- CSR Summary Available
- NCT02065791
- Primary Citation
Trial Information
Generic NameCanagliflozinProduct NameINVOKANA®Therapeutic AreaNutritional and Metabolic DiseasesEnrollment4401% Female33.9%% White40.7%
Product ClassSodium-Glucose Co-Transporter 2 (SGLT2) InhibitorSponsor Protocol Number28431754DNE3001Data PartnerJohnson & JohnsonCondition StudiedDiabetes Mellitus, Type 2Mean/Median Age (Years)63
Supporting Documentation
- Collected Datasets Available
- Data Definition Specification Available
- Protocol with Amendments Available
- Statistical Analysis Plan Available
- Clinical Study Report Available
Approved Data Requests Associated with this Trial
- 2024-0716 : Validation of causal machine learning methods to identify heterogeneous treatment effects
- 2024-0600 : Bayesian machine learning for the identification of benefiting subgroups and treatment effect heterogeneity for canagliflozin in T2DM patients
- 2024-0580 : Developing approaches to accelerate clinical trials using real world data (RWD) from electronic health records (EHR)
- 2024-0572 : Meta-analysis on the effectiveness of canagliflozin in heart failure in elderly patients
- 2024-0516 : Identify treatment responders in patients with type 2 diabetes using a machine learning based dynamic cardiovascular risk assessment tool ML-CVD in clinical trials
- 2024-0356 : Combining clinical trials with external data: applications in the YODA database
- 2024-0296 : Validation of a novel clinical risk score for cardiovascular outcomes in type 2 diabetes
- 2024-0184 : Safety and Effectiveness of Sodium-Glucose Cotransporter-2 Inhibitors in Comparison with Glucagon-Like Peptide-1 Agonists on Weight Loss: A Meta-Analysis
- 2024-0060 : Using Synthetic Controls to Improve Randomised Controlled Trials for Rare Diseases
- 2023-5534 : Quality tolerance limit and duplicated patient investigation in clinical trials
- 2023-5514 : Development of two predictive tools to estimate (1) cardiovascular and (2) renal risk in CKD patients using machine learning
- 2023-5367 : Efficacy and safety of canagliflozin in diabetic patients with erythrocytosis: A pooled analysis of the CANVAS Program and CREDENCE trial
- 2023-5195 : Predictive modeling of adverse events and symptoms patterns in large scale clinical trials
- 2022-5124 : Understanding frailty, multimorbidity and renal failure in clinical trials: Attrition, retention and heterogeneity of treatment effects in trials
- 2022-5076 : The efficacy of canagliflozin in diabetes subgroups by using an unsupervised machine-learning method
- 2022-5045 : Network MA of RCTs to compare the effects of metabolic surgery vs. modern drug treatment on cardiovascular outcomes + mortality in patients with DMT2
- 2022-5007 : Risk stratification and responder identification for GLP-1RA and SGLT2i in T2DM: application of two machine learning based prediction models
- 2022-4996 : Risk stratification and responder identification for GLP-1RA and SGLT2i in T2DM: application of two machine learning based prediction models
- 2021-4850 : Cluster Analysis of Cardiovascular Phenotypes and SGLT2 Inhibition in Patients With Type 2 Diabetes and Established Cardiovascular Disease
- 2021-4814 : A systematic review and network meta-analysis (NMA) to determine the best second-line therapy for type 2 diabetes mellitus in people aged 65 and over
- 2021-4812 : Effects of new antidiabetic agents on cardiovascular outcomes in older adults: systemic review and meta-analysis
- 2020-4488 : Mediators between Canagliflozin and End-stage kidney disease: Post-hoc mediation analyses of the CREDENCE trial