Objectives: An increasing number of abandoned clinical trials have forestalled efforts to advance the evidence base for the treatment of mood and anxiety disorders in children and adolescents. With this in mind, we sought to present and validate a Bayesian approach for the reanalysis of summary data in abandoned clinical trials and to review and re-evaluate available pharmacokinetic, tolerability, and efficacy data from two large, randomized controlled trials of buspirone in pediatric patients with generalized anxiety disorder (GAD).

Methods: Prospective, randomized, parallel-group controlled trials of buspirone in pediatric patients with GAD as well as associated pharmacokinetic studies were identified and data were extracted. In addition to descriptive statistics, marginal posterior densities for each variable of interest were determined and a Monte Carlo pseudosample was generated with random draws obtained from the Student's t-distribution to assess, with inferential statistics, differences in variables of interest.

Results: Buspirone was evaluated in one flexibly dosed (N = 227) and one fixed-dose (N = 341) trial in children and adolescents aged 6-17 years with a primary diagnosis of GAD. With regard to improvement in the sum of the Columbia Schedule for Affective Disorders and Schizophrenia GAD items, buspirone did not separate from placebo in the fixed-dose trial at low (95% CI: -0.78 to 2.39, p = 0.32) or high dose (95% CI: -0.87 to 1.87, p = 0.47) nor did it separate from placebo in the flexibly dosed study (95% CI: -0.3 to 1.9, p = 0.15). Drop out as a result of a treatment-emergent adverse event was significantly greater in buspirone-treated patients compared to placebo (p = 0.011). Side effects were consistent with the known profile of buspirone with lightheadedness occurring more frequently in buspirone-treated patients (p < 0.001).

Conclusions: Buspirone is well tolerated in pediatric patients with GAD, although two randomized controlled trials were underpowered to detect small effect sizes (Cohen's d < 0.15). Finally, Bayesian approaches may facilitate re-examination of data from abandoned clinical trials.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5771537PMC
http://dx.doi.org/10.1089/cap.2017.0060DOI Listing

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