Data-driven treatment selection for seamless phase II/III trials incorporating early-outcome data

Seamless phase II/III clinical trials are conducted in two stages with treatment selection at the first stage. In the first stage, patients are randomized to a control or one of k > 1 experimental treatments. At the end of this stage, interim data are analysed, and a decision is made concerning which experimental treatment should continue to the second stage. If the primary endpoint is observable only after some period of follow-up, at the interim analysis data may be available on some early outcome on a larger number of patients than those for whom the primary endpoint is available. These early endpoint data can thus be used for treatment selection. For two previously proposed approaches, the power has been shown to be greater for one or other method depending on the true treatment effects and correlations. We propose a new approach that builds on the previously proposed approaches and uses data available at the interim analysis to estimate these parameters and then, on the basis of these estimates, chooses the treatment selection method with the highest probability of correctly selecting the most effective treatment. This method is shown to perform well compared with the two previously described methods for a wide range of true parameter values. In most cases, the performance of the new method is either similar to or, in some cases, better than either of the two previously proposed methods.

Solar wind control of magnetospheric energy content: substorm quenching and multiple onsets

In this paper we report coordinated multispacecraft and ground-based observations of a double substorm onset close to Scandinavia on November 17, 1996. The Wind and the Geotail spacecraft, which were located in the solar wind and the subsolar magnetosheath, respectively, recorded two periods of southward directed interplanetary magnetic field (IMF). These periods were separated by a short northward IMF excursion associated with a solar wind pressure pulse, which compressed the magnetosphere to such a degree that Geotail for a short period was located outside the bow shock. The first period of southward IMF initiated a substorm growth. phase, which was clearly detected by an array of ground-based instrumentation and by Interball in the northern tail lobe. A first substorm onset occurred in close relation to the solar wind pressure pulse impinging on the magnetopause and almost simultaneously with the northward turning of the IMF. However, this substorm did not fully develop. In clear association with the expansion of the magnetosphere at the end of the pressure pulse, the auroral expansion was stopped, and the northern sky cleared. We will present evidence that the change in the solar wind dynamic pressure actively quenched the energy available for any further substorm expansion. Directly after this period, the magnetometer network detected signatures of a renewed substorm growth phase, which was initiated by the second southward turning of the IMF and which finally lead to a second, and this time complete, substorm intensification. We have used our multipoint observations in order to understand the solar wind control of the substorm onset and substorm quenching. The relative timings between the observations on the various satellites and on the ground were used to infer a possible causal relationship between the solar wind pressure variations and consequent substorm development. Furthermore, using a relatively simple algorithm to model the tail lobe field and the total tail flux, we show that there indeed exists a close relationship between the relaxation of a solar wind pressure pulse, the reduction of the tail lobe field, and the quenching of the initial substorm.

A comparison of methods for treatment selection in seamless phase II/III clinical trials incorporating information on short-term endpoints

In an adaptive seamless phase II/III clinical trial interim analysis, data are used for treatment selection, enabling resources to be focused on comparison of more effective treatment(s) with a control. In this paper, we compare two methods recently proposed to enable use of short-term endpoint data for decision-making at the interim analysis. The comparison focuses on the power and the probability of correctly identifying the most promising treatment. We show that the choice of method depends on how well short-term data predict the best treatment, which may be measured by the correlation between treatment effects on short- and long-term endpoints.

The expression of ferritin, lactoferrin, transferrin receptor and solute carrier family 11A1 in the host response to BCG-vaccination and Mycobacterium tuberculosis challenge

Iron is an essential cofactor for both mycobacterial growth during infection and for a successful protective immune response by the host. The immune response partly depends on the regulation of iron by the host, including the tight control of expression of the iron-storage protein, ferritin. BCG vaccination can protect against disease following Mycobacterium tuberculosis infection, but the mechanisms of protection remain unclear. To further explore these mechanisms, splenocytes from BCG-vaccinated guinea pigs were stimulated ex vivo with purified protein derivative from M. tuberculosis and a significant down-regulation of ferritin light- and heavy-chain was measured by reverse-transcription quantitative-PCR (P ≤0.05 and ≤0.01, respectively). The mechanisms of this down-regulation were shown to involve TNFα and nitric oxide. A more in depth analysis of the mRNA expression profiles, including genes involved in iron metabolism, was performed using a guinea pig specific immunological microarray following ex vivo infection with M. tuberculosis of splenocytes from BCG-vaccinated and naïve guinea pigs. M. tuberculosis infection induced a pro-inflammatory response in splenocytes from both groups, resulting in down-regulation of ferritin (P ≤0.05). In addition, lactoferrin (P ≤0.002), transferrin receptor (P ≤0.05) and solute carrier family 11A1 (P ≤0.05), were only significantly down-regulated after infection of the splenocytes from BCG-vaccinated animals. The results show that expression of iron-metabolism genes is tightly regulated as part of the host response to M. tuberculosis infection and that BCG-vaccination enhances the ability of the host to mount an iron-restriction response which may in turn help to combat invasion by mycobacteria.

