G P Fadini1, G Zatti2, A Consoli3, E Bonora4, G Sesti5, A Avogaro2. 1. Department of Medicine, University of Padova, 35128 Padova, Italy. Electronic address: gianpaolo.fadini@unipd.it. 2. Department of Medicine, University of Padova, 35128 Padova, Italy. 3. Department of Medicine and Aging Science, "G. D'Annunzio" University of Chieti, 68100 Chieti, Italy. 4. Department of Medicine, University of Verona, 37154 Verona, Italy. 5. Department of Medical and Surgical Sciences, "Magna Graecia" University of Catanzaro, 88100 Catanzaro, Italy.
Abstract
BACKGROUND: Randomized controlled trials (RCTs) in the field of diabetes have limitations inherent to the fact that design, setting, and patient characteristics may be poorly transferrable to clinical practice. Thus, evidence from studies using routinely accumulated clinical data are increasingly valued. AIMS: We herein describe rationale and design of the DARWIN-T2D (DApagliflozin Real World evIdeNce in Type 2 Diabetes), a multicenter retrospective nationwide study conducted at 50 specialist outpatient clinics in Italy and promoted by the Italian Diabetes Society. DATA SYNTHESIS: The primary objective of the study is to describe the baseline clinical characteristics (particularly HbA1c) of patients initiated on dapagliflozin from marketing authorization approval to the end of 2016. Secondary and exploratory objectives will evaluate the changes in glycaemic and extraglycaemic efficacy parameters after initiation of dapagliflozin or after initiation of comparator glucose lowering medications (DPP-4 inhibitors, gliclazide extended release, and long-acting GLP-1 receptor agonists). An automated software will extract relevant data from the same electronic chart system at all centres, thereby minimizing data treatment and human intervention. CONCLUSION: The study is expected to collect an enormous dataset of information on dapagliflozin- and comparator-using patients. After study completion, the Italian Diabetes Society will launch an open crowdsourcing call on the DARWIN-T2D database, challenging diabetes researchers to apply their ideas and approaches to address new unmet needs and knowledge gaps in diabetes. We believe this will move DARWIN-T2D to the next generation of real world studies.
BACKGROUND: Randomized controlled trials (RCTs) in the field of diabetes have limitations inherent to the fact that design, setting, and patient characteristics may be poorly transferrable to clinical practice. Thus, evidence from studies using routinely accumulated clinical data are increasingly valued. AIMS: We herein describe rationale and design of the DARWIN-T2D (DApagliflozin Real World evIdeNce in Type 2 Diabetes), a multicenter retrospective nationwide study conducted at 50 specialist outpatient clinics in Italy and promoted by the Italian Diabetes Society. DATA SYNTHESIS: The primary objective of the study is to describe the baseline clinical characteristics (particularly HbA1c) of patients initiated on dapagliflozin from marketing authorization approval to the end of 2016. Secondary and exploratory objectives will evaluate the changes in glycaemic and extraglycaemic efficacy parameters after initiation of dapagliflozin or after initiation of comparator glucose lowering medications (DPP-4 inhibitors, gliclazide extended release, and long-acting GLP-1 receptor agonists). An automated software will extract relevant data from the same electronic chart system at all centres, thereby minimizing data treatment and human intervention. CONCLUSION: The study is expected to collect an enormous dataset of information on dapagliflozin- and comparator-using patients. After study completion, the Italian Diabetes Society will launch an open crowdsourcing call on the DARWIN-T2D database, challenging diabetes researchers to apply their ideas and approaches to address new unmet needs and knowledge gaps in diabetes. We believe this will move DARWIN-T2D to the next generation of real world studies.
Authors: Gian Paolo Fadini; Anna Solini; Maria Laura Manca; Giuseppe Penno; Adriano Gatti; Roberto Anichini; Stefano Del Prato; Angelo Avogaro Journal: Diabetes Obes Metab Date: 2018-09-21 Impact factor: 6.577
Authors: Jetty A Overbeek; Edith M Heintjes; Eline L Huisman; Christian K Tikkanen; Arnout W van Diermen; Fernie J A Penning-van Beest; Ron M C Herings Journal: Diabetes Obes Metab Date: 2018-05-29 Impact factor: 6.577