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dc.contributor.authorDennis, JM
dc.contributor.authorYoung, KG
dc.contributor.authorMcGovern, AP
dc.contributor.authorMateen, BA
dc.contributor.authorVollmer, SJ
dc.contributor.authorSimpson, MD
dc.contributor.authorHenley, WE
dc.contributor.authorHolman, RR
dc.contributor.authorSattar, N
dc.contributor.authorPearson, ER
dc.contributor.authorHattersley, AT
dc.contributor.authorJones, AG
dc.contributor.authorShields, BM
dc.date.accessioned2022-11-25T11:03:40Z
dc.date.issued2022-11-14
dc.date.updated2022-11-25T10:50:06Z
dc.description.abstractBackground Current treatment guidelines do not provide recommendations to support the selection of treatment for most people with type 2 diabetes. We aimed to develop and validate an algorithm to allow selection of optimal treatment based on glycaemic response, weight change, and tolerability outcomes when choosing between SGLT2 inhibitor or DPP-4 inhibitor therapies. Methods In this retrospective cohort study, we identified patients initiating SGLT2 and DPP-4 inhibitor therapies after Jan 1, 2013, from the UK Clinical Practice Research Datalink (CPRD). We excluded those who received SGLT2 or DPP-4 inhibitors as first-line treatment or insulin at the same time, had estimated glomerular filtration rate (eGFR) of less than 45 mL/min per 1·73 m2, or did not have a valid baseline glycated haemoglobin (HbA1c) measure (<53 or ≥120 mmol/mol). The primary efficacy outcome was the HbA1c value reached 6 months after drug initiation, adjusted for baseline HbA1c. Clinical features associated with differential HbA1c outcome on the two therapies were identified in CPRD (n=26 877), and replicated in reanalysis of 14 clinical trials (n=10 414). An algorithm to predict individual-level differential HbA1c outcome on the two therapies was developed in CPRD (derivation; n=14 069) and validated in head-to-head trials (n=2499) and CPRD (independent validation; n=9376). In CPRD, we further explored heterogeneity in 6-month weight change and treatment discontinuation. Findings Among 10 253 patients initiating SGLT2 inhibitors and 16 624 patients initiating DPP-4 inhibitors in CPRD, baseline HbA1c, age, BMI, eGFR, and alanine aminotransferase were associated with differential HbA1c outcome with SGLT2 inhibitor and DPP-4 inhibitor therapies. The median age of participants was 62·0 years (IQR 55·0–70·0). 10 016 (37·3%) were women and 16 861 (62·7%) were men. An algorithm based on these five features identified a subgroup, representing around four in ten CPRD patients, with a 5 mmol/mol or greater observed benefit with SGLT2 inhibitors in all validation cohorts (CPRD 8·8 mmol/mol [95% CI 7·8–9·8]; CANTATA-D and CANTATA-D2 trials 5·8 mmol/mol [3·9–7·7]; BI1245.20 trial 6·6 mmol/mol [2·2–11·0]). In CPRD, predicted differential HbA1c response with SGLT2 inhibitor and DPP-4 inhibitor therapies was not associated with weight change. Overall treatment discontinuation within 6 months was similar in patients predicted to have an HbA1c benefit with SGLT2 inhibitors over DPP-4 inhibitors (median 15·2% [13·2–20·3] vs 14·4% [12·9–16·7]). A smaller subgroup predicted to have greater HbA1c reduction with DPP-4 inhibitors were twice as likely to discontinue SGLT2 inhibitors than DPP-4 inhibitors (median 26·8% [23·4–31·0] vs 14·8% [12·9–16·8]). Interpretation A validated treatment selection algorithm for SGLT2 inhibitor and DPP-4 inhibitor therapies can support decisions on optimal treatment for people with type 2 diabetes.en_GB
dc.description.sponsorshipBHF-Turing Cardiovascular Data Science Awarden_GB
dc.description.sponsorshipMedical Research Councilen_GB
dc.format.extent2021.11.11.21265959-
dc.identifier.citationVol. 4, No. 12, pp. 873-883en_GB
dc.identifier.doihttps://doi.org/10.1016/S2589-7500(22)00174-1
dc.identifier.grantnumberSP/19/6/34809en_GB
dc.identifier.grantnumberMR/N00633X/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/131850
dc.identifierORCID: 0000-0002-7171-732X (Dennis, John M)
dc.identifierORCID: 0000-0003-2570-3864 (Young, Katherine G)
dc.identifierORCID: 0000-0002-6833-9399 (McGovern, Andrew P)
dc.identifierORCID: 0000-0001-6273-2619 (Henley, William E)
dc.identifierORCID: 0000-0001-5620-473X (Hattersley, Andrew T)
dc.identifierORCID: 0000-0002-0883-7599 (Jones, Angus G)
dc.identifierScopusID: 7407101887 (Jones, Angus G)
dc.identifierORCID: 0000-0003-3785-327X (Shields, Beverley M)
dc.language.isoenen_GB
dc.publisherElsevieren_GB
dc.rights© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.en_GB
dc.subjectNutritionen_GB
dc.subjectClinical Trials and Supportive Activitiesen_GB
dc.subjectDiabetesen_GB
dc.subjectObesityen_GB
dc.subjectPreventionen_GB
dc.subjectClinical Researchen_GB
dc.titleDevelopment of a treatment selection algorithm for SGLT2 and DPP-4 inhibitor therapies in people with type 2 diabetes: a retrospective cohort studyen_GB
dc.typeArticleen_GB
dc.date.available2022-11-25T11:03:40Z
dc.identifier.issn2589-7500
dc.descriptionThis is the final version. Available from Elsevier via the DOI in this record. en_GB
dc.descriptionData sharing: CPRD data are available by application to the CPRD Independent Scientific Advisory Committee and clinical trial data are accessible by application to the Yale University Open Data Access Project and Vivli.en_GB
dc.identifier.journalThe Lancet Digital Healthen_GB
dc.relation.ispartofThe Lancet Digital Health, 4(12)
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_GB
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2022-11-14
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2022-11-25T10:58:37Z
refterms.versionFCDVoR
refterms.dateFOA2022-11-25T11:03:41Z
refterms.panelAen_GB
refterms.dateFirstOnline2022-11-14


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© 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY
4.0 license.
Except where otherwise noted, this item's licence is described as © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.