","unstructured":"Honeycutt AA, Segel JE, Zhuo X, Hoerger TJ, Imai K, Williams D. Medical costs of CKD in the Medicare population. J Am Soc Nephrol. 2013;24(9):1478\u201383.","journal-title":"J Am Soc Nephrol"},{"issue":"4","key":"775_CR43","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1016\/j.semnephrol.2016.05.008","volume":"36","author":"V Wang","year":"2016","unstructured":"Wang V, Vilme H, Maciejewski ML, Boulware LE. The Economic Burden of Chronic Kidney Disease and End-Stage Renal Disease. Semin Nephrol. 2016;36(4):319\u201330.","journal-title":"Semin Nephrol"},{"key":"775_CR44","doi-asserted-by":"publisher","first-page":"123","DOI":"10.2147\/CEOR.S75523","volume":"7","author":"T Knight","year":"2015","unstructured":"Knight T, Schaefer C, Krasa H, Oberdhan D, Chapman A, Perrone RD. Medical resource utilization and costs associated with autosomal dominant polycystic kidney disease in the USA: a retrospective matched cohort analysis of private insurer data. Clinicoecon Outcomes Res. 2015;7:123\u201332.","journal-title":"Clinicoecon Outcomes Res"},{"key":"775_CR45","unstructured":"United States Renal Data System. 2021 USRDS annual data report: epidemiology of kidney disease in the United States. National institutes of health, national institute of diabetes and digestive and kidney diseases, Bethesda, MD. 2021."},{"issue":"3","key":"775_CR46","first-page":"16","volume":"10","author":"D Forfang","year":"2018","unstructured":"Forfang D. Chronic Kidney Disease: Achieving Better Outcomes. ASN Kidney News. 2018;10(3):16.","journal-title":"ASN Kidney News"},{"key":"775_CR47","unstructured":"Nephcure kidney International. Transplant Available from: https:\/\/nephcure.org\/livingwithkidneydisease\/kidney-failure\/transplant\/."},{"key":"775_CR48","unstructured":"United States Renal Data System. Epidemiology of kidney disease in the United States. Bethesda (MD). 2015."},{"key":"775_CR49","unstructured":"Dapagliflozin GoodRx. GoodRx, Inc.; Available from: https:\/\/www.goodrx.com\/dapagliflozin?dosage=5mg&form=tablet&label_override=Farxiga&quantity=30&sort_type=popularity"},{"key":"775_CR50","volume-title":"U.S. consumer price index: prescription and nonprescription drugs 1960\u20132023 Statista","author":"M Milkulic","year":"2024","unstructured":"Milkulic M. U.S. consumer price index: prescription and nonprescription drugs 1960\u20132023 Statista. Search Department: Statista; 2024."},{"issue":"1","key":"775_CR51","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1007\/s11136-012-0139-1","volume":"22","author":"M Rajan","year":"2013","unstructured":"Rajan M, Lai KC, Tseng CL, Qian S, Selim A, Kazis L, et al. Estimating utilities for chronic kidney disease, using SF-36 and SF-12-based measures: challenges in a population of veterans with diabetes. Qual Life Res. 2013;22(1):53\u201364.","journal-title":"Qual Life Res"},{"issue":"2","key":"775_CR52","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1111\/j.1524-4733.2009.00668.x","volume":"13","author":"K Howard","year":"2010","unstructured":"Howard K, White S, Salkeld G, McDonald S, Craig JC, Chadban S, et al. Cost-effectiveness of screening and optimal management for diabetes, hypertension, and chronic kidney disease: a modeled analysis. Value Health. 2010;13(2):196\u2013208.","journal-title":"Value Health"},{"issue":"1","key":"775_CR53","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1038\/ki.1996.307","volume":"50","author":"A Laupacis","year":"1996","unstructured":"Laupacis A, Keown P, Pus N, Krueger H, Ferguson B, Wong C, et al. A study of the quality of life and cost-utility of renal transplantation. Kidney Int. 1996;50(1):235\u201342.","journal-title":"Kidney Int"},{"issue":"1","key":"775_CR54","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1186\/s12882-017-0497-6","volume":"18","author":"BO Yarnoff","year":"2017","unstructured":"Yarnoff BO, Hoerger TJ, Simpson SK, Leib A, Burrows NR, Shrestha SS, et al. The cost-effectiveness of using chronic kidney disease risk scores to screen for early-stage chronic kidney disease. BMC Nephrol. 2017;18(1):85.","journal-title":"BMC Nephrol"},{"key":"775_CR55","doi-asserted-by":"publisher","first-page":"c5869","DOI":"10.1136\/bmj.c5869","volume":"341","author":"B Manns","year":"2010","unstructured":"Manns B, Hemmelgarn B, Tonelli M, Au F, Chiasson TC, Dong J, et al. Population based screening for chronic kidney disease: cost effectiveness study. BMJ. 2010;341:c5869.","journal-title":"BMJ"},{"issue":"4","key":"775_CR56","first-page":"312","volume":"15","author":"F Lalibert\u00e9","year":"2009","unstructured":"Lalibert\u00e9 F, Bookhart BK, Vekeman F, Corral M, Duh MS, Bailey RA, et al. Direct all-cause health care costs associated with chronic kidney disease in patients with diabetes and hypertension: a managed care perspective. J Manag Care Pharm. 