Most statistical methodology for phase III clinical trials focuses on the comparison of a single experimental treatment with a control. An increasing desire to reduce the time before regulatory approval of a new drug is sought has led to development of two-stage or sequential designs for trials that combine the definitive analysis associated with phase III with the treatment selection element of a phase II study. In this paper we consider a trial in which the most promising of a number of experimental treatments is selected at the first interim analysis. This considerably reduces the computational load associated with the construction of stopping boundaries compared to the approach proposed by Follman, Proschan and Geller (Biometrics 1994; 50: 325-336). The computational requirement does not exceed that for the sequential comparison of a single experimental treatment with a control. Existing methods are extended in two ways. First, the use of the efficient score as a test statistic makes the analysis of binary, normal or failure-time data, as well as adjustment for covariates or stratification straightforward. Second, the question of trial power is also considered, enabling the determination of sample size required to give specified power.

Substitution of 9.5-9.6%TE dietary SFAs with either MUFAs or n-6 PUFAs did not significantly affect the percentage of flow-mediated dilatation or other measures of vascular function. However, the beneficial effects on serum lipid biomarkers, blood pressure, and E-selectin offer a potential public health strategy for CVD risk reduction. This trial was registered at www.clinicaltrials.gov as NCT01478958.

In this paper, data obtained between 1984 and 1993 from 11,629 men and women as part of the Scottish Heart Health Study (Scotland, United Kingdom) were used to investigate the relation between antioxidant vitamin and fiber intakes and both incident coronary heart disease (CHD) (649 events) and all-causes mortality (591 deaths). All age-adjusted mean intakes tended to be higher in the group that experienced no event. For men, increased fiber intake was associated with decreased risk of CHD even after adjustment for a host of other major coronary risk factors; hazard ratios relative to the lowest quarter were 0.68, 0.70, and 0.64 by increasing quarter. This relation was also observed for mortality (hazard ratios of 0.62, 0.66, and 0.62). Evidence was found that higher intakes of the antioxidants were also beneficial, although the associations were weaker. For women, fiber was the only obviously influential dietary factor, with hazard ratios of 0.94, 0.60, and 0.56 for CHD and 1.25, 0.82, and 0.65 for mortality. These results suggest that the current public health drive to increase the consumption of foods rich in antioxidant vitamins and (particularly) fiber will impact on both CHD risk and the general health of the population.

In recent years adaptive seamless phase II/III designs (ASDs) allowing treatment or dose selection at an interim analysis have gained much attention because of their potential to save development costs and to shorten time-to-market of a new compound compared to conventional drug development programmes with separate trials for individual phases. In this paper, we describe an ASD with treatment selection based on early outcome data, specifically considering the situation where no final outcomes are observed at the time of the interim analysis. Bringing together combination tests for adaptive designs and the closure principle for multiple testing, control of the familywise type I error rate in the strong sense is achieved. Furthermore, a simulation model is proposed based on standardized test statistics that allows the generation of virtual trials for a variety of outcomes. We use this simulation model to investigate the actual type I error rate of the proposed testing procedure and find that the familywise type I error rate is controlled as expected. The method is often conservative, with the degree of conservatism depending on the correlation between early and late outcome, the true mean values of the early outcome in the different treatment groups and the selection rule. The investigations are motivated and illustrated by an application of the proposed design and simulation model to progressive multiple sclerosis.

Adaptive designs (ADs) allow pre-planned changes to an ongoing trial without compromising the validity of conclusions and it is essential to distinguish pre-planned from unplanned changes that may also occur. The reporting of ADs in randomised trials is inconsistent and needs improving. Incompletely reported AD randomised trials are difficult to reproduce and are hard to interpret and synthesise. This consequently hampers their ability to inform practice as well as future research and contributes to research waste. Better transparency and adequate reporting will enable the potential benefits of ADs to be realised.This extension to the Consolidated Standards Of Reporting Trials (CONSORT) 2010 statement was developed to enhance the reporting of randomised AD clinical trials. We developed an Adaptive designs CONSORT Extension (ACE) guideline through a two-stage Delphi process with input from multidisciplinary key stakeholders in clinical trials research in the public and private sectors from 21 countries, followed by a consensus meeting. Members of the CONSORT Group were involved during the development process.The paper presents the ACE checklists for AD randomised trial reports and abstracts, as well as an explanation with examples to aid the application of the guideline. The ACE checklist comprises seven new items, nine modified items, six unchanged items for which additional explanatory text clarifies further considerations for ADs, and 20 unchanged items not requiring further explanatory text. The ACE abstract checklist has one new item, one modified item, one unchanged item with additional explanatory text for ADs, and 15 unchanged items not requiring further explanatory text.The intention is to enhance transparency and improve reporting of AD randomised trials to improve the interpretability of their results and reproducibility of their methods, results and inference. We also hope indirectly to facilitate the much-needed knowledge transfer of innovative trial designs to maximise their potential benefits.