Sequentially testing for a gene-drug interaction in a genomewide analysis

Assaying a large number of genetic markers from patients in clinical trials is now possible in order to tailor drugs with respect to efficacy. The statistical methodology for analysing such massive data sets is challenging. The most popular type of statistical analysis is to use a univariate test for each genetic marker, once all the data from a clinical study have been collected. This paper presents a sequential method for conducting an omnibus test for detecting gene-drug interactions across the genome, thus allowing informed decisions at the earliest opportunity and overcoming the multiple testing problems from conducting many univariate tests. We first propose an omnibus test for a fixed sample size. This test is based on combining F-statistics that test for an interaction between treatment and the individual single nucleotide polymorphism (SNP). As SNPs tend to be correlated, we use permutations to calculate a global p-value. We extend our omnibus test to the sequential case. In order to control the type I error rate, we propose a sequential method that uses permutations to obtain the stopping boundaries. The results of a simulation study show that the sequential permutation method is more powerful than alternative sequential methods that control the type I error rate, such as the inverse-normal method. The proposed method is flexible as we do not need to assume a mode of inheritance and can also adjust for confounding factors. An application to real clinical data illustrates that the method is computationally feasible for a large number of SNPs. Copyright (c) 2007 John Wiley & Sons, Ltd.

A comparison of three different models for estimating relative risk in meta-analysis of clinical trials under unobserved heterogeneity

We focus on the comparison of three statistical models used to estimate the treatment effect in metaanalysis when individually pooled data are available. The models are two conventional models, namely a multi-level and a model based upon an approximate likelihood, and a newly developed model, the profile likelihood model which might be viewed as an extension of the Mantel-Haenszel approach. To exemplify these methods, we use results from a meta-analysis of 22 trials to prevent respiratory tract infections. We show that by using the multi-level approach, in the case of baseline heterogeneity, the number of clusters or components is considerably over-estimated. The approximate and profile likelihood method showed nearly the same pattern for the treatment effect distribution. To provide more evidence two simulation studies are accomplished. The profile likelihood can be considered as a clear alternative to the approximate likelihood model. In the case of strong baseline heterogeneity, the profile likelihood method shows superior behaviour when compared with the multi-level model. Copyright (C) 2006 John Wiley & Sons, Ltd.

A 25-year review of sequential methodology in clinical studies

This paper explores the theoretical developments and subsequent uptake of sequential methodology in clinical studies in the 25 years since Statistics in Medicine was launched. The review examines the contributions which have been made to all four phases into which clinical trials are traditionally classified and highlights major statistical advancements, together with assessing application of the techniques. The vast majority of work has been in the setting of phase III clinical trials and so emphasis will be placed here. Finally, comments are given indicating how the subject area may develop in the future.

Differences in perceived risks and benefits of herbal, over-the-counter conventional, and prescribed conventional, medicines, and the implications of this for the safe and effective use of herbal products

Objectives: To investigate people's views about the efficacy and specific risks of herbal, over-the-counter (OTC) conventional, and prescribed conventional medicines, and their likelihood of taking a second (herbal or OTC conventional) product in addition to a prescribed medicine. Methods: Experiment 1 (1 factor within-participant design); Experiment 2 (1 factor between-participant design). Convenience samples of general population were given a hypothetical scenario and required to make a number of judgements. Results: People believed herbal remedies to be less effective, but less risky than OTC and prescribed conventional medicines. Herbal medicines were not seen as being safer simply because of their easier availability. Participants indicated that they would be more likely to take a herbal medicine than a conventional OTC medicine in addition to a prescribed medicine, and less likely to consult their doctor in advance. Conclusion: People believe that herbal medicines are natural and relatively safe and can be used with less caution. People need to be given clear information about the risks and benefits of herbal medicines if they are to use such products safety and effectively. (c) 2006 Elsevier Ltd. All rights reserved.

The benefits of providing benefit information: examining the effectiveness of provision of simple benefit statements on people's judgements about a medicine

Three experiments examined the effects of adding information about medication benefits to a short written explanation about a medicine. Participants were presented with a fictitious scenario about visiting the doctor, being prescribed an antibiotic and being given information about the medicine. They were asked to make various judgements relating to the information, the medicine and their intention to take it. Experiment 1 found that information about benefits enhanced the judgements, but did not influence the intention to comply. Experiment 2 compared the relative effectiveness of two different forms of the benefit statement, and found that both were effective in improving judgements, but had no effect on intention to comply. Experiment 3 compared the effectiveness of the two forms of benefit information but participants were told that the medicine was associated with four named side effects. Both types of statement improved ratings of the intention to comply, as well as ratings on the other measures. The experiments provide fairly consistent support for the inclusion of benefit information in medicine information leaflets, particularly to balance concerns about side effects.

