National Institutes of Health Consensus Development Project on Criteria for Clinical Trials in Chronic Graft-Versus-Host Disease: III. The 2014 Biomarker Working Group Report

Biology-based markers to confirm or aid in the diagnosis or prognosis of chronic GVHD after allogeneic hematopoietic cell transplantation (HCT) or monitor its progression are critically needed to facilitate evaluation of new therapies. Biomarkers have been defined as any characteristic that is objectively measured and evaluated as an indicator of a normal biological or pathogenic process, a pharmacologic response to a therapeutic intervention. Applications of biomarkers in chronic GVHD clinical trials or patient management include: a) diagnosis and assessment of chronic GVHD disease activity, including distinguishing irreversible damage from continued disease activity, b) prognostic risk to develop chronic GVHD, and c) prediction of response to therapy. Sample collection for chronic GVHD biomarkers studies should be well-documented following established quality control guidelines for sample acquisition, processing, preservation and testing, at intervals that are both calendar- and event-driven. The consistent therapeutic treatment of subjects and standardized documentation needed to support biomarker studies are most likely to be provided in prospective clinical trials. To date, no chronic GVHD biomarkers have been qualified for utilization in clinical applications. Since our previous chronic GVHD Biomarkers Working Group report in 2005, an increasing number of chronic GVHD candidate biomarkers are available for further investigation. This paper provides a four-part framework for biomarker investigations: identification, verification, qualification, and application with terminology based on Food and Drug Administration and European Medicines Agency guidelines

FDA perspectives on potential microarray-based clinical diagnostics

Abstract The US Food and Drug Administration (FDA) encourages the development of new technologies such as microarrays which may improve and streamline assessments of safety and the effectiveness of medical products for the benefit of public health. The FDA anticipates that these new technologies may offer the potential for more effective approaches to medical treatment and disease prevention and management. This paper discusses issues associated with the translation of nucleic acid microarray-based devices from basic research and target discovery to in vitro clinical diagnostic use, which the Office of In Vitro Diagnostic Device Evaluation and Safety in the Center for Devices and Radiological Health foresees will be important for assurance of safety and effectiveness of these types of devices. General technological points, assessment of potential concerns for transitioning microarrays into clinical diagnostic use and approaches for evaluating the performance of these types of devices will be discussed.</p

Physiological response curve analysis using nonlinear mixed models

Nonlinear response curves are often used to model the physiological responses of plants. These models are preferable to polynomials because the coefficients fit to the curves have biological meaning. The response curves are often generated by repeated measurements on one subject, over a range of values for the environmental variable of interest. However, the typical analysis of differences in coefficients between experimental groups does not include a repeated measures approach. This may lead to inappropriate estimation of error terms. Here, we show how to combine mixed model analysis, available in SAS, that allows for repeated observations on the same experimental unit, with nonlinear response curves. We illustrate the use of this nonlinear mixed model with a study in which two plant species were grown under contrasting light environments. We recorded light levels and net photosynthetic response on anywhere from 8 to 10 points per plant and fit a Mitscherlich model in which each plant has its own coefficients. The coefficients for the photosynthetic light-response curve for each plant were assumed to follow a multivariate normal distribution in which the mean was determined by the treatment. The approach yielded biologically relevant coefficients and unbiased standard error estimates for multiple treatment comparisons

Temperature-Driven Campylobacter Seasonality in England and Wales

Campylobacter incidence in England and Wales between 1990 and 1999 was examined in conjunction with weather conditions. Over the 10-year interval, the average annual rate was determined to be 78.4 ± 15.0 cases per 100,000, with an upward trend. Rates were higher in males than in females, regardless of age, and highest in children less than 5 years old. Major regional differences were detected, with the highest rates in Wales and the southwest and the lowest in the southeast. The disease displayed a seasonal pattern, and increased campylobacter rates were found to be correlated with temperature. The most marked seasonal effect was observed for children under the age of 5. The seasonal pattern of campylobacter infections indicated a linkage with environmental factors rather than food sources. Therefore, public health interventions should not be restricted to food-borne approaches, and the epidemiology of the seasonal peak in human campylobacter infections may best be understood through studies in young children