Statistical Considerations for Cardiovascular Outcome Trials in Patients with T2DM
Christy Chuang-Stein, Chuang-Stein Consulting Qi Jiang, Amgen Chunlei Ke, Amgen Mark Levenson, CDER, FDA Lingyun Liu, Cytel Haijun Ma, Amgen Jeff Maca, Quintiles *Olga V Marchenko, Quintiles Cyrus Mehta, Cytel Soomin Park, Eli Lilly Estelle Russek-Cohen, CBER FDA Matilde Sanchez-Kam, Arena Pharmaceuticals Richard C Zink, JMP Life Sciences, SAS Institute Keywords: diabetes mellitus, cardiovascular risk, CVOT, multiplicity, subgroup analysis, missing data In 2008 the US FDA released the Guidance for Industry, “Diabetes Mellitus – Evaluating Cardiovascular Risk in New Anti-diabetic Therapies to Treat Type 2 Diabetes”, that changed the way new anti-diabetes drugs are evaluated and brought to the market. To meet guidance requirements on CV risk assessment, different strategies that include meta-analyses and CVOTs have been proposed. The CVOTs provide an opportunity to assess safety signals beyond CV risk and assess the benefit/risk ratio better in diabetic patients with a high risk for CV events, but they also present challenges. Key statistical issues and challenges encountered at the design and analysis stages of CVOTs include complex multiplicity scenarios, non-inferiority and superiority testing, subgroup analysis, patient retention and missing data. In this presentation, the work of the American Statistical Association Biopharmaceutical Section Safety Working Group on these issues will be shared and strategies to address some of the challenges will be discussed.
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