Blinded sample size recalculation for clinical trials with normal data and baseline adjusted analysis

Baseline adjusted analyses are commonly encountered in practice, and regulatory guidelines endorse this practice. Sample size calculations for this kind of analyses require knowledge of the magnitude of nuisance parameters that are usually not given when the results of clinical trials are reported in the literature. It is therefore quite natural to start with a preliminary calculated sample size based on the sparse information available in the planning phase and to re‐estimate the value of the nuisance parameters (and with it the sample size) when a portion of the planned number of patients have completed the study. We investigate the characteristics of this internal pilot study design when an analysis of covariance with normally distributed outcome and one random covariate is applied. For this purpose we first assess the accuracy of four approximate sample size formulae within the fixed sample size design. Then the performance of the recalculation procedure with respect to its actual Type I error rate and power characteristics is examined. The results of simulation studies show that this approach has favorable properties with respect to the Type I error rate and power. Together with its simplicity, these features should make it attractive for practical application. Copyright © 2009 John Wiley & Sons, Ltd.     

The potential for bias in reporting of industry-sponsored clinical trials

Concerns about potentially misleading reporting of pharmaceutical industry research have surfaced many times. The potential for duality (and thereby conflict) of interest is only too clear when you consider the sums of money required for the discovery, development and commercialization of new medicines. As the ability of major, mid-size and small pharmaceutical companies to innovate has waned, as evidenced by the seemingly relentless decline in the numbers of new medicines approved by Food and Drug Administration and European Medicines Agency year-on-year, not only has the cost per new approved medicine risen: so too has the public and media concern about the extent to which the pharmaceutical industry is open and honest about the efficacy, safety and quality of the drugs we manufacture and sell. In 2005 an Editorial in Journal of the American Medical Association made clear that, so great was their concern about misleading reporting of industry-sponsored studies, henceforth no article would be published that was not also guaranteed by independent statistical analysis. We examine the precursors to this Editorial, as well as its immediate and lasting effects for statisticians, for the manner in which statistical analysis is carried out, and for the industry more generally.     

Evaluation of single and mixed verbal operant arrangements for teaching mands and tacts

The purpose of this series of experiments was to evaluate the effects of mixed mand-tact arrangements on the acquisition of mands and tacts in preschool-aged children. In Experiment 1, the effects of three training arrangements (mand-only training, tact-only training, and mand-tact training) were investigated with 3 typically developing children. Rates of acquisition in single (mand-only and tact-only) versus mixed (mand-tact) presentation were comparable, in contrast to earlier investigations. Experiment 2 attempted to clarify the equivocal findings of Experiment 1 by directly replicating the Carroll and Hesse (1987) investigation with 2 typically developing children. Results again demonstrated no clear benefit of mixed verbal operant training on tact acquisition. In Experiment 3, these same arrangements were evaluated with a boy with autism and included assessments to determine that a relevant establishing operation was in effect prior to each mand training session. Experiment 3 again failed to demonstrate the facilitative effects of mand-tact training on the acquisition of mands or tacts. Taken together, the data from these three experiments fail to support the improved efficiency of mand-tact training suggested by prior studies. Findings are discussed in the context of future research investigating mixed verbal operant arrangements.     

Adaptive Percolation Using Subjective Likelihoods

A phenomenon that I call “adaptive percolation” commonly arises in biology, business, economics, defense, finance, manufacturing, and the social sciences. Here one wishes to select a handful of entities from a large pool of entities via a process of screening through a hierarchy of sieves. The process is not unlike the percolation of a liquid through a porous medium. The probability model developed here is based on a nested and adaptive Bayesian approach that results in the product of beta-binomial distributions with common parameters. The common parameters happen to be the observed data. I call this the percolated beta-binomial distribution . The model turns out to be a slight generalization of the probabilistic model used in percolation theory. The generalization is a consequence of using a subjectively specified likelihood function to construct a probability model. The notion of using likelihoods for constructing probability models is not a part of the conventional toolkit of applied probabilists. To the best of my knowledge, a use of the product of beta-binomial distributions as a probability model for Bernoulli trials appears to be new. The development of the material of this article is illustrated via data from the 2009 astronaut selection program, which motivated this work.     

