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Validation of a host response test to distinguish bacterial and viral respiratory infection.

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Date
2019-10-17
Authors
Lydon, Emily C
Henao, Ricardo
Burke, Thomas W
Aydin, Mert
Nicholson, Bradly P
Glickman, Seth W
Fowler, Vance G
Quackenbush, Eugenia B
Cairns, Charles B
Kingsmore, Stephen F
Jaehne, Anja K
Rivers, Emanuel P
Langley, Raymond J
Petzold, Elizabeth
Ko, Emily R
McClain, Micah T
Ginsburg, Geoffrey S
Woods, Christopher W
Tsalik, Ephraim L
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(19 total)
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Abstract
BACKGROUND:Distinguishing bacterial and viral respiratory infections is challenging. Novel diagnostics based on differential host gene expression patterns are promising but have not been translated to a clinical platform nor extensively tested. Here, we validate a microarray-derived host response signature and explore performance in microbiology-negative and coinfection cases. METHODS:Subjects with acute respiratory illness were enrolled in participating emergency departments. Reference standard was an adjudicated diagnosis of bacterial infection, viral infection, both, or neither. An 87-transcript signature for distinguishing bacterial, viral, and noninfectious illness was measured from peripheral blood using RT-PCR. Performance characteristics were evaluated in subjects with confirmed bacterial, viral, or noninfectious illness. Subjects with bacterial-viral coinfection and microbiologically-negative suspected bacterial infection were also evaluated. Performance was compared to procalcitonin. FINDINGS:151 subjects with microbiologically confirmed, single-etiology illness were tested, yielding AUROCs 0•85-0•89 for bacterial, viral, and noninfectious illness. Accuracy was similar to procalcitonin (88% vs 83%, p = 0•23) for bacterial vs. non-bacterial infection. Whereas procalcitonin cannot distinguish viral from non-infectious illness, the RT-PCR test had 81% accuracy in making this determination. Bacterial-viral coinfection was subdivided. Among 19 subjects with bacterial superinfection, the RT-PCR test identified 95% as bacterial, compared to 68% with procalcitonin (p = 0•13). Among 12 subjects with bacterial infection superimposed on chronic viral infection, the RT-PCR test identified 83% as bacterial, identical to procalcitonin. 39 subjects had suspected bacterial infection; the RT-PCR test identified bacterial infection more frequently than procalcitonin (82% vs 64%, p = 0•02). INTERPRETATION:The RT-PCR test offered similar diagnostic performance to procalcitonin in some subgroups but offered better discrimination in others such as viral vs. non-infectious illness and bacterial/viral coinfection. Gene expression-based tests could impact decision-making for acute respiratory illness as well as a growing number of other infectious and non-infectious diseases.
Type
Journal article
Subject
Biomarkers
Coinfection
Diagnosis
Gene expression
Precision medicine
Respiratory tract infections
Permalink
https://hdl.handle.net/10161/19461
Published Version (Please cite this version)
10.1016/j.ebiom.2019.09.040
Publication Info
Lydon, Emily C; Henao, Ricardo; Burke, Thomas W; Aydin, Mert; Nicholson, Bradly P; Glickman, Seth W; ... Tsalik, Ephraim L (2019). Validation of a host response test to distinguish bacterial and viral respiratory infection. EBioMedicine. 10.1016/j.ebiom.2019.09.040. Retrieved from https://hdl.handle.net/10161/19461.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
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Scholars@Duke

Burke

Thomas Burke

Manager, Systems Project
Fowler

Vance Garrison Fowler Jr.

Florence McAlister Distinguished Professor of Medicine
Determinants of Outcome in Patients with Staphylococcus aureus Bacteremia Antibacterial ResistancePathogenesis of Bacterial Infections Tropical medicine/International Health
Ginsburg

Geoffrey Steven Ginsburg

Adjunct Professor in the Department of Medicine
Dr. Geoffrey S. Ginsburg's research interests are in the development of novel paradigms for developing and translating genomic information into medical practice and the integration of personalized medicine into health care.
Henao

Ricardo Henao

Assistant Professor in Biostatistics & Bioinformatics
Ko

Emily Ray Ko

Assistant Professor of Medicine
Clinical and translational research, COVID-19 therapeutics, clinical biomarkers for infectious disease, hospitalist
McClain

Micah Thomas McClain

Associate Professor of Medicine
Tsalik

Ephraim Tsalik

Adjunct Associate Professor in the Department of Medicine
My research is focused on understanding the dynamic between host and pathogen so as to discover and develop host-response markers that can diagnose and predict health and disease.  This new and evolving approach to diagnosing illness has the potential to significantly impact individual as well as public health considering the rise of antibiotic resistance. With any potential infectious disease diagnosis, it is difficult, if not impossible, to determine at the time of presentation
Woods

Christopher Wildrick Woods

Professor of Medicine
1. Emerging Infections 2. Global Health 3. Epidemiology of infectious diseases 4. Clinical microbiology and diagnostics 5. Bioterrorism Preparedness 6. Surveillance for communicable diseases 7. Antimicrobial resistance
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