A generalized p-value approach for assessing noninferiority in a three-arm trial.

The existing generalized p-value approach, from statistical literature, is applied to assess noninferiority of an experimental treatment in a three-arm clinical trial including a placebo. Two generalized test functions (GTFs) are constructed and Monte Carlo simulations are used to compute the p-value. The GTFs perform well in terms of maintaining the Type-I error probabilities, and the power of the tests are shown to increase to 1 as both the sample size and the parameter denoting the fraction of the effect of the reference drug with respect to placebo increase. The generalized confidence intervals are shown to retain the coverage probabilities. A published dataset is re-analysed using the proposed test and the results are in agreement with earlier findings.

Bayesian approach to noninferiority trials for proportions.

Noninferiority trials are unique because they are dependent upon historical information in order to make meaningful interpretation of their results. Hence, a direct application of the Bayesian paradigm in sequential learning becomes apparently useful in the analysis. This paper describes a Bayesian procedure for testing noninferiority in two-arm studies with a binary primary endpoint that allows the incorporation of historical data on an active control via the use of informative priors. In particular, the posteriors of the response in historical trials are assumed as priors for its corresponding parameters in the current trial, where that treatment serves as the active control. The Bayesian procedure includes a fully Bayesian method and two normal approximation methods on the prior and/or on the posterior distributions. Then a common Bayesian decision criterion is used but with two prespecified cutoff levels, one for the approximation methods and the other for the fully Bayesian method, to determine whether the experimental treatment is noninferior to the active control. This criterion is evaluated and compared with the frequentist method using simulation studies in keeping with regulatory framework that new methods must protect type I error and arrive at a similar conclusion with existing standard strategies. Results show that both methods arrive at comparable conclusions of noninferiority when applied to a modified real data set. The advantage of the proposed Bayesian approach lies in its ability to provide posterior probabilities for effect sizes of the experimental treatment over the active control.

Anterior cingulate activity correlates with blood pressure during stress.

The anterior cingulate cortex presumptively regulates blood pressure reactions to behavioral stressors. There is little evidence in humans, however, that stressor-evoked changes in blood pressure correlate with concurrent changes in anterior cingulate activity. Using fMRI, we tested whether changes in mean arterial blood pressure correlate with ongoing changes in blood oxygen level dependent (BOLD) activation in 9 women and 11 men who completed a stressful Stroop color-word interference task. Higher mean arterial pressure during the Stroop task correlated with greater BOLD activation in two regions of the cingulate cortex (perigenual and mid-anterior) and in other networked brain regions, including the insula, thalamus, and periaqueductal gray. These results support the hypothesis that the anterior cingulate cortex regulates blood pressure reactions to behavioral stressors in humans.

Comparing extent of activation: a robust permutation approach.

The number of contiguous voxels activated in a brain image can differ between groups or conditions even though the amplitude of activation does not markedly differ. Existing techniques test for differences in amplitude given that extent (number of contiguous voxels) exceeds some threshold. We present a technique that tests for differences in extent of activation given that amplitude of activation exceeds some threshold. The technique was motivated by apparent differences in extent of regional cerebral blood flow (rCBF) between hypertensive and normotensive participants performing cognitive tasks. These data are used to illustrate our test for extent of activation. We threshold the estimated parameter map for each subject, count the number of voxels exceeding the threshold over a defined region enclosing activated cortical area, and test the hypothesis of difference in the number of activated voxels between the two groups. Due to the large number of zeros resulting from the thresholding and the occurrence of extreme observations, we use a Robust permutation test [Lambert, D., 1985. Robust two-sample permutation tests. Ann. Stat., 13, 606-625], which is based on the sum of censored log-likelihood ratios. This statistic has desirable properties relative to the usual permutation test in contaminated distributions, i.e., idealized histogram with outliers, and provides an appropriate and robust test of extent of activation between conditions or groups.