Statistical testing strategies for assessing treatment efficacy and marker accuracy in phase III trials

When a candidate predictive marker is available, but evidence on its predictive ability is not sufficiently reliable, all‐comers trials with marker stratification are frequently conducted. We propose a framework for planning and evaluating prospective testing strategies in confirmatory, phase III marker‐stratified clinical trials based on a natural assumption on heterogeneity of treatment effects across marker‐defined subpopulations, where weak rather than strong control is permitted for multiple population tests. For phase III marker‐stratified trials, it is expected that treatment efficacy is established in a particular patient population, possibly in a marker‐defined subpopulation, and that the marker accuracy is assessed when the marker is used to restrict the indication or labelling of the treatment to a marker‐based subpopulation, ie, assessment of the clinical validity of the marker. In this paper, we develop statistical testing strategies based on criteria that are explicitly designated to the marker assessment, including those examining treatment effects in marker‐negative patients. As existing and developed statistical testing strategies can assert treatment efficacy for either the overall patient population or the marker‐positive subpopulation, we also develop criteria for evaluating the operating characteristics of the statistical testing strategies based on the probabilities of asserting treatment efficacy across marker subpopulations. Numerical evaluations to compare the statistical testing strategies based on the developed criteria are provided.     

Development of the Mental Illness and Disorder Understanding Scale

Abstract: Although administrative bodies such as community health centers have implemented various awareness campaigns to promote community understanding of mental health and to reduce the stigma associated with mental illness and disorder, there have been few reports that have quantitatively analyzed the effects of these campaigns in Japan. Therefore, this study was conducted for the purpose of developing the evaluative “Mental Illness and Disorder Understanding Scale (MIDUS)” for awareness campaigns and assessing its reliability and validity. A survey was conducted on 1 004 community residents using a self‐administered questionnaire. An assessment of the reliability and validity of the scale was then conducted. The Cronbach a coefficient of the MIDUS was 0.78, thus indicating adequate reliability. Factor analysis of the MIDUS revealed three factors: “Treatability of illness”, “Efficacy of medication” and “Social recognition of illness”. In addition, a significant correlation was observed between the MIDUS and existing scales, and fixed criterion‐based validity was demonstrated. The MIDUS utilizes items worded in the form of affirmative expressions so as to avoid promoting new bias. It was confirmed to be both reliable and valid, thereby suggesting its usefulness as an evaluative scale of awareness campaigns.     

Daily Inhalation Rate and Time‐Activity/Location Pattern in Japanese Preschool Children

Lack of data on daily inhalation rate and activity of children has been an issue in health risk assessment of air pollutants. This study aimed to obtain the daily inhalation rate and intensity and frequency of physical activity in relation to the environment in Japanese preschool children. Children aged four–six years (n= 138) in the suburbs of Tokyo participated in this study, which involved three days' continuous monitoring of physical activity using a tri‐axial accelerometer and parent's completion of a time/location diary during daily life. The estimated three‐day mean daily inhalation rate (body temperature, pressure, saturated with water vapor) was 9.9 ± 1.6 m³/day (0.52 ± 0.09 m³/kg/day). The current daily inhalation rate value of 0.580 m³/kg/day proposed for use in health risk assessment in Japan is confirmed to be valid to calculate central value of inhaled dose of air pollutants in five‐ to six‐year‐old children. However, the 95th percentile daily inhalation rate of 0.83 m³/kg/day based on measurement for five‐year‐old children is recommended to be used to provide an upper bound estimate of exposure that ensure the protection of all five‐ to six‐year‐old children from the health risk of air pollutants. Children spent the majority of their time in sedentary and light level of physical activity (LPA) when indoors, while 85% of their time when outdoors was spent in LPA and moderate‐to‐vigorous physical activity. The results suggest the need to consider variability of minute respiratory ventilation rate according to the environment for more refined short‐term health risk assessment.     

On second-order improved estimation of a gamma scale parameter

This paper concludes our comprehensive study on point estimation of model parameters of a gamma distribution from a second-order decision theoretic point of view. It should be noted that efficient estimation of gamma model parameters for samples ‘not large’ is a challenging task since the exact sampling distributions of the maximum likelihood estimators and its variants are not known. Estimation of a gamma scale parameter has received less attention from the earlier researchers compared to shape parameter estimation. What we have observed here is that improved estimation of the shape parameter does not necessarily lead to improved scale estimation if a natural moment condition (which is also the maximum likelihood restriction) is satisfied. Therefore, this work deals with the gamma scale parameter estimation as a separate new problem, not as a by-product of the shape parameter estimation, and studies several estimators in terms of second-order risk.     

