A structured framework for adaptively incorporating external evidence in sequentially monitored clinical trials.

We present a Bayesian framework for sequential monitoring that allows for use of external data, and that can be applied in a wide range of clinical trial applications. The basis for this framework is the idea that, in many cases, specification of priors used for sequential monitoring and the stopping criteria can be semi-algorithmic byproducts of the trial hypotheses and relevant external data, simplifying the process of prior elicitation. Monitoring priors are defined using the family of generalized normal distributions, which comprise a flexible class of priors, naturally allowing one to construct a prior that is peaked or flat about the parameter values thought to be most likely. External data are incorporated into the monitoring process through mixing an a priori skeptical prior with an enthusiastic prior using a weight that can be fixed or adaptively estimated. In particular, we introduce an adaptive monitoring prior for efficacy evaluation that dynamically weighs skeptical and enthusiastic prior components based on the degree to which observed data are consistent with an enthusiastic perspective. The proposed approach allows for prospective and pre-specified use of external data in the monitoring procedure. We illustrate the method for both single-arm and two-arm randomized controlled trials. For the latter case, we also include a retrospective analysis of actual trial data using the proposed adaptive sequential monitoring procedure. Both examples are motivated by completed pediatric trials, and the designs incorporate information from adult trials to varying degrees. Preposterior analysis and frequentist operating characteristics of each trial design are discussed.

No association of abacavir use with myocardial infarction: findings of an FDA meta-analysis.

BACKGROUND: Several studies have reported an association between abacavir (ABC) exposure and increased risk of myocardial infarction (MI) among HIV-infected individuals. Randomized controlled trials (RCTs) and a pooled analysis by GlaxoSmithKline, however, do not support this association. To better estimate the effect of ABC use on risk of MI, the US Food and Drug Administration (FDA) conducted a trial-level meta-analysis of RCTs in which ABC use was randomized as part of a combined antiretroviral regimen. METHODS: From a literature search conducted among 4 databases, 26 RCTs were selected that met the following criteria: conducted in adults, sample size more than 50 subjects, status completed, not a pharmacokinetic trial, and not conducted in Africa. The Mantel-Haenszel method, with risk difference and 95% confidence interval, was used for the primary analysis, along with additional alternative analyses, based on FDA-requested adverse event reports of MI provided by each investigator. RESULTS: The 26 RCTs were conducted from 1996 to 2010, and included 9868 subjects (5028 ABC and 4840 non-ABC). Mean follow-up was 1.43 person-years in the ABC group and 1.49 person-years in the non-ABC group. Forty-six (0.47%) MI events were reported [24 (0.48%) ABC and 22 (0.46%) non-ABC], with no significant difference noted between the 2 groups (risk difference of 0.008% with 95% confidence interval: -0.26% to 0.27%). CONCLUSIONS: To the best of our knowledge, our study represents the largest trial-level meta-analysis to date of clinical trials in which ABC use was randomized. Our analysis found no association between ABC use and MI risk.