BackgroundGSK2190915 is a high affinity 5-lipoxygenase-activating protein inhibitor being developed for the treatment of asthma. The objective of this study was to evaluate GSK2190915 efficacy, dose–response and safety in subjects with persistent asthma treated with short-acting beta2-agonists (SABAs) only.MethodsEight-week multicentre, randomised, double-blind, double-dummy, stratified (by age and smoking status), parallel-group, placebo-controlled study in subjects aged ≥12 years with a forced expiratory volume in 1 second (FEV1) of 50–85% predicted. Subjects (n = 700) were randomised to receive once-daily (QD) oral GSK2190915 (10–300 mg), twice-daily inhaled fluticasone propionate 100 μg, oral montelukast 10 mg QD or placebo. The primary endpoint was mean change from baseline (randomisation) in trough (morning pre-dose and pre-rescue bronchodilator) FEV1 at the end of the 8-week treatment period. Secondary endpoints included morning and evening peak expiratory flow, symptom-free days and nights, rescue-free days and nights, day and night-time symptom scores, day and night-time rescue medication use, withdrawals due to lack of efficacy, Asthma Control Questionnaire and Asthma Quality of Life Questionnaire scores.ResultsFor the primary endpoint, there was no statistically significant difference between any dose of GSK2190915 QD and placebo. However, repeated measures sensitivity analysis demonstrated nominal statistical significance for GSK2190915 30 mg QD compared with placebo (mean difference: 0.115 L [95% confidence interval: 0.00, 0.23], p = 0.044); no nominally statistically significant differences were observed with any of the other doses. For the secondary endpoints, decreases were observed in day-time symptom scores and day-time SABA use for GSK2190915 30 mg QD versus placebo (p ≤ 0.05). No dose–response relationship was observed for the primary and secondary endpoints across the GSK2190915 dose range studied; the 10 mg dose appeared to be sub-optimal. GSK2190915 was associated with a dose-dependent reduction in urinary leukotriene E4. The profile and incidence of adverse events were similar between treatment groups.ConclusionEfficacy was demonstrated for GSK2190915 30 mg compared with placebo in day-time symptom scores and day-time SABA use. No additional improvement on efficacy endpoints was gained by administration of GSK2190915 doses greater than 30 mg. GSK2190915 was well-tolerated. These results may support further studies with GSK2190915 30 mg.Trial registrationClinicaltrials.gov: NCT01147744.

We consider intersection-union tests involving multiple endpoints in a combination drug trial, for which we control the familywise error rate in the strong sense using closed testing methods. Bonferroni-Holm, Simes-Hommel, and Resampling-Based methods all are considered in this context. Familywise error rate control heuristics are developed and evaluated using a simulation study that is specifically tailored to the intersection-union setting. Both Resampling-Based and Simes-Hommel uniformly outperform the Bonferroni-Holm. Using simulations of power, the choice of Simes-Hommel versus Resampling-Based is seen to depend on the particular alternative of interest. Because it is simpler and has generally good power, we recommend the Simes-Hommel intersection-union tests. The techniques are illustrated using real data from a clinical trial to evaluate a combination asthma therapy.

A well designed clinical trial requires an appropriate sample size with adequate statistical power to address trial objectives. The statistical power is traditionally defined as the probability of rejecting the null hypothesis with a pre-specified true clinical treatment effect. This power is a conditional probability conditioned on the true but actually unknown effect. In practice, however, this true effect is never a fixed value. Thus we discuss a newly proposed alternative to this conventional statistical power: statistical assurance, defined as the unconditional probability of rejecting the null hypothesis. This kind of assurance can then be obtained as an expected power where the expectation is based on the prior probability distribution of the unknown treatment effect, which leads to the Bayesian paradigm. In this paper, we outline the transition from conventional statistical power to the newly developed assurance and discuss the computations of assurance using Monte-Carlo simulation-based approach.

Clinicaltrials.gov identifiers: NCT01156792 and NCT01248975.