Cargando…

Predictors of the Outcomes Following the Tocilizumab Treatment for Severe COVID-19

Background: Tocilizumab is used in severe COVID-19 yet has significant rates of treatment failure. Objectives: This retrospective study aimed to identify early predictors of the response to tocilizumab therapy. Methods: Biochemical and clinical characteristics of adult patients who received tocilizu...

Descripción completa

Detalles Bibliográficos
Autores principales: Singla, Karan, Puri, Goverdhan D, Guha Niyogi, Subhrashis, Mahajan, Varun, Kajal, Kamal, Bhalla, Ashish
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cureus 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9509663/
https://www.ncbi.nlm.nih.gov/pubmed/36176874
http://dx.doi.org/10.7759/cureus.28428
_version_ 1784797277099917312
author Singla, Karan
Puri, Goverdhan D
Guha Niyogi, Subhrashis
Mahajan, Varun
Kajal, Kamal
Bhalla, Ashish
author_facet Singla, Karan
Puri, Goverdhan D
Guha Niyogi, Subhrashis
Mahajan, Varun
Kajal, Kamal
Bhalla, Ashish
author_sort Singla, Karan
collection PubMed
description Background: Tocilizumab is used in severe COVID-19 yet has significant rates of treatment failure. Objectives: This retrospective study aimed to identify early predictors of the response to tocilizumab therapy. Methods: Biochemical and clinical characteristics of adult patients who received tocilizumab for severe COVID-19 pneumonia were retrospectively examined. A multivariable logistic regression model was constructed to identify factors that could predict the failure of tocilizumab therapy. A predictive nomogram was also created using the selected model. Results: Out of 101 eligible patients, 30 had treatment failure, and 71 survived on a 28-day follow-up. The partial pressure of oxygen to fraction of inspired oxygen ratio (PFR) on the day of tocilizumab administration (100 vs 80.5), lactate dehydrogenase (LDH; 668 vs 507 U/L), neutrophil-to-lymphocyte ratio (NL ratio; 24.7 vs 10), and creatine kinase myocardial band (CKMB; 30.9 vs 22.7 U/L) were significantly different among the non-survivors and survivors, respectively. A logistic regression model was created, identifying LDH, NL ratio, pro-brain natriuretic peptide (ProBNP), and PFR on the day of tocilizumab administration as best predictors of mortality with an optimism-corrected area under the receiver operator characteristics (ROC) curve of 0.82. The model-implied odds ratios for mortality were 1.89 (95% CI 1.13-3.15) for every 100 U/L rise in serum LDH, 2.29 (95% CI 2.2-4.39) for every 10 unit rise in NL ratio, 1.23 (95% CI 0.95-1.58) for every 100 pg/ml increase in ProBNP, and 0.36 (95% CI 0.13-0.95) for every mmHg rise in PFR at intervention. Conclusion: This study identified NL ratio, LDH, CKMB, and PFR at intervention as important markers of risk of treatment failure following the tocilizumab therapy. A multivariable logistic regression model including LDH, NL ratio, ProBNP, and PFR at intervention best predicted the risk of mortality in patients with severe COVID-19 pneumonia treated with tocilizumab.
format Online
Article
Text
id pubmed-9509663
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Cureus
record_format MEDLINE/PubMed
spelling pubmed-95096632022-09-28 Predictors of the Outcomes Following the Tocilizumab Treatment for Severe COVID-19 Singla, Karan Puri, Goverdhan D Guha Niyogi, Subhrashis Mahajan, Varun Kajal, Kamal Bhalla, Ashish Cureus Anesthesiology Background: Tocilizumab is used in severe COVID-19 yet has significant rates of treatment failure. Objectives: This retrospective study aimed to identify early predictors of the response to tocilizumab therapy. Methods: Biochemical and clinical characteristics of adult patients who received tocilizumab for severe COVID-19 pneumonia were retrospectively examined. A multivariable logistic regression model was constructed to identify factors that could predict the failure of tocilizumab therapy. A predictive nomogram was also created using the selected model. Results: Out of 101 eligible patients, 30 had treatment failure, and 71 survived on a 28-day follow-up. The partial pressure of oxygen to fraction of inspired oxygen ratio (PFR) on the day of tocilizumab administration (100 vs 80.5), lactate dehydrogenase (LDH; 668 vs 507 U/L), neutrophil-to-lymphocyte ratio (NL ratio; 24.7 vs 10), and creatine kinase myocardial band (CKMB; 30.9 vs 22.7 U/L) were significantly different among the non-survivors and survivors, respectively. A logistic regression model was created, identifying LDH, NL ratio, pro-brain natriuretic peptide (ProBNP), and PFR on the day of tocilizumab administration as best predictors of mortality with an optimism-corrected area under the receiver operator characteristics (ROC) curve of 0.82. The model-implied odds ratios for mortality were 1.89 (95% CI 1.13-3.15) for every 100 U/L rise in serum LDH, 2.29 (95% CI 2.2-4.39) for every 10 unit rise in NL ratio, 1.23 (95% CI 0.95-1.58) for every 100 pg/ml increase in ProBNP, and 0.36 (95% CI 0.13-0.95) for every mmHg rise in PFR at intervention. Conclusion: This study identified NL ratio, LDH, CKMB, and PFR at intervention as important markers of risk of treatment failure following the tocilizumab therapy. A multivariable logistic regression model including LDH, NL ratio, ProBNP, and PFR at intervention best predicted the risk of mortality in patients with severe COVID-19 pneumonia treated with tocilizumab. Cureus 2022-08-26 /pmc/articles/PMC9509663/ /pubmed/36176874 http://dx.doi.org/10.7759/cureus.28428 Text en Copyright © 2022, Singla et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Anesthesiology
Singla, Karan
Puri, Goverdhan D
Guha Niyogi, Subhrashis
Mahajan, Varun
Kajal, Kamal
Bhalla, Ashish
Predictors of the Outcomes Following the Tocilizumab Treatment for Severe COVID-19
title Predictors of the Outcomes Following the Tocilizumab Treatment for Severe COVID-19
title_full Predictors of the Outcomes Following the Tocilizumab Treatment for Severe COVID-19
title_fullStr Predictors of the Outcomes Following the Tocilizumab Treatment for Severe COVID-19
title_full_unstemmed Predictors of the Outcomes Following the Tocilizumab Treatment for Severe COVID-19
title_short Predictors of the Outcomes Following the Tocilizumab Treatment for Severe COVID-19
title_sort predictors of the outcomes following the tocilizumab treatment for severe covid-19
topic Anesthesiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9509663/
https://www.ncbi.nlm.nih.gov/pubmed/36176874
http://dx.doi.org/10.7759/cureus.28428
work_keys_str_mv AT singlakaran predictorsoftheoutcomesfollowingthetocilizumabtreatmentforseverecovid19
AT purigoverdhand predictorsoftheoutcomesfollowingthetocilizumabtreatmentforseverecovid19
AT guhaniyogisubhrashis predictorsoftheoutcomesfollowingthetocilizumabtreatmentforseverecovid19
AT mahajanvarun predictorsoftheoutcomesfollowingthetocilizumabtreatmentforseverecovid19
AT kajalkamal predictorsoftheoutcomesfollowingthetocilizumabtreatmentforseverecovid19
AT bhallaashish predictorsoftheoutcomesfollowingthetocilizumabtreatmentforseverecovid19