Gait and behavior in an IL1β-mediated model of rat knee arthritis and effects of an IL1 antagonist.

Interleukin-1 beta (IL1β) is a proinflammatory cytokine that mediates arthritic pathologies. Our objectives were to evaluate pain and limb dysfunction resulting from IL1β over-expression in the rat knee and to investigate the ability of local IL1 receptor antagonist (IL1Ra) delivery to reverse-associated pathology. IL1β over-expression was induced in the right knees of 30 Wistar rats via intra-articular injection of rat fibroblasts retrovirally infected with human IL1β cDNA. A subset of animals received a 30 µl intra-articular injection of saline or human IL1Ra on day 1 after cell delivery (0.65 µg/µl hIL1Ra, n = 7 per group). Joint swelling, gait, and sensitivity were investigated over 1 week. On day 8, animals were sacrificed and joints were collected for histological evaluation. Joint inflammation and elevated levels of endogenous IL1β were observed in knees receiving IL1β-infected fibroblasts. Asymmetric gaits favoring the affected limb and heightened mechanical sensitivity (allodynia) reflected a unilateral pathology. Histopathology revealed cartilage loss on the femoral groove and condyle of affected joints. Intra-articular IL1Ra injection failed to restore gait and sensitivity to preoperative levels and did not reduce cartilage degeneration observed in histopathology. Joint swelling and degeneration subsequent to IL1β over-expression is associated limb hypersensitivity and gait compensation. Intra-articular IL1Ra delivery did not result in marked improvement for this model; this may be driven by rapid clearance of administered IL1Ra from the joint space. These results motivate work to further investigate the behavioral consequences of monoarticular arthritis and sustained release drug delivery strategies for the joint space.

Quantifying data quality for clinical trials using electronic data capture.

BACKGROUND: Historically, only partial assessments of data quality have been performed in clinical trials, for which the most common method of measuring database error rates has been to compare the case report form (CRF) to database entries and count discrepancies. Importantly, errors arising from medical record abstraction and transcription are rarely evaluated as part of such quality assessments. Electronic Data Capture (EDC) technology has had a further impact, as paper CRFs typically leveraged for quality measurement are not used in EDC processes. METHODS AND PRINCIPAL FINDINGS: The National Institute on Drug Abuse Treatment Clinical Trials Network has developed, implemented, and evaluated methodology for holistically assessing data quality on EDC trials. We characterize the average source-to-database error rate (14.3 errors per 10,000 fields) for the first year of use of the new evaluation method. This error rate was significantly lower than the average of published error rates for source-to-database audits, and was similar to CRF-to-database error rates reported in the published literature. We attribute this largely to an absence of medical record abstraction on the trials we examined, and to an outpatient setting characterized by less acute patient conditions. CONCLUSIONS: Historically, medical record abstraction is the most significant source of error by an order of magnitude, and should be measured and managed during the course of clinical trials. Source-to-database error rates are highly dependent on the amount of structured data collection in the clinical setting and on the complexity of the medical record, dependencies that should be considered when developing data quality benchmarks.

Membrane binding of plasmid DNA and endocytic pathways are involved in electrotransfection of mammalian cells.

Electric field mediated gene delivery or electrotransfection is a widely used method in various studies ranging from basic cell biology research to clinical gene therapy. Yet, mechanisms of electrotransfection are still controversial. To this end, we investigated the dependence of electrotransfection efficiency (eTE) on binding of plasmid DNA (pDNA) to plasma membrane and how treatment of cells with three endocytic inhibitors (chlorpromazine, genistein, dynasore) or silencing of dynamin expression with specific, small interfering RNA (siRNA) would affect the eTE. Our data demonstrated that the presence of divalent cations (Ca(2+) and Mg(2+)) in electrotransfection buffer enhanced pDNA adsorption to cell membrane and consequently, this enhanced adsorption led to an increase in eTE, up to a certain threshold concentration for each cation. Trypsin treatment of cells at 10 min post electrotransfection stripped off membrane-bound pDNA and resulted in a significant reduction in eTE, indicating that the time period for complete cellular uptake of pDNA (between 10 and 40 min) far exceeded the lifetime of electric field-induced transient pores (∼10 msec) in the cell membrane. Furthermore, treatment of cells with the siRNA and all three pharmacological inhibitors yielded substantial and statistically significant reductions in the eTE. These findings suggest that electrotransfection depends on two mechanisms: (i) binding of pDNA to cell membrane and (ii) endocytosis of membrane-bound pDNA.

