Comprehensive validation of published immunohistochemical prognostic biomarkers of prostate cancer-what has gone wrong? A blueprint for the way forward in biomarker studies

BACKGROUND Treatment planning of localised prostate cancer remains challenging. Besides conventional parameters, a wealth of prognostic biomarkers has been proposed so far. None of which, however, have successfully been implemented in a routine setting so far. The aim of our study was to systematically verify a set of published prognostic markers for prostate cancer. METHODS Following an in-depth PubMed search, 28 markers were selected that have been proposed as multivariate prognostic markers for primary prostate cancer. Their prognostic validity was examined in a radical prostatectomy cohort of 238 patients with a median follow-up of 60 months and biochemical progression as endpoint of the analysis. Immunohistochemical evaluation was performed using previously published cut-off values, but allowing for optimisation if necessary. Univariate and multivariate Cox regression were used to determine the prognostic value of biomarkers included in this study. RESULTS Despite the application of various cut-offs in the analysis, only four (14%) markers were verified as independently prognostic (AKT1, stromal AR, EZH2, and PSMA) for PSA relapse following radical prostatectomy. CONCLUSIONS Apparently, many immunohistochemistry-based studies on prognostic markers seem to be over-optimistic. Codes of best practice, such as the REMARK guidelines, may facilitate the performance of conclusive and transparent future studies.

Moving forward on facilitation research: response to changing environments and effects on the diversity, functioning and evolution of plant communities

Once seen as anomalous, facilitative interactions among plants and their importance for community structure and functioning are now widely recognized. The growing body of modelling, descriptive and experimental studies on facilitation covers a wide variety of terrestrial and aquatic systems throughout the globe. However, the lack of a general body of theory linking facilitation among different types of organisms and biomes and their responses to environmental changes prevents further advances in our knowledge regarding the evolutionary and ecological implications of facilitation in plant communities. Moreover, insights gathered from alternative lines of inquiry may substantially improve our understanding of facilitation, but these have been largely neglected thus far. Despite over 15 years of research and debate on this topic, there is no consensus on the degree to which plant–plant interactions change predictably along environmental gradients (i.e. the stress-gradient hypothesis), and this hinders our ability to predict how plant–plant interactions may affect the response of plant communities to ongoing global environmental change. The existing controversies regarding the response of plant–plant interactions across environmental gradients can be reconciled when clearly considering and determining the species-specificity of the response, the functional or individual stress type, and the scale of interest (pairwise interactions or community-level response). Here, we introduce a theoretical framework to do this, supported by multiple lines of empirical evidence. We also discuss current gaps in our knowledge regarding how plant–plant interactions change along environmental gradients. These include the existence of thresholds in the amount of species-specific stress that a benefactor can alleviate, the linearity or non-linearity of the response of pairwise interactions across distance from the ecological optimum of the beneficiary, and the need to explore further how frequent interactions among multiple species are and how they change across different environments. We review the latest advances in these topics and provide new approaches to fill current gaps in our knowledge. We also apply our theoretical framework to advance our knowledge on the evolutionary aspects of plant facilitation, and the relative importance of facilitation, in comparison with other ecological processes, for maintaining ecosystem structure, functioning and dynamics. We build links between these topics and related fields, such as ecological restoration, woody encroachment, invasion ecology, ecological modelling and biodiversity–ecosystem-functioning relationships. By identifying commonalities and insights from alternative lines of research, we further advance our understanding of facilitation and provide testable hypotheses regarding the role of (positive) biotic interactions in the maintenance of biodiversity and the response of ecological communities to ongoing environmental changes.

Pushing forward in embodied cognition: May we mouse the mathematical mind?

Freely available software has popularized “mousetracking” to study cognitive processing; this involves the on-line recording of cursor positions while participants move a computer mouse to indicate their choice. Movement trajectories of the cursor can then be reconstructed off-line to assess the efficiency of responding in time and across space. Here we focus on the process of selecting among alternative numerical responses. Several studies have recently measured the mathematical mind with cursor movements while people decided about number magnitude or parity, computed sums or differences, or simply located numbers on a number line. After some general methodological considerations about mouse tracking we discuss several conceptual concerns that become particularly evident when “mousing” the mathematical mind.

Detecting outlying studies in meta-regression models using a forward search algorithm.

When considering data from many trials, it is likely that some of them present a markedly different intervention effect or exert an undue influence on the summary results. We develop a forward search algorithm for identifying outlying and influential studies in meta-analysis models. The forward search algorithm starts by fitting the hypothesized model to a small subset of likely outlier-free studies and proceeds by adding studies into the set one-by-one that are determined to be closest to the fitted model of the existing set. As each study is added to the set, plots of estimated parameters and measures of fit are monitored to identify outliers by sharp changes in the forward plots. We apply the proposed outlier detection method to two real data sets; a meta-analysis of 26 studies that examines the effect of writing-to-learn interventions on academic achievement adjusting for three possible effect modifiers, and a meta-analysis of 70 studies that compares a fluoride toothpaste treatment to placebo for preventing dental caries in children. A simple simulated example is used to illustrate the steps of the proposed methodology, and a small-scale simulation study is conducted to evaluate the performance of the proposed method. Copyright © 2016 John Wiley & Sons, Ltd.