B-spline neural network based single-carrier frequency domain equalisation for Hammerstein channels

A practical single-carrier (SC) block transmission with frequency domain equalisation (FDE) system can generally be modelled by the Hammerstein system that includes the nonlinear distortion effects of the high power amplifier (HPA) at transmitter. For such Hammerstein channels, the standard SC-FDE scheme no longer works. We propose a novel Bspline neural network based nonlinear SC-FDE scheme for Hammerstein channels. In particular, we model the nonlinear HPA, which represents the complex-valued static nonlinearity of the Hammerstein channel, by two real-valued B-spline neural networks, one for modelling the nonlinear amplitude response of the HPA and the other for the nonlinear phase response of the HPA. We then develop an efficient alternating least squares algorithm for estimating the parameters of the Hammerstein channel, including the channel impulse response coefficients and the parameters of the two B-spline models. Moreover, we also use another real-valued B-spline neural network to model the inversion of the HPA’s nonlinear amplitude response, and the parameters of this inverting B-spline model can be estimated using the standard least squares algorithm based on the pseudo training data obtained as a byproduct of the Hammerstein channel identification. Equalisation of the SC Hammerstein channel can then be accomplished by the usual one-tap linear equalisation in frequency domain as well as the inverse Bspline neural network model obtained in time domain. The effectiveness of our nonlinear SC-FDE scheme for Hammerstein channels is demonstrated in a simulation study.

Exploration of the neural correlates of cerebral palsy for sensorimotor BCI control

Cerebral palsy (CP) includes a broad range of disorders, which can result in impairment of posture and movement control. Brain-computer interfaces (BCIs) have been proposed as assistive devices for individuals with CP. Better understanding of the neural processing underlying motor control in affected individuals could lead to more targeted BCI rehabilitation and treatment options. We have explored well-known neural correlates of movement, including event-related desynchronization (ERD), phase synchrony, and a recently-introduced measure of phase dynamics, in participants with CP and healthy control participants. Although present, significantly less ERD and phase locking were found in the group with CP. Additionally, inter-group differences in phase dynamics were also significant. Taken together these findings suggest that users with CP exhibit lower levels of motor cortex activation during motor imagery, as reflected in lower levels of ongoing mu suppression and less functional connectivity. These differences indicate that development of BCIs for individuals with CP may pose additional challenges beyond those faced in providing BCIs to healthy individuals.

Flexible selection of a single treatment incorporating short-term endpoint information in a phase II/III clinical trial

Seamless phase II/III clinical trials in which an experimental treatment is selected at an interim analysis have been the focus of much recent research interest. Many of the methods proposed are based on the group sequential approach. This paper considers designs of this type in which the treatment selection can be based on short-term endpoint information for more patients than have primary endpoint data available. We show that in such a case, the familywise type I error rate may be inflated if previously proposed group sequential methods are used and the treatment selection rule is not specified in advance. A method is proposed to avoid this inflation by considering the treatment selection that maximises the conditional error given the data available at the interim analysis. A simulation study is reported that illustrates the type I error rate inflation and compares the power of the new approach with two other methods: a combination testing approach and a group sequential method that does not use the short-term endpoint data, both of which also strongly control the type I error rate. The new method is also illustrated through application to a study in Alzheimer's disease. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

The efficacy of potassium sorbate-coated packaging to control postharvest gray mold in raspberries, blackberries, and blueberries

The aim of this work is to build on the success of in vitro studies of an active packaging, produced by coating the surface of post-consumer recycled polyethylene terephthalate (PCRPET) package with an aqueous silicone solution (2%, v/v) containing an antifungal agent (potassium sorbate, KS). Antifungal efficacy was evaluated, in vivo, during the storage of raspberries, blackberries and blueberries by examining their shelf life extension. The packaging effectively delayed the growth of Botrytis by extending its lag-phase, which, in turn, extended the shelf life of the berries by up to 3d. Among the three berries tested, the packaging proved to be more advantageous in the case of raspberries, due to their physiological characteristics and shorter shelf life. Based on sensory panel evaluations, it was shown that the coating, containing KS, did not influence the packaging appearance and transparency, and the fruit did not suffer from any off-flavor development.