Statistical considerations associated with a comprehensive regulatory framework to address the unmet need for new antibacterial therapies

At present, there are situations in antibiotic drug development where the low number of enrollable patients with key problem pathogens makes it impossible to conduct fully powered non‐inferiority trials in the traditional way. Recent regulatory changes have begun to address this situation. In parallel, statistical issues regarding the application of alternative techniques, balancing the unmet need with the level of certainty in the approval process, and the use of additional sources of data are critical areas to increase development feasibility. Although such approaches increase uncertainty compared with a traditional development program, this will be necessary to allow new agents to be made available. Identification of these risks and explicit discussion around requirements in these areas should help clarify the situation, and hence, the feasibility of developing drugs to treat the most concerning pathogens before the unmet need becomes even more acute than at present. Copyright © 2014 John Wiley & Sons, Ltd.     

The cross-product ratio in bivariate lognormal and gamma distributions,with an application to non-randomized trials

Non-randomized trials can give a biased impression of the effectiveness of any intervention. We consider trials in which incidence rates are compared in two areas over two periods. Typically, one area receives an intervention, whereas the other does not. We outline and illustrate a method to estimate the bias in such trials under two different bivariate models. The illustrations use data in which no particular intervention is operating. The purpose is to illustrate the size of the bias that could be observed purely due to regression towards the mean (RTM). The illustrations show that the bias can be appreciably different from zero, and even when centred on zero, the variance of the bias can be large. We conclude that the results of non-randomized trials should be treated with caution, as interventions which show small effects could be explained as artefacts of RTM.     

Design and analysis considerations for comparing dynamic treatment regimens with binary outcomes from sequential multiple assignment randomized trials

In behavioral, educational and medical practice, interventions are often personalized over time using strategies that are based on individual behaviors and characteristics and changes in symptoms, severity, or adherence that are a result of one's treatment. Such strategies that more closely mimic real practice, are known as dynamic treatment regimens (DTRs). A sequential multiple assignment randomized trial (SMART) is a multi-stage trial design that can be used to construct effective DTRs. This article reviews a simple to use ‘weighted and replicated’ estimation technique for comparing DTRs embedded in a SMART design using logistic regression for a binary, end-of-study outcome variable. Based on a Wald test that compares two embedded DTRs of interest from the ‘weighted and replicated’ regression model, a sample size calculation is presented with a corresponding user-friendly applet to aid in the process of designing a SMART. The analytic models and sample size calculations are presented for three of the more commonly used two-stage SMART designs. Simulations for the sample size calculation show the empirical power reaches expected levels. A data analysis example with corresponding code is presented in the appendix using data from a SMART developing an effective DTR in autism.     

Distributions of statistics describing concentration of runs in non homogeneous Markov-dependent trials

In the first n, n ? 3, trials of a non homogeneous zero-one Markov chain of first order, we consider runs of ones of length exceeding a threshold. The article deals with statistics denoting, the length and the position of the shortest segment of the chain in which all such runs of ones are concentrated. The study provides recursive schemes for conditional distributions of these statistics. Numerical examples illustrate the theoretical results.     

Two-stage phase II trials with early stopping for effectiveness and safety as well as ineffectiveness or harm

This article proposes new optimal and minimax designs, which allow early stopping not only for ineffectiveness or toxicity but also for sufficient effectiveness and safety. These designs may facilitate effective drug development by detecting sufficient effectiveness and safety at an early stage or by detecting ineffectiveness or excessive toxicity at an early stage. The proposed design has advantage over other designs in the sense that it can control the type I error rate and is robust against the real association parameter. Comparing to Jin's design, it is always advantageous in terms of expected sample size.     

Are Private Interests Clouding the Peer-Review Process of the WHO Bulletin? A Case Study

Readers’ trust on the medical literature has been eroded, and journal editors and some editorial boards are taking measures to ensure that authors fully and accurately report research findings and disclose conflicts of interest. This article describes a case study in which the papers editor of the World Health Organization (WHO) Bulletin influenced the content of an article that had been approved by the external reviewers. The editor objected to the publication of the large price differentials of the new molecular entities (NMEs) across the Latin American countries where they had been tested and the limited added therapeutic value of the NMEs that had been assessed by independent drug bulletins. This article summarizes the exchanges with WHO staff and posits the hypothesis that the WHO Bulletin might be affected by the shifts in WHO financing. Several authors have raised concern about the impact of financial conflicts of interest in WHO activities in the field of nutrition, intellectual property, and in the emergency response to the flu pandemic. Moreover, it has been reported that powerful WHO contributors pressured WHO into revising its publication policy. This is the first time that authors question if these conflicts of interest are also affecting the editorial independence of the WHO Bulletin.