The overall goal of this research study is to estimate the risk of female breast cancer and bladder cancer in patients who are prescribed dapagliflozin compared to patients prescribed other oral antidiabetic drugs (ADs). Dapagliflozin and other antidiabetic drugs are used to treat type 2 diabetes mellitus. Because dapagliflozin's mechanism of action and the potential for an increased risk of cancer, there is interest in further evaluating its safety in a large population. The study will be implemented in four administrative health care data sources in three countries: in the United Kingdom, the Clinical Practice Research Datalink (CPRD); in the United States, the Centers for Medicare and Medicaid Services (CMS) Medicare databases and the HealthCore Integrated Research Database (HIRDSM); and, in the Netherlands, the PHARMO Database Network. Individuals in the databases will be included in the study if they meet the following age criteria; 40 years or older (CPRD and PHARMO), 40-64 years in HIRDSM or 65 years or older (Medicare). The final study report will be submitted for review to the European Medicines Agency to ensure the continued safety of the drug and will be submitted for publication in a scientific journal.
This cohort study compares the incidence of female breast cancer and the sex-specific incidence of bladder cancer among new users of dapagliflozin with those among new users of other specific ADs. The study duration is 10 years. Follow-up will start on the date a patient has a first prescription or dispensing for a study drug, and will continue until first occurrence of any cancer end-point, death, discontinuation from the study database, or the end of the study. The study will be implemented in adults in four administrative health care data sources in three countries: United Kingdom: the Clinical Practice Research Datalink; United States: the Centers for Medicare and Medicaid Services Medicare databases and the HealthCore Integrated Research Database; Netherlands: the PHARMO Database Network. Propensity scores will be estimated at cohort entry by logistic regression models. Incidence rates of each outcome will be determined in each cohort. Propensity score stratification will be used to estimate adjusted incidence rate ratios of the outcomes of interest with 95% confidence intervals. Analyses will be conducted in each data source, and a pooled estimate will be calculated if deemed appropriate.
Lia Gutierrez - Chief Investigator - RTI Health Solutions ( USA )
Alicia Gilsenan - Corresponding Applicant - RTI Health Solutions ( USA )
Alicia Gilsenan - Collaborator - RTI Health Solutions ( USA )
Brian Calingaert - Collaborator - RTI Health Solutions ( USA )
Catherine Saltus - Collaborator - RTI Health Solutions ( USA )
David Martinez - Collaborator - RTI Health Solutions ( USA )
Elizabeth Andrews - Collaborator - RTI Health Solutions ( USA )
Estel Plana Hortoneda - Collaborator - RTI Health Solutions ( USA )
Heather Danysh - Collaborator - RTI Health Solutions ( USA )
James Kaye - Collaborator - RTI Health Solutions ( USA )
Jaume Aguado - Collaborator - RTI Health Solutions ( USA )
Jennifer Bartsch - Collaborator - RTI Health Solutions ( USA )
Joan Fortuny - Collaborator - RTI Health Solutions ( USA )
Karolina Andersson Sundell - Collaborator - Astra Zeneca R&D Molndal Sweden
Kay Johannes - Collaborator - RTI Health Solutions ( USA )
Lisa McQuay - Collaborator - RTI Health Solutions ( USA )
Maria Reynolds - Collaborator - RTI Health Solutions ( USA )
Ryan Ziemiecki - Collaborator - RTI Health Solutions ( USA )
Shannon Hunter - Collaborator - RTI Health Solutions ( USA )
Sophie Shen - Collaborator - Bristol-Myers Squibb Pharmaceuticals Limited - UK ( BMS )
Zhou Xiaolei - Collaborator - RTI Health Solutions ( USA )
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