Compositional control of the electrical transport properties in the new series of thiospinels Ga1-xGexV4S8-delta (0 <=x<=1)

A new series of non-stoichiometric sulfides Ga1−xGexV4S8−δ (0≤x≤1; δ≤0.23) has been synthesized at high temperatures by heating stoichiometric mixtures of the elements in sealed quartz tubes. The samples have been characterized by powder X-ray diffraction, SQUID magnetometry and electrical transport-property measurements. Structural analysis reveals that a solid solution is formed throughout this composition range, whilst thermogravimetric data reveal sulfur deficiency of up to 2.9% in the quaternary phases. Magnetic measurements suggest that the ferromagnetic behavior of the end-member phase GaV4S8 is retained at x≤0.7; samples in this composition range showing a marked increase in magnetization at low temperatures. By contrast Ga0.25Ge0.75V4S8−δ appears to undergo antiferromagnetic ordering at ca. 15 K. All materials with x≠1 are n-type semiconductors whose resistivity falls by almost six orders of magnitude with decreasing Ga content, whilst the end-member phase GeV4S8−δ is a p-type semiconductor. The results demonstrate that the physical properties are determined principally by the degree of electron filling of narrow-band states arising from intracluster V–V interactions.

Stopping rules for phase II studies

This paper, the second in a series of three papers concerned with the statistical aspects of interim analyses in clinical trials, is concerned with stopping rules in phase II clinical trials. Phase II trials are generally small-scale studies, and may include one or more experimental treatments with or without a control. A common feature is that the results primarily determine the course of further clinical evaluation of a treatment rather than providing definitive evidence of treatment efficacy. This means that there is more flexibility available in the design and analysis of such studies than in phase III trials. This has led to a range of different approaches being taken to the statistical design of stopping rules for such trials. This paper briefly describes and compares the different approaches. In most cases the stopping rules can be described and implemented easily without knowledge of the detailed statistical and computational methods used to obtain the rules.

Control of nanomaterial self-assembly in ultrasonically levitated droplets

We demonstrate that acoustic trapping can be used to levitate and manipulate droplets of soft matter, in particular, lyotropic mesophases formed from selfassembly of different surfactants and lipids, which can be analyzed in a contact-less manner by X-ray scattering in a controlled gas-phase environment. On the macroscopic length scale, the dimensions and the orientation of the particle are shaped by the ultrasonic field, while on the microscopic length scale the nanostructure can be controlled by varying the humidity of the atmosphere around the droplet. We demonstrate levitation and in situ phase transitions of micellar, hexagonal, bicontinuous cubic, and lamellar phases. The technique opens up a wide range of new experimental approaches of fundamental importance for environmental, biological, and chemical research.

What controls the vertical distribution of aerosol? Relationships between process sensitivity in HadGEM3–UKCA and inter-model variation from AeroCom Phase II

The vertical profile of aerosol is important for its radiative effects, but weakly constrained by observations on the global scale, and highly variable among different models. To investigate the controlling factors in one particular model, we investigate the effects of individual processes in HadGEM3–UKCA and compare the resulting diversity of aerosol vertical profiles with the inter-model diversity from the AeroCom Phase II control experiment. In this way we show that (in this model at least) the vertical profile is controlled by a relatively small number of processes, although these vary among aerosol components and particle sizes. We also show that sufficiently coarse variations in these processes can produce a similar diversity to that among different models in terms of the global-mean profile and, to a lesser extent, the zonal-mean vertical position. However, there are features of certain models' profiles that cannot be reproduced, suggesting the influence of further structural differences between models. In HadGEM3–UKCA, convective transport is found to be very important in controlling the vertical profile of all aerosol components by mass. In-cloud scavenging is very important for all except mineral dust. Growth by condensation is important for sulfate and carbonaceous aerosol (along with aqueous oxidation for the former and ageing by soluble material for the latter). The vertical extent of biomass-burning emissions into the free troposphere is also important for the profile of carbonaceous aerosol. Boundary-layer mixing plays a dominant role for sea salt and mineral dust, which are emitted only from the surface. Dry deposition and below-cloud scavenging are important for the profile of mineral dust only. In this model, the microphysical processes of nucleation, condensation and coagulation dominate the vertical profile of the smallest particles by number (e.g. total CN  >  3 nm), while the profiles of larger particles (e.g. CN  >  100 nm) are controlled by the same processes as the component mass profiles, plus the size distribution of primary emissions. We also show that the processes that affect the AOD-normalised radiative forcing in the model are predominantly those that affect the vertical mass distribution, in particular convective transport, in-cloud scavenging, aqueous oxidation, ageing and the vertical extent of biomass-burning emissions.