Trade Costs, Quality, and The Skill Premium

We develop a monopolistic competition model with nonhomothetic factor input bundles where increasing quality requires increasing use of skilled workers. As a result more skill abundant countries export higher quality, higher priced goods. Using a multicountry dataset we test and confirm the findings in Schott (2004) of a positive effect of skill abundance on unit values identified with US data. We extend the core model with per unit trade costs leading to the Washington-apples effect that goods shipped over larger distance are of higher quality. The combination of high-quality goods being relatively skill intensive with the Washington-apples effect implies that countries at a larger distance from their trading partners display a higher skill premium. Simulating our model we find that a doubling of distance of a country relative to all its trading partners raises the skill premium in a country by about 2.3 percent.

Lessons for emerging state Children's Health Insurance Premium Assistance programs: Case study of the Massachusetts Masshealth Family Assistance Program (MHFAP)

Providing health insurance coverage for vulnerable populations such as low-income high-risk children with limited access to health care is a challenge for many states. Over the past decade, higher private insurance premiums and unpredictable labor markets have increased the number of uninsured and underinsured children nationwide. Due to recent economic downfalls, many states such as Texas, have expressed interest in using premium assistance programs to increase enrollment of low income children and families in private coverage through employer sponsored health insurance. Massachusetts has been especially successful in reducing the number of uninsured children through the implementation of MassHealth Family Assistance Program (MHFAP), an employer based premium assistance program. The purpose of this study is to identify key implementation factors of a fully established premium assistance program which may provide lessons and facilitate implementation of emerging premium assistance programs. ^ The case study of the fully established MassHealth Family Assistance Program (MHFAP) has illustrated the ability of states to expand their Medicaid and SCHIP programs in order to provide affordable health coverage to uninsured and underinsured low income children and their families. As demonstrated by MHFAP, the success of a premium assistance program depends on four key factors: (1) determination of participant and employer eligibility; (2) determination of employer benefits meeting benchmark equivalency (Medicaid or State Children's Health Insurance Program); (3) the use of appropriate marketing and outreach strategies; and (4) establishment of adequate monitoring and reporting techniques. Successful implementation strategies, revealed by the case study of the Massachusetts MassHealth Family Assistance Program, may be used by emerging premium assistance programs, such as Texas Children's Health Insurance Premium Assistance Program (CHIP-PA) toward establishment of an effective, efficient, and equitable employer sponsored health program.^

A Path Forward: Evidence-Based Approaches to Educational Policy and Practice

In the complex landscape of public education, participants at all levels are searching for policy and practice levers that can raise overall performance and close achievement gaps. The collection of articles in this edition of the Journal of Applied Research on Children takes a big step toward providing the tools and tactics needed for an evidence-based approach to educational policy and practice.

Skill sorting, inter-industry skill wage premium, and production chains: evidence from India 1999-2000

This paper proposes a mechanism that links industry’s technological characteristics (i.e. quality of non-labor inputs, which is proxied by the length of industry production chains), industry-specific skill wage premium, and skill sorting across industries. It is hypothesized that high-skilled workers are sorted into industries where they can receive a higher skill wage premium, by working with better quality non-labor input. The quality of non-labor inputs is assumed to be worse in industries with longer production chains due to the increased involvement of low-skilled labor and poor infrastructure over the sequential production. By examining Indian wage and employment data for 1999-2000, empirical evidence to support this mechanism can be obtained: First, the skill wage premium is lower [higher] in industries with longer [shorter] production chains. Second, the skill wage premium is lower [higher] in industries with a higher [lower] proportion of low-skilled workers producing inputs outside their own industry. Third, the proportion of high-skilled workers is larger in industries with shorter production chains and lower ratio of low-skilled labor involved, i.e., a skill sorting trend can be observed.

Is there any premium for unobservable quality? : a hedonic price analysis of the Malagasy rice market

This paper examines if consumers pay a premium for unobservable quality in the absence of quality standards and/or quality grading systems and, if so, how they assess that unobservable quality, using a rice retail market in Madagascar as an example. In Madagascar, the lack of quality standards and/or grading systems for rice makes is considered to be one of the causes of the rice market's spatial disintegration. Thus, quality standards and grading systems will be necessary to increase the market's efficiency. We hypothesize that consumers and retailers use product origin and rice name as observable indictors of unobservable quality and test the hypothesis using hedonic price regressions. We find that the interaction terms of product origin and rice name significantly affect the price after controlling for both observable quality and spatial and temporal price variation, but that the contribution of product origin and rice name to rice price variation is smaller than spatial and temporal factors. We thus conclude that consumers pay a premium for unobservable quality throughout Madagascar. This finding implies that quality standards and/or grading systems will work in the Malagasy market and that improving market infrastructure such as roads and storage will make them even more effective.