An enhanced three-stage design with trend analysis for allergen immunotherapy trials.

We previously introduced a three-stage design and associated end-of-stage analyses for allergen immunotherapy (AIT) trials. End-of-stage differences alone may not provide a fuller picture of Stages 2 and 3 effects because they may depend upon stage-specific durations. Therefore, we introduce an additional trend analysis to evaluate the difference in progression curves of two groups over the entire stage. Results from such analysis are used to inform persistence of end-of-stage benefit and thus provide evidence for stagewise effects beyond the study periods. We jointly apply end-of-stage and trend analyses to support the enhanced three-stage design to determine treatment response over time and sustained response to AIT. A simulation study was performed to illustrate the statistical properties (bias and power) of trend analyses under varying statistical missing mechanisms and effect sizes. The extent of bias depended on the missing mechanism and magnitude. Powers were largely driven by effect and sample sizes as well as pre-specified success margins, particularly of relative trend. As an illustration, assuming relative treatment differences of 25-30%, stagewise dropout rate of 15%, and parallel outcome progressions, a sample size of 200 per group may achieve 97% power to demonstrate a treatment effect and 53% power to demonstrate a sustained effect post-treatment. Trend analysis supplements the end-of-stage analysis to enhance the statistical claims of stagewise effects. Inferential statistics support our proposed trend analysis for evaluating benefits of AIT over time and inform clinical understanding and decisions.

Conditional power in vaccine trials with seasonal variations.

Conditional power (CP) is widely used in clinical trial monitoring to quantify the evidence for futility stopping or sample size adaptation during the trial. When planning an interim analysis in vaccine trials for seasonal infectious diseases, CPs calculated under the hypothesized or currently estimated effect sizes may not truly reflect future data due to seasonal variations in disease incidence and/or vaccine efficacy (VE). Relying on these estimates alone could lead to erroneous decisions. Therefore, we carried out simulation studies to investigate the use of seven different choices for the drift parameter in computing CP or predictive power (PP) in end-of-season interim analysis. Our simulations showed that, when used to inform futility stopping, CP under the hypothesized effect and a weighted PP under a normal prior distribution appear to outperform others in terms of the overall type II error rate. All CPs and PPs considered in this study resulted in comparable powers and expected sample sizes when used to inform sample size adaptation. The performance of either CP or PP largely depends on the extent to which the chosen drift parameter or the prior distribution of the drift parameter matches the remainder of the trial. Weighted CP/PP tends to be less sensitive to settings where observed data and emerging data in future seasons differ substantially as they incorporate both current estimate and future variations. Therefore, weighted strategies deserve further exploration and perhaps increased usage in guiding trial operations because they are more robust to inaccuracies in prediction. In summary, for vaccine trials with seasonal variations, a decision on trial operations should be guided by a careful consideration of plausible CPs and PPs calculated under reasonable assumptions leveraging the data, prior hypotheses, and new evidence on clinical relevance.

A three-stage design for allergen immunotherapy trials.

BACKGROUND: Clinical trials of allergen immunotherapy (AIT) may require up to 5 years to complete. These lengthy trials may be complicated by high and potentially differential dropouts, especially among participants who perceive that they are receiving placebo. We propose a three-stage design in which the placebo group in Stage 1 crosses over to receive active treatment in Stage 2. In Stage 3, AIT is discontinued to determine whether benefit is maintained post-treatment. We apply inferential statistics to support the three-stage design for clinical trials to determine clinical efficacy, treatment response over time, and sustained response to AIT. METHODS: The proposed framework constitutes a series of hypothesis tests for comparing treatment responses at the end of each stage. A simulation study was performed to illustrate the statistical properties under varying statistical missing mechanisms and effect sizes. RESULTS: The statistical properties in terms of bias and statistical power were consistent with what are expected from conventional analyses. Specifically, the extent of bias depended on the missing mechanism and magnitude. The statistical powers were largely driven by effect and sample sizes as well as prespecified success margins. As an illustration, assuming relative treatment differences of 25% and stagewise dropout rate of 15%, a sample size of 200 per group may achieve 93% power to demonstrate a treatment effect and 60% power to demonstrate a maintained response post-treatment. CONCLUSIONS: Inferential statistics support our proposed study design for evaluating benefits of AIT over time and inform clinical understanding and decisions.

