Publications by authors named "P Janiaud"

This paper reviews the scientific evidence on new anti-amyloid monoclonal antibodies for treating Alzheimer's disease as a case study for improving scientific evidence communication. We introduce five guidelines condensed from the biomedical evidence literature but adapted to the short format of science communication in e.g.

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Conducting systematic reviews of clinical trials is arduous and resource consuming. One potential solution is to design databases that are continuously and automatically populated with clinical trial data from harmonised and structured datasets. We aimed to map publicly available, continuously updated, topic-specific databases of randomised clinical trials (RCTs).

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Background And Objectives: Over half a century ago, the terms "pragmatic" and "explanatory" were introduced to biomedicine by Schwartz and Lellouch, presenting two distinct conceptual approaches to trial design. Today, we frequently say that there are pragmatic trials and there are explanatory trials. Pragmatic trials inform decision-making in practice, and explanatory trials aim to understand the mechanism of an intervention.

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Article Synopsis
  • The study assesses the effectiveness of large language models (LLMs) in evaluating scientific research reports and systematic reviews compared to human raters, using established criteria like PRISMA, AMSTAR, and PRECIS-2.
  • Five LLMs were tested across a total of 168 systematic reviews and clinical trials, revealing that while individual LLMs showed lower accuracy (ranging from 38% to 74%), combined LLM ratings improved that accuracy significantly.
  • The most accurate results came from human and AI collaboration, which achieved accuracies between 80% and 96%, suggesting that integrating human judgment with AI technology enhances the appraisal process more than either can do alone.
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Background: Treatment decisions for persons with relapsing-remitting multiple sclerosis (RRMS) rely on clinical and radiological disease activity, the benefit-harm profile of drug therapy, and preferences of patients and physicians. However, there is limited evidence to support evidence-based personalized decision-making on how to adapt disease-modifying therapy treatments targeting no evidence of disease activity, while achieving better patient-relevant outcomes, fewer adverse events, and improved care. Serum neurofilament light chain (sNfL) is a sensitive measure of disease activity that captures and prognosticates disease worsening in RRMS.

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