Group sequential monitoring based on the weighted log‐rank test statistic with the Fleming–Harrington class of weights in cancer vaccine studies

In recent years, immunological science has evolved, and cancer vaccines are now approved and available for treating existing cancers. Because cancer vaccines require time to elicit an immune response, a delayed treatment effect is expected and is actually observed in drug approval studies. Accordingly, we propose the evaluation of survival endpoints by weighted log‐rank tests with the Fleming–Harrington class of weights. We consider group sequential monitoring, which allows early efficacy stopping, and determine a semiparametric information fraction for the Fleming–Harrington family of weights, which is necessary for the error spending function. Moreover, we give a flexible survival model in cancer vaccine studies that considers not only the delayed treatment effect but also the long‐term survivors. In a Monte Carlo simulation study, we illustrate that when the primary analysis is a weighted log‐rank test emphasizing the late differences, the proposed information fraction can be a useful alternative to the surrogate information fraction, which is proportional to the number of events. Copyright © 2016 John Wiley & Sons, Ltd.     

Justice and Tyranny: Bringing “Rural” Back into the Sociology of Food and Agriculture

In the current polarizing political climate, what constitutes just has become increasingly questioned and debated in the public arena. Tyrants seem everywhere to shape people's understanding of who belongs in communities and nation-states and, therefore, who should be given a voice and what should be valued. This paper unpacks the mechanisms of tyranny and the pursuit of justice in the global agri-food system. The first section discusses justice and tyranny as sociological concepts and practice, followed by the second section that examins two types of tyrannies in the globalized agri-food system: neoliberal capitalism and community. I argue that neoliberal capitalism and community are the logics for organizing social relations and the sites of enacting tyrannies and justice. Third, I argue that in the tension between capitalism and community in achieving justice, rural becomes critical both theoretically and empirically for understanding the current transformations and the future challenges for transforming agri-food systems. Finally, the paper concludes with possible contributions of rural sociological imaginations to shaping the discourse of justice and explore the process of justice.     

Kernel naive Bayes discrimination for high‐dimensional pattern recognition

Kernel discriminant analysis translates the original classification problem into feature space and solves the problem with dimension and sample size interchanged. In high‐dimension low sample size (HDLSS) settings, this reduces the ‘dimension’ to that of the sample size. For HDLSS two‐class problems we modify Mika's kernel Fisher discriminant function which – in general – remains ill‐posed even in a kernel setting; see Mika et al. (1999). We propose a kernel naive Bayes discriminant function and its smoothed version, using first‐ and second‐degree polynomial kernels. For fixed sample size and increasing dimension, we present asymptotic expressions for the kernel discriminant functions, discriminant directions and for the error probability of our kernel discriminant functions. The theoretical calculations are complemented by simulations which show the convergence of the estimators to the population quantities as the dimension grows. We illustrate the performance of the new discriminant rules, which are easy to implement, on real HDLSS data. For such data, our results clearly demonstrate the superior performance of the new discriminant rules, and especially their smoothed versions, over Mika's kernel Fisher version, and typically also over the commonly used naive Bayes discriminant rule.     

Using GIS in community design charrettes: Lessons from a Japan–U.S. collaboration in earthquake recovery and mitigation planning for Kobe

Charrettes have become popular in the urban design field, especially for use among multidisciplinary teams of professionals and non-professional community stakeholders seeking to incorporate a rich array of expertise in short visioning activities. Geographic Information Systems are among the technologies with potential to provide sophisticated spatial information to charrette participants efficiently. This article reports on a charrette carried out jointly by teams from Kobe University and the University of Washington, Seattle, USA, using GIS to inform urban design in three neighborhoods affected by the Great Hanshin–Awaji Earthquake of 1995 in Kobe, Japan. The article describes the charrette itself, and discusses the utility of GIS, given the challenges of disaster recovery in a context of undeveloped institutions for public participation, and with participants of different linguistic and educational backgrounds. In combination with electronically storable drawing technology, GIS proved useful in enlarging the multidisciplinary and cross-cultural reach of urban design; in incorporating new layers of pre-prepared expert data, and in combining such data with dynamically-generated “advice maps” and design ideas. For GIS-based charrettes to become more widely useful in community-scale design in Japan, however, additional property-scale data need to be available.     

Infants' Processing of Featural and Configural Information in the Upper and Lower Halves of the Face

Three‐ to 4‐month‐old and 6‐ to 7‐month‐old infants were administered an infant version of the Face Dimensions Test that has been used with adults (e.g., Bukach, Le Grand, Kaiser, Bub, & Tanaka, 2008). Infants were familiarized with a photograph of a woman's face and then tested with the familiar face paired with a face differing in the (a) distance separating the eyes (a configural/eyes change), (b) distance between the nose and mouth (configural/mouth change), (c) size of the eyes (featural/eyes change), and (d) size of the mouth (featural/mouth change). Infants were shown to be more sensitive to (a) configural than featural change, and (b) change around the eyes versus the mouth. Implications for the development of face processing are discussed.