Effectiveness of Dapagliflozin as Add-On to Metformin with or without Other Oral Antidiabetic Drugs in Type 2 Diabetes Mellitus: A Multicentre, Retrospective, Real-World Database Study.
{"title":"Effectiveness of Dapagliflozin as Add-On to Metformin with or without Other Oral Antidiabetic Drugs in Type 2 Diabetes Mellitus: A Multicentre, Retrospective, Real-World Database Study.","authors":"Bipin Sethi, Rakesh Sahay, Mangesh Tiwaskar, Vijay Negalur, Rajnish Dhediya, Kumar Gaurav, Rahul Rathod, Bhavesh Kotak, Gauri Dhanaki, Snehal Shah","doi":"10.1007/s40801-023-00398-8","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Real-world Indian studies evaluating effectiveness of dapagliflozin as an add-on to other oral antidiabetic drugs (OAD) in patients with type 2 diabetes mellitus (DM) are scarce.</p><p><strong>Methods: </strong>An electronic medical record (EMR)-based, retrospective, multicentre study was conducted to evaluate the effectiveness of dapagliflozin as add-on therapy in adult patients with inadequately controlled DM on metformin with or without other OAD. Baseline characteristics (visit 1: metformin or metformin plus OAD treatment for at least 30 days) and treatment-related outcomes (visit 2: follow-up) considered between 60 and 140 days after adding/switching dapagliflozin [glycated haemoglobin (HbA1c), body mass index (BMI), systolic blood pressure (SBP) and diastolic blood pressure (DBP)] were analysed.</p><p><strong>Results: </strong>A total of 3616 patients were screened from 478 centres. Most patients had received dapagliflozin (D) + metformin (M) + at least one other OAD [D + M + OAD, n = 2907 (80.4%), 408 followed-up with HbA1c reported], while 709 patients (19.6%, 138 followed-up with HbA1c reported) received dapagliflozin + metformin (D + M). Treatment with dapagliflozin as an add-on therapy resulted in significant change in HbA1c (-1.1 ± 1.44%; p < 0.05 for HbA1c subgroup ≥ 7.5%; -1.6 ± 1.41%; p < 0.05 for HbA1c subgroup ≥ 8%) at visit 2 compared with visit 1. Significant change in body weight (-1.4 ± 3.31 kg; p < 0.05 for HbA1c subgroup ≥ 7.5%; - 1.5 ± 3.22 kg; p < 0.05 for HbA1c subgroup ≥ 8%) was observed at visit 2. Similarly, a significant change in BMI was noted for the HbA1c subgroup ≥ 7.5% (-1.0 ± 8.38 kg/m<sup>2</sup>). However, the change in BMI in the HbA1c subgroup ≥ 8% was noted to be -1.4 ± 10.4 kg/m<sup>2</sup>, which was not statistically significant (p = 0.08). In the overall study population, significant change in the SBP (-4.5 ± 14.9 mmHg; p < 0.05 for HbA1c subgroup ≥ 7.5%; -4.5 ± 15.1 mmHg; p < 0.0001 for HbA1c subgroup ≥ 8%) was observed at visit 2 compared with visit 1. On identical lines, significant change in DBP (-1.5 ± 8.94 mmHg; p < 0.05 for HbA1c subgroup ≥ 7.5%; -1.4 ± 8.91 mmHg; p < 0.05 for HbA1c subgroup ≥ 8%) was noted.</p><p><strong>Conclusions: </strong>Dapagliflozin showed significant improvement in glycemic parameter, BMI and BP when added to metformin, with or without other OADs in a real-world scenario.</p>","PeriodicalId":11282,"journal":{"name":"Drugs - Real World Outcomes","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10928049/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Drugs - Real World Outcomes","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40801-023-00398-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/10/28 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Real-world Indian studies evaluating effectiveness of dapagliflozin as an add-on to other oral antidiabetic drugs (OAD) in patients with type 2 diabetes mellitus (DM) are scarce.
Methods: An electronic medical record (EMR)-based, retrospective, multicentre study was conducted to evaluate the effectiveness of dapagliflozin as add-on therapy in adult patients with inadequately controlled DM on metformin with or without other OAD. Baseline characteristics (visit 1: metformin or metformin plus OAD treatment for at least 30 days) and treatment-related outcomes (visit 2: follow-up) considered between 60 and 140 days after adding/switching dapagliflozin [glycated haemoglobin (HbA1c), body mass index (BMI), systolic blood pressure (SBP) and diastolic blood pressure (DBP)] were analysed.
Results: A total of 3616 patients were screened from 478 centres. Most patients had received dapagliflozin (D) + metformin (M) + at least one other OAD [D + M + OAD, n = 2907 (80.4%), 408 followed-up with HbA1c reported], while 709 patients (19.6%, 138 followed-up with HbA1c reported) received dapagliflozin + metformin (D + M). Treatment with dapagliflozin as an add-on therapy resulted in significant change in HbA1c (-1.1 ± 1.44%; p < 0.05 for HbA1c subgroup ≥ 7.5%; -1.6 ± 1.41%; p < 0.05 for HbA1c subgroup ≥ 8%) at visit 2 compared with visit 1. Significant change in body weight (-1.4 ± 3.31 kg; p < 0.05 for HbA1c subgroup ≥ 7.5%; - 1.5 ± 3.22 kg; p < 0.05 for HbA1c subgroup ≥ 8%) was observed at visit 2. Similarly, a significant change in BMI was noted for the HbA1c subgroup ≥ 7.5% (-1.0 ± 8.38 kg/m2). However, the change in BMI in the HbA1c subgroup ≥ 8% was noted to be -1.4 ± 10.4 kg/m2, which was not statistically significant (p = 0.08). In the overall study population, significant change in the SBP (-4.5 ± 14.9 mmHg; p < 0.05 for HbA1c subgroup ≥ 7.5%; -4.5 ± 15.1 mmHg; p < 0.0001 for HbA1c subgroup ≥ 8%) was observed at visit 2 compared with visit 1. On identical lines, significant change in DBP (-1.5 ± 8.94 mmHg; p < 0.05 for HbA1c subgroup ≥ 7.5%; -1.4 ± 8.91 mmHg; p < 0.05 for HbA1c subgroup ≥ 8%) was noted.
Conclusions: Dapagliflozin showed significant improvement in glycemic parameter, BMI and BP when added to metformin, with or without other OADs in a real-world scenario.
期刊介绍:
Drugs - Real World Outcomes targets original research and definitive reviews regarding the use of real-world data to evaluate health outcomes and inform healthcare decision-making on drugs, devices and other interventions in clinical practice. The journal includes, but is not limited to, the following research areas: Using registries/databases/health records and other non-selected observational datasets to investigate: drug use and treatment outcomes prescription patterns drug safety signals adherence to treatment guidelines benefit : risk profiles comparative effectiveness economic analyses including cost-of-illness Data-driven research methodologies, including the capture, curation, search, sharing, analysis and interpretation of ‘big data’ Techniques and approaches to optimise real-world modelling.