Respiratory syncytial virus (RSV) is an important etiological agent of respiratory infections, particularly in children. Much information regarding the immune response to RSV comes from animal models and studies. Here, we provide a comprehensive description of the human immune response to RSV infection, based on a systematic literature review of research on infected humans. There is an initial strong neutrophil response to RSV infection in humans, which is positively correlated with disease severity and mediated by interleukin-8 (IL-8). Dendritic cells migrate to the lungs as the primary antigen-presenting cell. An initial systemic T-cell lymphopenia is followed by a pulmonary CD8 T-cell response, mediating viral clearance. Humoral immunity to reinfection is incomplete, but RSV IgG and IgA are protective. B-cell-stimulating factors derived from airway epithelium play a major role in protective antibody generation. Gamma interferon (IFN-γ) has a strongly protective role, and a Th2-biased response may be deleterious. Other cytokines (particularly IL-17A), chemokines (particularly CCL-5 and CCL-3), and local innate immune factors (including cathelicidins and IFN-λ) contribute to pathogenesis. In summary, neutrophilic inflammation is incriminated as a harmful response, whereas CD8 T cells and IFN-γ have protective roles. These may represent important therapeutic targets to modulate the immunopathogenesis of RSV infection.

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An outcome assessment, the patient assessment used in an endpoint, is the measuring instrument that provides a rating or score (categorical or continuous) that is intended to represent some aspect of the patient’s health status. Outcome assessments are used to define efficacy endpoints when developing a therapy for a disease or condition. Most efficacy endpoints are based on specified clinical assessments of patients. When clinical assessments are used as clinical trial outcomes, they are called clinical outcome assessments (COAs). COAs include any assessment that may be influenced by human choices, judgment, or motivation, COAs must be well-defined and possess adequate measurement properties in order to demonstrate (directly or indirectly) the benefits of a treatment. In contrast, a biomarker assessment is one that is subject to little, if any, patient motivational or rater judgmental influence. This is the first of two reports by the ISPOR Clinical Outcomes Assessment – Emerging Good Practices for Outcomes Research Task Force. This report provides foundational definitions important for an understanding of COA measurement principles. The foundation provided in this report includes what it means to demonstrate a beneficial effect, how assessments of patients relate to the objective of showing a treatment’s benefit, and how these assessments are used in clinical trial endpoints. In addition, this report describes intrinsic attributes of patient assessments and clinical trial factors that can affect the properties of the measurements. These factors should be considered when developing or refining assessments. These considerations will aid investigators designing trials in their choice of using an existing assessment or developing a new outcome assessment. Although the focus of this report is in the development of a new COA to define endpoints in a clinical trial, these principles may be applied more generally. A critical element in appraising or developing a COA is to describe the treatment’s intended benefit as an effect on a clearly identified aspect of how a patient feels or functions. This aspect must have importance to the patient and be part of their typical life. This meaningful health aspect can be measured directly or measured indirectly when it is impractical to evaluate it directly or difficult to measure. For indirect measurement, a concept of interest (COI) can be identified. The COI must be related to how a patient feels or functions. Procedures are then developed to measure the concept of interest. The relationship of these measurements to how a patient feels or functions in the intended setting and manner of use of the COA (the context of use) could then be defined. A COA has identifiable attributes or characteristics that affect the measurement properties of the COA when used in endpoints. One of these features is whether judgment can influence the measurement, and if so, whose judgment. This attribute defines four categories of COAs: Patient-reported outcomes (PROs), clinician-reported outcomes (...

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.