Impact of Funding Source on Clinical Trial Results Including Cardiovascular Outcome Trials.

Previous authors have suggested a higher likelihood for industry-sponsored (IS) studies to have positive outcomes than non-IS studies, though the influence of publication bias was believed to be a likely confounder. We attempted to control for the latter using a prepublication database to compare the primary outcome of recent trials based on sponsorship. We used the "advanced search" feature in the clinicaltrials.gov website to identify recently completed phase III studies involving the implementation of a pharmaceutical agent or device for which primary data were available. Studies were categorized as either National Institutes of Health (NIH) sponsored or IS. Results were labeled "favorable" if the results favored the intervention under investigation or "unfavorable" if the intervention fared worse than standard medical treatment. We also performed an independent literature search to identify the cardiovascular trials as a case example and again categorized them into IS versus NIH sponsored. A total of 226 studies sponsored by NIH were found. When these were compared with the latest 226 IS studies, it was found that IS studies were almost 4 times more likely to report a positive outcome (odds ratio [OR] 3.90, 95% confidence interval [CI] 2.6087 to 5.9680, p <0.0001). As a case example of a specialty, we also identified 25 NIH-sponsored and 215 IS cardiovascular trials, with most focusing on hypertension therapy (31.6%) and anticoagulation (17.9%). IS studies were 7 times more likely to report favorable outcomes (OR 7.54, 95% CI 2.19 to 25.94, p = 0.0014). They were also considerably less likely to report unfavorable outcomes (OR 0.11, 95% CI 0.04 to 0.26, p <0.0001). In conclusion, the outcomes of large clinical studies especially cardiovascular differ considerably on the basis of their funding source, and publication bias appears to have limited influence on these findings.

The IGNITE network: a model for genomic medicine implementation and research.

BACKGROUND: Patients, clinicians, researchers and payers are seeking to understand the value of using genomic information (as reflected by genotyping, sequencing, family history or other data) to inform clinical decision-making. However, challenges exist to widespread clinical implementation of genomic medicine, a prerequisite for developing evidence of its real-world utility. METHODS: To address these challenges, the National Institutes of Health-funded IGNITE (Implementing GeNomics In pracTicE; www.ignite-genomics.org ) Network, comprised of six projects and a coordinating center, was established in 2013 to support the development, investigation and dissemination of genomic medicine practice models that seamlessly integrate genomic data into the electronic health record and that deploy tools for point of care decision making. IGNITE site projects are aligned in their purpose of testing these models, but individual projects vary in scope and design, including exploring genetic markers for disease risk prediction and prevention, developing tools for using family history data, incorporating pharmacogenomic data into clinical care, refining disease diagnosis using sequence-based mutation discovery, and creating novel educational approaches. RESULTS: This paper describes the IGNITE Network and member projects, including network structure, collaborative initiatives, clinical decision support strategies, methods for return of genomic test results, and educational initiatives for patients and providers. Clinical and outcomes data from individual sites and network-wide projects are anticipated to begin being published over the next few years. CONCLUSIONS: The IGNITE Network is an innovative series of projects and pilot demonstrations aiming to enhance translation of validated actionable genomic information into clinical settings and develop and use measures of outcome in response to genome-based clinical interventions using a pragmatic framework to provide early data and proofs of concept on the utility of these interventions. Through these efforts and collaboration with other stakeholders, IGNITE is poised to have a significant impact on the acceleration of genomic information into medical practice.