A new meta-analysis posted to the medRxiv* preprint server reports that some of the biomarkers used to predict mortality due to the coronavirus disease 2019 (COVID-19) show variable efficacies in different parts of the world; therefore, these prognostic markers and scores cannot be generalized across regions.
Study: Non-generalizability of biomarkers for mortality in SARS-COV-2: A meta-analyses series. Image Credit: sfam_photo / Shutterstock.com
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the pathogen responsible for COVID-19, has infected over 654 million people worldwide and caused over 6.6 million deaths. In addition to the significant morbidity and mortality caused by COVID-19 and its associated burden on healthcare systems, the COVID-19 pandemic has also led to substantial economic and societal impacts worldwide.
When healthcare systems are overburdened, and resources are limited, the early prediction of disease outcomes is essential to identify high-risk patients. Furthermore, such predictive biomarkers can allow clinicians to customize treatment plans and delivery of care.
About the study
To date, several biomarkers have been shown to predict potential adverse outcomes of COVID-19. However, most prognostic models devised to predict SARS-CoV-2 in-hospital mortality did not perform consistently when tested against clinically similar cohorts.
The current study's authors examined possible reasons for these inconsistencies by conducting a meta-analysis. Here, reliable single-parameter biomarkers that could be easily measured and used to predict mortality in patients who have tested positive for COVID-19 were searched. This was proposed because a complete prognostic model cannot always calculate.
The PubMed database was searched for several keywords, including ‘SARS-CoV-2,’ ‘biomarker name,' and 'mortality.' In addition, a survey of all studies published between January 1, 2019, and June 30, 2021, was conducted.
The meta library in R was used to report the overall mean values and 95% confidence intervals for the data collected. For the European/North American, Asian, and overall datasets, the authors fitted a random effects model to obtain pooled areas under the curve (AUCs) and 95% confidence intervals.
A sensitivity analysis was conducted by serially excluding each study so that the effects of individual studies on the pooled AUC could be determined.
Biomarker effectiveness for mortality prediction with SARS-CoV-2 infection was found to vary significantly by geographical location. C-reactive protein (CRP) levels at admission provided a reliable mortality prediction in Asian countries, with a pooled AUC of 0.83 from 34 studies and 0.67 from 21 studies. Comparatively, this parameter was only an average predictor of mortality in Europe and North America.
At admission, D-dimer and interleukin 6 (IL-6) levels were also well-predicted mortality biomarkers in Asian countries but not in Europe and North America.
Nevertheless, two biomarkers, including troponin and urea, performed well across cohorts, regardless of geographical location.
Troponin levels at admission were 0.81 in Asian countries and 0.79 in European and North American countries. Similarly, urea levels on admission had a pooled AUC of 0.79 in Asian countries and 0.78 in European and North American countries.
Therefore, it is likely that end-organ damage at the time of presentation can effectively be used to predict SARS-CoV-2 severity.
SARS-CoV-2 biomarkers are commonly used worldwide; however, their effectiveness varies from region to region. For example, CRP and IL-6 levels were good predictive markers of mortality in Asian countries, whereas these parameters were not as effective in determining COVID-19 outcomes in Europe and North America.
The researchers conclude that combining results from Asian, European, and North American studies can mislead the public about the effectiveness of CRP, D-dimer, and IL-6 treatments. This observation is significant for clinicians who use biomarkers and/or prognostic scores derived in other regions to assist in decision-making, strategizing management, and planning admission to critical care, especially when upcoming COVID-19 waves threaten to disrupt local healthcare resources.
medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
- Shuvo, M. E. R., Schwiening, M., Soares, F., et al. (2022). Non-generalizability of biomarkers for mortality in SARS-COV-2: A meta-analyses series. medRxiv. doi:10.1101/2022.12.03.22282974. https://www.medrxiv.org/content/10.1101/2022.12.03.22282974v1.full-text.
Posted in: Medical Science News | Medical Research News | Disease/Infection News | Healthcare News
Tags: Biomarker, Coronavirus, Coronavirus Disease COVID-19, C-Reactive Protein, Critical Care, D-dimer, Healthcare, Hospital, Interleukin, Mortality, Pandemic, Pathogen, Protein, Respiratory, SARS, SARS-CoV-2, Severe Acute Respiratory, Severe Acute Respiratory Syndrome, Syndrome, Troponin
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