Objective: To describe the priors and decision thresholds in phase 2 and 3 RCTs evaluating drug efficacy using Bayesian methods.
Study Design And Setting: A systematic review of phase 2 and 3 RCTs evaluating drug efficacy through Bayesian inference was conducted across the MEDLINE, EMBASE and Cochrane databases, with no date restrictions until September 2022. The type of prior used for the analysis of the primary endpoint and its characteristics (type and parameters of the distribution, justification, sensitivity analysis), the use of a posterior probability decision threshold defined a priori, and its value, were extracted.
Background: Trastuzumab emtansine has been recently suspected to be associated with the development of pulmonary arterial hypertension (PAH).
Research Question: Is there an association between trastuzumab, trastuzumab emtansine, or trastuzumab deruxtecan and the development of PAH?.
Study Design And Methods: Characteristics of incident PAH cases treated with trastuzumab, trastuzumab emtansine, or trastuzumab deruxtecan were analyzed from the French PH Registry, the VIGIAPATH program, concurrently with a pharmacovigilance disproportionality analysis using the World Health Organization pharmacovigilance database using a broad definition of pulmonary hypertension (PH) and a narrow definition of PAH.
We aim to discover new safety signals of drug-induced sleep apnoea (SA), a global health problem affecting approximately 1 billion people worldwide. We first conducted a series of sequence symmetry analyses (SSA) in a cohort composed from all patients who received a first SA diagnosis or treatment between 2006 and 2018 in the Echantillon Généraliste des Bénéficaires (EGB), a random sample of the French healthcare database. We used two primary outcomes to estimate the sequence ratio (SR) for all drug classes available in France: a sensitive one (diagnosis or treatment of SA) and a specific one (Positive Airway Pressure (PAP) therapy).
View Article and Find Full Text PDFIntroduction: Pulmonary arterial hypertension (PAH) is a rare and severe disease for which most of the evidence about prognostic factors, evolution and treatment efficacy comes from cohorts, registries and clinical trials. We therefore aimed to develop and validate a new PAH identification algorithm that can be used in the French healthcare database "Système National des Données de Santé (SNDS)".
Methods: We developed and validated the algorithm using the Grenoble Alpes University Hospital medical charts.