• CSR Summary
• NCT01809327
• Primary Citation
• Data Specification

Approved Data Requests Associated with this Trial

• 2024-0960 : Predictability of Canagliflozin and Metformin on Type 2 Diabetes
• 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)
• 2024-0060 : Using Synthetic Controls to Improve Randomised Controlled Trials for Rare Diseases
• 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
• 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
• 2021-4764 : Reporting of harms in SGLT2 clinical study reports compared to trial registries and publications: a methodological review
• 2020-4465 : Examination of implications of acute declines in kidney function with SGLTII inhibitors
• 2020-4417 : Vibration of effects in pooled analyses of Canagliflozin vs placebo, randomized, double blind trials
• 2020-4319 : Subtype-dependent risk of stroke following the use of SGLT2 inhibitors
• 2020-4211 : The effect of SGLT2 inhibitors in diabetes subgroups identified by data-driven clustering
• 2019-4071 : Efficacy and safety of SGLT2 inhibitors in the treatment of type 2 diabetes: systematic review incorporating unpublished clinical study reports
• 2017-1746 : Heterogeneity in relative treatment efficacy by age, sex, socioeconomic status and comorbidity