Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/214193
Title: | Bayesian analysis of the ICAT·COVID randomized clinical trial |
Author: | Malchair, Pierre Villoria, Jesús Giol, Jordi Jacob, Javier Carnaval, Thiago Videla, Sebastián |
Keywords: | Estadística bayesiana COVID-19 SARS-CoV-2 Bayesian statistical decision COVID-19 SARS-CoV-2 |
Issue Date: | Feb-2024 |
Publisher: | Elsevier B.V. |
Abstract: | This communication provides new effect measures in the multiplicative scale from the ICAT·COVID randomized clinical trial, obtained through Bayesian statistics. These could not be calculated using the traditional frequentist statistics included in the original publication because the benefits of icatibant (a competitive antagonist of the bradykinin B2 receptors) on top of standard care in patients with COVID-19 pneumonia were such that there were no events in the active group.1 Additive effect measures (eg, risk differences) are the most appropriate measures for identifying the population groups that will benefit most from interventions in presence of interactions acting as effect modifiers.2 However, an aspect that multiplicative measures provide where additive effect measures cannot, is an indication of how many times interventions or exposures increase or decrease disease risk (eg, risk ratio, hazard ratio). Furthermore, multiplicative measures are more commonly used in epidemiology, and are more appropriate for outcome measures with strictly positive values, such as counts and the numerators of incidence rates. |
Note: | Reproducció del document publicat a: https://doi.org/10.1016/j.clinthera.2023.11.010 |
It is part of: | Clinical Therapeutics, 2024, vol. 46, num.2, p. 176-180 |
URI: | http://hdl.handle.net/2445/214193 |
Related resource: | https://doi.org/10.1016/j.clinthera.2023.11.010 |
ISSN: | 0149-2918 |
Appears in Collections: | Articles publicats en revistes (Ciències Clíniques) Articles publicats en revistes (Institut d'lnvestigació Biomèdica de Bellvitge (IDIBELL)) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
854911.pdf | 1.25 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License