Midpoint perturbation response in haptically-guided movements

This study investigates the human response to impulse perturbations at the midpoint of a haptically-guided straight-line point-to-point movement. Such perturbation response may be used as an assessment tool during robot-mediated neuro-rehabilitation therapy. Subjects show variety in their perturbation responses. Movements with a lower perturbation displacement exhibit high frequency oscillations, indicative of increased joint stiffness. Equally, movements with a high perturbation displacement exhibit lower frequency oscillations with higher amplitude and a longer settling time. Some subjects show unexpected transients during the perturbation impulse, which may be caused by complex joint interactions in the hand and arm.

Design considerations in the sequential analysis of matched case–control data

A role for sequential test procedures is emerging in genetic and epidemiological studies using banked biological resources. This stems from the methodology's potential for improved use of information relative to comparable fixed sample designs. Studies in which cost, time and ethics feature prominently are particularly suited to a sequential approach. In this paper sequential procedures for matched case–control studies with binary data will be investigated and assessed. Design issues such as sample size evaluation and error rates are identified and addressed. The methodology is illustrated and evaluated using both real and simulated data sets.

Preliminary results on the non-thermal effects of 200-350 GHz radiation on the growth rate of S. cerevisiae cells in microcolonies

We report preliminary results from studies of biological effects induced by non-thermal levels of non-ionizing electromagnetic radiation. Exponentially growing Saccharomyces cerevisiae yeast cells grown on dry media were exposed to electromagnetic fields in the 200–350 GHz frequency range at low power density to observe possible non-thermal effects on the microcolony growth. Exposure to the electromagnetic field was conducted over 2.5 h. The data from exposure and control experiments were grouped into either large-, medium- or small-sized microcolonies to assist in the accurate assessment of growth. The three groups showed significant differences in growth between exposed and control microcolonies. A statistically significant enhanced growth rate was observed at 341 GHz. Growth rate was assessed every 30 min via time-lapse photography. Possible interaction mechanisms are discussed, taking into account Frohlich's hypothesis.

Reduction of invasive tests in chagasic patients with a modified self-organizing map

The applicability of AI methods to the Chagas' disease diagnosis is carried out by the use of Kohonen's self-organizing feature maps. Electrodiagnosis indicators calculated from ECG records are used as features in input vectors to train the network. Cross-validation results are used to modify the maps, providing an outstanding improvement to the interpretation of the resulting output. As a result, the map might be used to reduce the need for invasive explorations in chronic Chagas' disease.

Minimum recovery time between reactive hyperemia stimulus in the repeated measurement of brachial flow-mediated dilatation.

The ability to undertake repeat measurements of flow-mediated dilatation (FMD) within a short time of a previous measurement would be useful to improve accuracy or to repeat a failed initial procedure. Although standard methods report that a minimum of 10 min is required between measurements, there is no published data to support this. Thirty healthy volunteers had five FMD measurements performed within a 2-h period, separated by various time intervals (5, 15 and 30 min). In 19 volunteers, FMD was also performed as soon as the vessel had returned to its baseline diameter. There was no significant difference between any of the FMD measurements or parameters across the visits indicating that repeat measurements may be taken after a minimum of 5 min or as soon as the vessel has returned to its baseline diameter, which in some subjects may be less than 5 min.

Gravity well visibility in haptic interfaces for motion-impaired

Haptic computer interfaces provide users with feedback through the sense of touch, thereby allowing users to feel a graphical user interface. Force feedback gravity wells, i.e. attractive basins that can pull the cursor toward a target, are one type of haptic effect that have been shown to provide improvements in "point and click" tasks. For motion-impaired users, gravity wells could improve times by as much as 50%. It has been reported that the presentation of information to multiple sensory modalities, e.g. haptics and vision, can provide performance benefits. However, previous studies investigating the use of force feedback gravity wells have generally not provided visual representations of the haptic effect. Where force fields extend beyond clickable targets, the addition of visual cues may affect performance. This paper investigates how the performance of motion-impaired computer users is affected by having visual representations of force feedback gravity wells presented on-screen. Results indicate that the visual representation does not affect times and errors in a "point and click" task involving multiple targets.

Conditionally unbiased estimation in phase II/III clinical trials with early stopping for futility

Seamless phase II/III clinical trials combine traditional phases II and III into a single trial that is conducted in two stages, with stage 1 used to answer phase II objectives such as treatment selection and stage 2 used for the confirmatory analysis, which is a phase III objective. Although seamless phase II/III clinical trials are efficient because the confirmatory analysis includes phase II data from stage 1, inference can pose statistical challenges. In this paper, we consider point estimation following seamless phase II/III clinical trials in which stage 1 is used to select the most effective experimental treatment and to decide if, compared with a control, the trial should stop at stage 1 for futility. If the trial is not stopped, then the phase III confirmatory part of the trial involves evaluation of the selected most effective experimental treatment and the control. We have developed two new estimators for the treatment difference between these two treatments with the aim of reducing bias conditional on the treatment selection made and on the fact that the trial continues to stage 2. We have demonstrated the properties of these estimators using simulations