2009;15(4):312\u201322.","journal-title":"J Manag Care Pharm"},{"issue":"5","key":"775_CR57","doi-asserted-by":"publisher","first-page":"534","DOI":"10.1111\/nep.13478","volume":"24","author":"S Low","year":"2019","unstructured":"Low S, Lim SC, Zhang X, Wang J, Yeo SJD, Yeoh LY, et al. Medical costs associated with chronic kidney disease progression in an Asian population with type 2 diabetes mellitus. Nephrol (Carlton Vic). 2019;24(5):534\u201341.","journal-title":"Nephrol (Carlton Vic)"},{"issue":"5","key":"775_CR58","doi-asserted-by":"publisher","first-page":"e0217487","DOI":"10.1371\/journal.pone.0217487","volume":"14","author":"J Thornton Snider","year":"2019","unstructured":"Thornton Snider J, Sullivan J, van Eijndhoven E, Hansen MK, Bellosillo N, Neslusan C, et al. Lifetime benefits of early detection and treatment of diabetic kidney disease. PLoS ONE. 2019;14(5):e0217487.","journal-title":"PLoS ONE"},{"key":"775_CR59","first-page":"28","volume-title":"Slowing Diabetic Kidney Disease Progression: Where Do We Stand Today? Chronic Kidney Disease and Type 2 Diabetes","author":"SC Naaman","year":"2021","unstructured":"Naaman SC, Bakris GL. Slowing Diabetic Kidney Disease Progression: Where Do We Stand Today? Chronic Kidney Disease and Type 2 Diabetes. Arlington (VA): American Diabetes Association; 2021. pp. 28\u201332."},{"key":"775_CR60","doi-asserted-by":"crossref","unstructured":"Radbill B, Murphy B, LeRoith D. Rationale and strategies for early detection and management of diabetic kidney disease. Mayo Clinic proceedings. 2008;83(12):1373-81.","DOI":"10.4065\/83.12.1373"},{"issue":"12","key":"775_CR61","doi-asserted-by":"publisher","first-page":"2900","DOI":"10.2337\/dc22-0614","volume":"45","author":"JA Lamprea-Montealegre","year":"2022","unstructured":"Lamprea-Montealegre JA, Madden E, Tummalapalli SL, Chu CD, Peralta CA, Du Y, et al. Prescription Patterns of Cardiovascular- and Kidney-Protective Therapies Among Patients With Type 2 Diabetes and Chronic Kidney Disease. Diabetes Care. 2022;45(12):2900\u20136.","journal-title":"Diabetes Care"},{"issue":"8","key":"775_CR62","doi-asserted-by":"publisher","first-page":"1139","DOI":"10.1002\/clc.23665","volume":"44","author":"DZI Cherney","year":"2021","unstructured":"Cherney DZI, Dagogo-Jack S, McGuire DK, Cosentino F, Pratley R, Shih WJ, et al. Kidney outcomes using a sustained \u2265 40% decline in eGFR: A meta-analysis of SGLT2 inhibitor trials. Clin Cardiol. 2021;44(8):1139\u201343.","journal-title":"Clin Cardiol"},{"issue":"5","key":"775_CR63","doi-asserted-by":"publisher","first-page":"1237","DOI":"10.1111\/dom.13648","volume":"21","author":"T Toyama","year":"2019","unstructured":"Toyama T, Neuen BL, Jun M, Ohkuma T, Neal B, Jardine MJ, et al. Effect of SGLT2 inhibitors on cardiovascular, renal and safety outcomes in patients with type 2 diabetes mellitus and chronic kidney disease: A systematic review and meta-analysis. Diabetes Obes Metab. 2019;21(5):1237\u201350.","journal-title":"Diabetes Obes Metab"},{"issue":"10","key":"775_CR64","doi-asserted-by":"publisher","first-page":"e25121","DOI":"10.1097\/MD.0000000000025121","volume":"100","author":"M Qiu","year":"2021","unstructured":"Qiu M, Ding L, Zhou H. Effects of SGLT2 inhibitors on cardiovascular and renal outcomes in type 2 diabetes: A meta-analysis with trial sequential analysis. Medicine. 2021;100(10):e25121.","journal-title":"Medicine"}],"container-title":["Cost Effectiveness and Resource Allocation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12962-026-00775-4","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12962-026-00775-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12962-026-00775-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T18:03:19Z","timestamp":1788804199000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s12962-026-00775-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,24]]},"references-count":64,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["775"],"URL":"https:\/\/doi.org\/10.1186\/s12962-026-00775-4","relation":{},"ISSN":["1478-7547"],"issn-type":[{"value":"1478-7547","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,24]]},"assertion":[{"value":"1 October 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 May 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 June 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Not applicable.","order":1,"name":"Ethics","label":"Ethics approval and consent to participate","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","label":"Consent for publication","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"JTC and JES are employees of Avalon Health Economics and were contracted by Renalytix for completion of this study. SC and MD are employees of Renalytix. TM is a former employee of Renalytix.","order":3,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}],"article-number":"112"}}