Statistical characteristics of moxifloxacin-induced QTc effect.

Moxifloxacin has been the most commonly used positive control in "thorough" QTc (TQT) studies. In a TQT study, the assay sensitivity is often considered to be established if the baseline corrected mean difference in QTc between moxifloxacin and placebo is greater than 5 ms in common practice at one or more prespecified time points and the observed moxifloxacin induced QTc effect over time follows the proper pharmacokinetics profile. To better understand the statistical characteristics of moxifloxacin-induced QTc prolongation and to provide guidance for future studies, 20 TQT studies that involved moxifloxacin have been evaluated. We study the QTc profile of the baseline adjusted mean difference in QTc between moxifloxacin and placebo over time. Zhang (2008) proposed that the moxifloxacin induced QTc effect can be evaluated between 1 and 4 h after a single dose (400 mg) administration near the time (T(max)) of peak concentration instead of all time points (typically 9-12 time points) at which QT was measured for the study drug evaluation. After evaluating 20 TQT studies, we confirm that the maximum moxifloxacin effect occurs in the time window between 1 and 4 h post dose. We also investigate the variability of the data as well as correlations between time points and between regimens. These findings and results can be used as a reference for future studies.

Multiple comparisons of repeatedly measured response: issues of validation testing in thorough QT/QTc clinical trials.

In order to validate the results of a thorough QT/QTc clinical trial, ICH E14 recommended that a concurrent positive control treatment be included in the trial. Zhang (2008) recommended that the study results are validated if the positive control establishes assay sensitivity, i.e., has an effect on the mean QT/QTc interval of 5 ms or more. Zhang (2008) and Tsong et al. (2008) discussed the intersection-union test approach and an alternative global average test approach for testing assay sensitivity during the validation process. In this article, we further discuss the multiple comparison issues of the repeatedly measured QT difference between positive control treatment and placebo in the validation test. We describe and discuss several approaches for type I error rate adjustment that are applicable to the situation.

Two-stage group sequential robust tests in family-based association studies: controlling type I error.

In family-based association studies, an optimal test statistic with asymptotic normal distribution is available when the underlying genetic model is known (e.g., recessive, additive, multiplicative, or dominant). In practice, however, genetic models for many complex diseases are usually unknown. Using a single test statistic optimal for one genetic model may lose substantial power when the model is mis-specified. When a family of genetic models is scientifically plausible, the maximum of several tests, each optimal for a specific genetic model, is robust against the model mis-specification. This robust test is preferred over a single optimal test. Recently, cost-effective group sequential approaches have been introduced to genetic studies. The group sequential approach allows interim analyses and has been applied to many test statistics, but not to the maximum statistic. When the group sequential method is applied, type I error should be controlled. We propose and compare several approaches of controlling type I error rates when group sequential analysis is conducted with the maximum test for family-based candidate-gene association studies. For a two-stage group sequential robust procedure with a single interim analysis, two critical values for the maximum tests are provided based on a given alpha spending function to control the desired overall type I error.

Clinical and immunologic responses to multiple doses of IMVAMUNE (Modified Vaccinia Ankara) followed by Dryvax challenge.

Smallpox vaccination with replication deficient vaccinia strains such as Modified Vaccinia Ankara (MVA) may induce protective immunity with improved safety and tolerability profiles compared with currently available smallpox vaccines. Ninety subjects were randomized equally to six groups in a partially blinded, randomized, controlled clinical trial. IMVAMUNE (MVA-BN, Bavarian Nordic A/S, Kvistgård, Denmark) vaccine or placebo was administered at Study Days 0 and 28 by subcutaneous or intramuscular injection and five groups were challenged with Dryvax at study Day 112. Vaccination with two doses of IMVAMUNE was safe and well tolerated compared to Dryvax. IMVAMUNE produced comparable cellular and humoral immune responses to one dose of Dryvax and the immunity induced appears robust 90 days post-vaccination by evidence of attenuated primary cutaneous reaction responses following Dryvax. IMVAMUNE vaccination prior to Dryvax reduced virus replication at the Dryvax site, decreased the size of the primary cutaneous lesion, and decreased the time to healing but did not completely ameliorate the immune response.