A clinician-reported outcome (ClinRO) assessment is a type of clinical outcome assessment (COA). ClinRO assessments, like all COAs (patient-reported, observer-reported, or performance outcome assessments), are used to 1) measure patients’ health status and 2) define end points that can be interpreted as treatment benefits of medical interventions on how patients feel, function, or survive in clinical trials. Like other COAs, ClinRO assessments can be influenced by human choices, judgment, or motivation. A ClinRO assessment is conducted and reported by a trained health care professional and requires specialized professional training to evaluate the patient’s health status. This is the second of two reports by the ISPOR Clinical Outcomes Assessment—Emerging Good Practices for Outcomes Research Task Force. The first report provided an overview of COAs including definitions important for an understanding of COA measurement practices. This report focuses specifically on issues related to ClinRO assessments. In this report, we define three types of ClinRO assessments (readings, ratings, and clinician global assessments) and describe emerging good measurement practices in their development and evaluation. The good measurement practices include 1) defining the context of use; 2) identifying the concept of interest measured; 3) defining the intended treatment benefit on how patients feel, function, or survive reflected by the ClinRO assessment and evaluating the relationship between that intended treatment benefit and the concept of interest; 4) documenting content validity; 5) evaluating other measurement properties once content validity is established (including intra- and inter-rater reliability); 6) defining study objectives and end point(s) objectives, and defining study end points and placing study end points within the hierarchy of end points; 7) establishing interpretability in trial results; and 8) evaluating operational considerations for the implementation of ClinRO assessments used as end points in clinical trials. Applying good measurement practices to ClinRO assessment development and evaluation will lead to more efficient and accurate measurement of treatment effects. This is important beyond regulatory approval in that it provides evidence for the uptake of new interventions into clinical practice and provides justification to payers for reimbursement on the basis of the clearly demonstrated added value of the new intervention.

Two large cardiovascular outcome trials of canagliflozin, comprising the CANVAS Program, will complete in early 2017: the CANagliflozin cardioVascular Assessment Study (CANVAS) and the CANagliflozin cardioVascular Assessment Study–Renal (CANVAS‐R). Accruing data for the sodium glucose co‐transporter 2 (SGLT2) inhibitor class has identified questions and opportunities that were not apparent when the trials were designed. Accordingly, a series of modifications have been made to the planned analyses. These updates will ensure that the data from the CANVAS Program will maximize advances in scientific knowledge and patient care. The specification of the analysis strategy prior to knowledge of the trial results, their design by the independent scientific trial Steering Committee, the detailed a priori definition of the analysis plans, and the external review provided by the US Food and Drug Administration all provide maximally efficient and robust utilization of the data. The CANVAS Program should significantly advance our understanding of the effects of canagliflozin, and the broader SGLT2 inhibitor class, on a range of important efficacy and safety outcomes.

MSFC Progression-20 and MSFC Progression-15 are sensitive measures of disability progression; correlate with EDSS, relapse rates, and SF-36 PCS; and are capable of demonstrating therapeutic effects in randomized, controlled clinical studies.

Background: The use of mobile devices in clinical research has advanced substantially in recent years due to the rapid pace of technology development. With an overall aim of informing the future use of mobile devices in interventional clinical research to measure primary outcomes, we conducted a systematic review of the use of and clinical outcomes measured by mobile devices (mobile outcomes) in observational and interventional clinical research. Method: We conducted a PubMed search using a range of search terms to retrieve peer-reviewed articles on clinical research published between January 2010 and May 2016 in which mobile devices were used to measure study outcomes. We screened each publication for specific inclusion and exclusion criteria. We then identified and qualitatively summarized the use of mobile outcome assessments in clinical research, including the type and design of the study, therapeutic focus, type of mobile device(s) used, and specific mobile outcomes reported. Results: The search retrieved 2,530 potential articles of interest. After screening, 88 publications remained. Twenty-five percent of the publications (n = 22) described mobile outcomes used in interventional research, and the rest (n = 66) described observational clinical research. Thirteen therapeutic areas were represented. Five categories of mobile devices were identified: (1) inertial sensors, (2) biosensors, (3) pressure sensors and walkways, (4) medication adherence monitors, and (5) location monitors; inertial sensors/accelerometers were most common (reported in 86% of the publications). Among the variety of mobile outcomes, various assessments of physical activity were most common (reported in 74% of the publications). Other mobile outcomes included assessments of sleep, mobility, and pill adherence, as well as biomarkers assessed using a mobile device, including cardiac measures, glucose, gastric reflux, respiratory measures, and intensity of head-related injury. Conclusion: Mobile devices are being widely used in clinical research to assess outcomes, although their use in interventional research to assess therapeutic effectiveness is limited. For mobile devices to be used more frequently in pivotal interventional research – such as trials informing regulatory decision-making – more focus should be placed on: (1) consolidating the evidence supporting the clinical meaningfulness of specific mobile outcomes, and (2) standardizing the use of mobile devices in clinical research to measure specific mobile outcomes (e.g., data capture frequencies, placement of device). To that aim, this manuscript offers a broad overview of the various mobile outcome assessments currently used in observational and interventional research, and categorizes and consolidates this information for researchers interested in using mobile devices to assess outcomes in interventional research.