The Cytel blog keeps you up to speed with the latest developments in biostatistics and clinical biometrics.

Why You Should Construct Primary Endpoints Using Bayesian Methods: Lessons from COVID-19

June 18, 2020

One of the revelations of the COVID-19 pandemic is that the flexibility and potential of Bayesian designs goes far beyond the benefits connected to informed priors. Rather a number of other benefits to Bayesian designs are sometimes under-appreciated. The importance of using Bayesian methods to choose composite endpoints, for example, particularly in longitudinal studies, can be overlooked when considering Bayesian and Frequentist options.

Cytel statisticians reflected on these benefits during a recent panel discussion.

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A Cautionary Tale about Composite Endpoint Construction: The ARISE Trial

June 18, 2015

In August 2006 AstraZeneca completed the ARISE trial, which aimed to determine whether AGI-1067 was effective in reducing atherosclerosis in patients with acute coronary artery disease [1][2]. A double-blind, placebo controlled, Phase 3 trial, the primary efficacy endpoint was a composite endpoint which included major adverse cardiovascular events (MACE) like cardiovascular death, resuscitated cardiac arrest, non-fatal myocardial infarction and non-fatal stroke. However, it also included two less serious but more frequently observed events, namely hospitalization due to coronary revascularization and hospitalization due to unstable angina with evidence of ischemia [2]. 

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