Gregory G. Enas

Absence of a relationship between adverse events and suicidality during pharmacotherapy for depression

This study tested the hypothesis that some patients treated with an antidepressant who develop adverse events (e.g., activation, akathisia) experience emergent suicidality specifically associated with such events. Seventeen double-blind, controlled clinical trials conducted in the United States and Canada with 3,065 patients with major depression were evaluated for treatment-emergent adverse events (events that first occurred or worsened during therapy) and suicidality (a suicidal act or emergence of substantial suicidal ideation or both) with fluoxetine, placebo, and tricyclic antidepressants. Nine relevant adverse event clusters were evaluated: activation, sedation, activation and sedation, decreased libido, mania, psychosis, psychosis and mania, acute brain syndrome, and violence. Incidence rates were determined for suicidality that was and was not temporally associated with an adverse event cluster and were analyzed within and across treatments (incidence difference method). Most patients experienced neither a cluster event nor suicidality. Where suicidality was reported, it generally was not in temporal association with an adverse event cluster. In no cluster was the incidence of suicidality statistically significantly higher when reported in temporal association with an event than when not. Suicidality was associated infrequently with treatment-emergent activation and at comparable rates across treatments. No increased risk of suicidality associated with an adverse event cluster was observed between the treatment groups (fluoxetine versus tricyclic anti-depressants; fluoxetine versus placebo). These results from double-blind, placebo- and comparator-controlled fluoxetine clinical trials in patients with major depression do not suggest a relationship between a treatment-emergent adverse event pattern and suicidality in this population.

Baseline Comparability in Clinical Trials: Prevention of “Poststudy Anxiety”

“PostStudy Anxiety” syndrome is our term for the feeling of ill-being at the end of a randomized clinical trial upon finding that the randomized groups differ to a disquieting degree with respect to one or more baseline characteristics. We discuss the meaning of such differences and argue that they are inevitable, not necessarily damaging the credibility of the study. We present an argument that “checking” the randomization is not a legitimate use of data collected at baseline. Further, we will present suggestions for steps that can be taken at the experimental design stage for dealing with important prognostic variables, whether unbalanced at baseline or note.

Making Decisions about Safety in Clinical Trials — The Case for Inferential Statistics

While not required for every adverse event, inferential statistical methods can be used both formally and informally to help characterize the safety profile of a new drug and help guide the resulting inferences to the broader population. Examples of probability statements will be shown when used both formally and informally. The particular setting or phase of clinical drug development dictates to some degree whether description with or without formal inference is appropriate.

10 Years with ICH E10: Choice of Control Groups.

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Substantial Evidence From a Replicated Secondary Analysis, Followed by a Single Prospective Confirmatory Study

In the context of a New Drug Application in the United States, the term “substantial evidence” of clinical efficacy is usually understood to mean two well-controlled confirmatory studies in which a statistically significant difference is shown on the primary endpoint(s) in both studies. We examine whether this usual understanding can be safely extended to include data packages based on other combinations of studies. For instance, it is not uncommon in drug development for two simultaneous phase 3 confirmatory studies to be designed on basis of limited phase 2 data and then for those studies to fail to show a statistically significant difference on the primary endpoint, but there is a difference seen in both studies on a secondary endpoint or in a particular subgroup. The standard paradigm would suggest that this “finding” would need to be replicated in two further confirmatory studies with the revised endpoint/study population as primary. However, given the evidence from the original two studies, replication of this “finding” in just one further study may provide “substantial evidence” for the purposes of registering an efficacy claim. We examine this and other similar scenarios in terms of whether accepting such registration packages by the Food and Drug Administration would inflate the statistical risk of accepting a false efficacy claim.

A simple stopping rule for declaring treatment ineffectiveness in clinical trials

We consider the problem of stopping a clinical trial before its scheduled termination due to the apparent ineffectiveness of the experimental therapy, as compared with a control. We propose a simple-to-implement, intuitive decision rule based on the unadjusted attained significance levels from any appropriate statistical test. The proposed procedure may be used at any time during the study as an aid to help determine whether the study of an experimental treatment should be terminated early with the conclusion of treatment ineffectiveness. Much of the power of the usual fixed-sample test is retained while maintaining the nominal test size.