The potential for increased power from combining P-values testing the same hypothesis.

The conventional approach to hypothesis testing for formal inference is to prespecify a single test statistic thought to be optimal. However, we usually have more than one test statistic in mind for testing the null hypothesis of no treatment effect but we do not know which one is the most powerful. Rather than relying on a single p-value, combining p-values from prespecified multiple test statistics can be used for inference.

Robust inference from multiple test statistics via permutations: a better alternative to the single test statistic approach for randomized trials.

Formal inference in randomized clinical trials is based on controlling the type I error rate associated with a single pre-specified statistic. The deficiency of using just one method of analysis is that it depends on assumptions that may not be met. For robust inference, we propose pre-specifying multiple test statistics and relying on the minimum p-value for testing the null hypothesis of no treatment effect.

Projecting adverse event incidence rates using empirical Bayes methodology.

Although there is considerable interest in adverse events observed in clinical trials, projecting adverse event incidence rates in an extended period can be of interest when the trial duration is limited compared to clinical practice. A naïve method for making projections might involve modeling the observed rates into the future for each adverse event. However, such an approach overlooks the information that can be borrowed across all the adverse event data.

Assessing Similarity to Existing Drugs to Decide Whether to Continue Drug Development.

Developing a drug requires large investments, over many years, with dramatic increases in development costs at later stages. Thus, one wants to make a No Go decision on a compound early, unless evidence continues to suggest that the project will ultimately be successful, so that resources can be focused on the most promising compounds to benefit patients. Instead of predicting the probability of success of a Phase III study, our approach to this decision uses the Phase II study results to assess similarity of the novel compound to existing drugs that are classified by different decision categories, such as a clear Go decision (e.

Addition of the neurokinin 1 receptor antagonist aprepitant to standard antiemetic therapy improves control of chemotherapy-induced nausea and vomiting. Results from a randomized, double-blind, placebo-controlled trial in Latin America.

Background: Aprepitant is a novel neurokinin 1 (NK(1)) antagonist that has been shown to improve control of chemotherapy-induced nausea and vomiting (CINV) when added to a standard antiemetic regimen of a 5-hydroxytriptamine-3 antagonist plus a corticosteroid. The authors sought to evaluate further the efficacy and tolerability of aprepitant plus standard therapy in a large clinical trial.

Methods: This was a multicenter, randomized, double-blind, placebo-controlled, parallel-groups, Phase III study.

Atypical depression: enhanced right hemispheric dominance for perceiving emotional chimeric faces.

Two studies compared hemispatial bias for perceiving chimeric faces in patients having either atypical or typical depression and healthy controls. A total of 245 patients having major depressive disorder (MDD) or dysthymia (164 with atypical features) and 115 controls were tested on the Chimeric Faces Test. Atypical depression differed from typical depression and controls in showing abnormally large right hemisphere bias.