Prospective validation study of prognostic biomarkers to predict adverse outcomes in patients with COVID-19: a study protocol.

Abstract

INTRODUCTION:

Accurate triage is an important first step to effectively manage the clinical treatment of severe cases in a pandemic outbreak. In the current COVID-19 global pandemic, there is a lack of reliable clinical tools to assist clinicians to perform accurate triage. Host response biomarkers have recently shown promise in risk stratification of disease progression; however, the role of these biomarkers in predicting disease progression in patients with COVID-19 is unknown. Here, we present a protocol outlining a prospective validation study to evaluate the biomarkers' performance in predicting clinical outcomes of patients with COVID-19.

METHODS AND ANALYSIS:

This prospective validation study assesses patients infected with COVID-19, in whom blood samples are prospectively collected. Recruited patients include a range of infection severity from asymptomatic to critically ill patients, recruited from the community, outpatient clinics, emergency departments and hospitals. Study samples consist of peripheral blood samples collected into RNA-preserving (PAXgene/Tempus) tubes on patient presentation or immediately on study enrolment. Real-time PCR (RT-PCR) will be performed on total RNA extracted from collected blood samples using primers specific to host response gene expression biomarkers that have been previously identified in studies of respiratory viral infections. The RT-PCR data will be analysed to assess the diagnostic performance of individual biomarkers in predicting COVID-19-related outcomes, such as viral pneumonia, acute respiratory distress syndrome or bacterial pneumonia. Biomarker performance will be evaluated using sensitivity, specificity, positive and negative predictive values, likelihood ratios and area under the receiver operating characteristic curve.

ETHICS AND DISSEMINATION:

This research protocol aims to study the host response gene expression biomarkers in severe respiratory viral infections with a pandemic potential (COVID-19). It has been approved by the local ethics committee with approval number 2020/ETH00886. The results of this project will be disseminated in international peer-reviewed scientific journals.

• Authors: Benjamin Tang, Maryam Shojaei, Ya Wang, Marek Nalos, Anthony Mclean, Ali Afrasiabi, Tim N Kwan, Win Sen Kuan, Yoann Zerbib, Velma Herwanto, Gunawan Gunawan, Davide Bedognetti, Gabriele Zoppoli, Alberto Ballestrero, Darawan Rinchai, Paolo Cremonesi, Michele Bedognetti, Martin Matejovic, Thomas Karvunidis, Stephen P J Macdonald, Amanda J Cox, Nicholas P West, Allan William Cripps, Klaus Schughart, Andrea de Maria, Damien Chaussabel, Jonathan Iredell, Stephen Weng, PREDICT-19 consortium
• Journal: BMJ open (BMJ Open) Vol. 11 Issue 1 Pg. e044497 (01 06 2021) ISSN: 2044-6055 [Electronic] England
• PMID: 33408218 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't, Validation Study)
• Copyright: © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Chemical References

• Biomarkers

Topics

• Adult
• Biomarkers (metabolism)
• COVID-19 (epidemiology, metabolism)
• Critical Illness (epidemiology)
• Emergency Service, Hospital (statistics & numerical data)
• Female
• Follow-Up Studies
• Humans
• Male
• Middle Aged
• Pandemics
• Prognosis
• Prospective Studies
• SARS-CoV-2
• Time Factors
• Triage (methods)