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The impact of tocilizumab on respiratory support states transition and clinical outcomes in COVID-19 patients. A Markov model multi-state study.

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Title: The impact of tocilizumab on respiratory support states transition and clinical outcomes in COVID-19 patients. A Markov model multi-state study.
Authors: Jovana Milic, Federico Banchelli, Marianna Meschiari, Erica Franceschini, Giacomo Ciusa, Licia Gozzi, Sara Volpi, Matteo Faltoni, Giacomo Franceschi, Vittorio Iadisernia, Dina Yaacoub, Giovanni Dolci, Erica Bacca, Carlotta Rogati, Marco Tutone, Giulia Burastero, Alessandro Raimondi, Marianna Menozzi, Gianluca Cuomo, Luca Corradi, Gabriella Orlando, Antonella Santoro, Margherita Digaetano, Cinzia Puzzolante, Federica Carli, Andrea Bedini, Stefano Busani, Massimo Girardis, Andrea Cossarizza, Rossella Miglio, Cristina Mussini, Giovanni Guaraldi, Roberto D'Amico
Source: PLoS ONE, Vol 16, Iss 8, p e0251378 (2021)
Publisher Information: Public Library of Science (PLoS), 2021.
Publication Year: 2021
Collection: LCC:Medicine
LCC:Science
Subject Terms: Medicine, Science
More Details: BackgroundThe benefit of tocilizumab on mortality and time to recovery in people with severe COVID pneumonia may depend on appropriate timing. The objective was to estimate the impact of tocilizumab administration on switching respiratory support states, mortality and time to recovery.MethodsIn an observational study, a continuous-time Markov multi-state model was used to describe the sequence of respiratory support states including: no respiratory support (NRS), oxygen therapy (OT), non-invasive ventilation (NIV) or invasive mechanical ventilation (IMV), OT in recovery, NRS in recovery.ResultsTwo hundred seventy-one consecutive adult patients were included in the analyses contributing to 695 transitions across states. The prevalence of patients in each respiratory support state was estimated with stack probability plots, comparing people treated with and without tocilizumab since the beginning of the OT state. A positive effect of tocilizumab on the probability of moving from the invasive and non-invasive mechanical NIV/IMV state to the OT in recovery state (HR = 2.6, 95% CI = 1.2-5.2) was observed. Furthermore, a reduced risk of death was observed in patients in NIV/IMV (HR = 0.3, 95% CI = 0.1-0.7) or in OT (HR = 0.1, 95% CI = 0.0-0.8) treated with tocilizumab.ConclusionTo conclude, we were able to show the positive impact of tocilizumab used in different disease stages depicted by respiratory support states. The use of the multi-state Markov model allowed to harmonize the heterogeneous mortality and recovery endpoints and summarize results with stack probability plots. This approach could inform randomized clinical trials regarding tocilizumab, support disease management and hospital decision making.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 1932-6203
Relation: https://doaj.org/toc/1932-6203
DOI: 10.1371/journal.pone.0251378
Access URL: https://doaj.org/article/76ab53450bd9487d864e78499269fdff
Accession Number: edsdoj.76ab53450bd9487d864e78499269fdff
Database: Directory of Open Access Journals
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  Data: BackgroundThe benefit of tocilizumab on mortality and time to recovery in people with severe COVID pneumonia may depend on appropriate timing. The objective was to estimate the impact of tocilizumab administration on switching respiratory support states, mortality and time to recovery.MethodsIn an observational study, a continuous-time Markov multi-state model was used to describe the sequence of respiratory support states including: no respiratory support (NRS), oxygen therapy (OT), non-invasive ventilation (NIV) or invasive mechanical ventilation (IMV), OT in recovery, NRS in recovery.ResultsTwo hundred seventy-one consecutive adult patients were included in the analyses contributing to 695 transitions across states. The prevalence of patients in each respiratory support state was estimated with stack probability plots, comparing people treated with and without tocilizumab since the beginning of the OT state. A positive effect of tocilizumab on the probability of moving from the invasive and non-invasive mechanical NIV/IMV state to the OT in recovery state (HR = 2.6, 95% CI = 1.2-5.2) was observed. Furthermore, a reduced risk of death was observed in patients in NIV/IMV (HR = 0.3, 95% CI = 0.1-0.7) or in OT (HR = 0.1, 95% CI = 0.0-0.8) treated with tocilizumab.ConclusionTo conclude, we were able to show the positive impact of tocilizumab used in different disease stages depicted by respiratory support states. The use of the multi-state Markov model allowed to harmonize the heterogeneous mortality and recovery endpoints and summarize results with stack probability plots. This approach could inform randomized clinical trials regarding tocilizumab, support disease management and hospital decision making.
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