A robust Bayesian bias-adjusted random effects model for consideration of uncertainty about bias terms in evidence synthesis.

Meta-analysis is a statistical method used in evidence synthesis for combining, analyzing and summarizing studies that have the same target endpoint and aims to derive a pooled quantitative estimate using fixed and random effects models or network models. Differences among included studies depend on variations in target populations (ie, heterogeneity) and variations in study quality due to study design and execution (ie, bias). The risk of bias is usually assessed qualitatively using critical appraisal, and quantitative bias analysis can be used to evaluate the influence of bias on the quantity of interest. We propose a way to consider ignorance or ambiguity in how to quantify bias terms in a bias analysis by characterizing bias with imprecision (as bounds on probability) and use robust Bayesian analysis to estimate the overall effect. Robust Bayesian analysis is here seen as Bayesian updating performed over a set of coherent probability distributions, where the set emerges from a set of bias terms. We show how the set of bias terms can be specified based on judgments on the relative magnitude of biases (ie, low, unclear, and high risk of bias) in one or several domains of the Cochrane's risk of bias table. For illustration, we apply a robust Bayesian bias-adjusted random effects model to an already published meta-analysis on the effect of Rituximab for rheumatoid arthritis from the Cochrane Database of Systematic Reviews.

A suggestion for the quantification of precise and bounded probability to quantify epistemic uncertainty in scientific assessments.

An honest communication of uncertainty about quantities of interest enhances transparency in scientific assessments. To support this communication, risk assessors should choose appropriate ways to evaluate and characterize epistemic uncertainty. A full treatment of uncertainty requires methods that distinguish aleatory from epistemic uncertainty. Quantitative expressions for epistemic uncertainty are advantageous in scientific assessments because they are nonambiguous and enable individual uncertainties to be characterized and combined in a systematic way. Since 2019, the European Food Safety Authority (EFSA) recommends assessors to express epistemic uncertainty in conclusions of scientific assessments quantitatively by subjective probability. A subjective probability can be used to represent an expert judgment, which may or may not be updated using Bayes's rule to integrate evidence available for the assessment and could be either precise or approximate. Approximate (or bounded) probabilities may be enough for decision making and allow experts to reach agreement on certainty when they struggle to specify precise subjective probabilities. The difference between the lower and upper bound on a subjective probability can also be used to reflect someone's strength of knowledge. In this article, we demonstrate how to quantify uncertainty by bounded probability, and explicitly distinguish between epistemic and aleatory uncertainty, by means of robust Bayesian analysis, including standard Bayesian analysis through precise probability as a special case. For illustration, the two analyses are applied to an intake assessment.

Beneficial effects of oral administration of C-Phycocyanin and Phycocyanobilin in rodent models of experimental autoimmune encephalomyelitis.

The only three oral treatments currently available for multiple sclerosis (MS) target the relapsing forms of the disease and concerns regarding efficacy, safety and tolerability limit their use. Identifying novel oral disease-modifying therapies for MS, targeting both its inflammatory and neurodegenerative components is still a major goal. AIM: The scope of this study was to provide evidence that the oral administration of C-Phycocyanin (C-PC), the main biliprotein of the Spirulina platensis cyanobacteria and its tetrapyrrolic prosthetic group, Phycocyanobilin (PCB), exert ameliorating actions on rodent models of experimental autoimmune encephalomyelitis (EAE). MAIN METHODS: EAE was induced in Lewis rats using the spinal cord encephalitogen from Sprague Dawley rats and in C57BL6 mice with MOG35-55 peptide. Clinical signs, motor function, oxidative stress markers, cytokine levels by ELISA and transmission electron microscopy analysis were assessed. KEY FINDINGS: Either prophylactic or early therapeutic administration of C-PC to Lewis rats with EAE, significantly improved clinical signs and restored the motor function of the animals. Furthermore, C-PC positively modulated oxidative stress markers measured in brain homogenate and serum and protected the integrity of cerebral myelin sheaths as shown by transmission electron microscopy analysis. In C57BL/6 mice with EAE, PCB orally improved clinical status of the animals and reduced the expression levels of brain IL-6 and IFN-γ proinflammatory cytokines. SIGNIFICANCE: These results, for the first time, support the fact that both C-PC and PCB administered orally could potentially improve neuroinflammation, protect from demyelination and axonal loss, which may be translated into an improved quality of life for MS patients.

Comparative Neuroregenerative Effects of C-Phycocyanin and IFN-Beta in a Model of Multiple Sclerosis in Mice.

Multiple Sclerosis (MS) therapies approved so far are unable to effectively reverse the chronic phase of the disease or improve the remyelination process. Here our aim is to evaluate the effects of C-Phycocyanin (C-Pc), a biliprotein from Spirulina platensis with anti-oxidant, anti-inflammatory and cytoprotective properties, in a chronic model of experimental autoimmune encephalomyelitis (EAE) in mice. C-Pc (2, 4 or 8 mg/kg i.p.) or IFN-beta (2000 IU, s.c.) was administered daily once a day or every other day, respectively, starting at disease onset, which differ among EAE mice between 11 and 15 days postinduction. Histological and immunohistochemistry (anti-Mac-3, anti-CD3 and anti-APP) assessments were performed in spinal cord in the postinduction time. Global gene expression in the brain was analyzed with the Illumina Mouse WG-6_V2 BeadChip microarray and the expression of particular genes, assessed by qPCR using the Fast SYBR Green RT-PCR Master Mix. Oxidative stress parameters (malondialdehyde, peroxidation potential, CAT/SOD ratio and GSH) were determined spectrophoto-metrically. Results showed that C-Pc ameliorates the clinical deterioration of animals, an effect that expresses the reduction of the inflammatory infiltrates invading the spinal cord tissue, the axonal preservation and the down-regulation of IL-17 expression in brain tissue and serum. C-Pc and IFN-beta improved the redox status in mice subjected to EAE, while microarray analysis showed that both treatments shared a common subset of differentially expressed genes, although they also differentially modulated another subset of genes. Specifically, C-Pc mainly modulated the expression of genes related to remyelination, gliogenesis and axon-glia processes. Taken together, our results indicate that C-Pc has significant therapeutic effects against EAE, mediated by the dynamic regulation of multiple biological processes.