Statistical Considerations for Cardiovascular Outcome Trials in Patients with Type 2 Diabetes Mellitus. (2nd October 2017)

• Record Type: Journal Article
• Authors: Marchenko, Olga; Jiang, Qi; Chuang-Stein, Christy; Mehta, Cyrus; Levenson, Mark; Russek-Cohen, Estelle; Liu, Lingyun; Sanchez-Kam, Matilde; Zink, Richard; Ke, Chunlei; Ma, Haijun; Maca, Jeff; Park, Soomin
• Is Part Of: Statistics in biopharmaceutical research. Volume 9:Number 4(2017)
• Page Start: 347
• Page End: 360
• Publication Date: 2017-10-02
• Subjects: Cardiovascular risk -- CVOT -- Diabetes mellitus -- Event window -- Missing data -- Multiplicity -- Subgroup analysis; Pharmacy -- Statistical methods -- Periodicals; Pharmaceutical biotechnology -- Statistical methods -- Periodicals; Biopharmaceutics -- Periodicals; Biometry -- Periodicals; Pharmacy -- Statistical methods; Periodicals; 615.190727
• DOI: 10.1080/19466315.2017.1280411
• Languages: English
• ISSNs: 1946-6315

Abstract

ABSTRACT: This is the second article written by the American Statistical Association Biopharmaceutical Section Safety Working Group. In the first article, we reviewed the drugs approved by the United States Food and Drug Administration to treat type 2 diabetes mellitus during 2002–2014 with a focus on the cardiovascular (CV) risk assessment. We discussed different strategies to address premarketing and post-marketing CV risk requirements and raised some questions that required further research. The main objective of this article is to outline statistical challenges encountered at the design and analysis stages of cardiovascular outcome trials (CVOTs). We discuss statistical challenges and strategies for testing multiple endpoints, populations, and doses; choosing an event window; addressing premarketing and post-marketing requirements for CV events with group-sequential and adaptive designs; designing a CVOT for noninferiority and superiority testing; assessing effects in subgroups; and evaluating patient's retention and missing data challenges.