Distinguishing bacterial versus non-bacterial causes of febrile illness – A systematic review of host biomarkers - 02/04/21
, Camille Escadafal a, Emily MacLean b, Anokhi J. Kapasi a, Sabine Dittrich a, cHighlights |
• | Review focused on host biomarkers differentiating bacterial vs non-bacterial infections. |
• | Most promising biomarkers are protein and RNA signatures. |
• | Performance for most biomarkers is lower than the minimum TPP performance criteria. |
• | Most studies identified have high risk of bias based on a QUADAS-based criteria. |
• | Host biomarkers should be used as part of integrated management guidelines. |
Summary |
Background |
Acute febrile illnesses (AFIs) represent a major disease burden globally; however, the paucity of reliable, rapid point-of-care testing makes their diagnosis difficult. A simple tool for distinguishing bacterial versus non-bacterial infections would radically improve patient management and reduce indiscriminate antibiotic use. Diagnostic tests based on host biomarkers can play an important role here, and a target product profile (TPP) was developed to guide development.
Objectives |
To qualitatively evaluate host biomarkers that can distinguish bacterial from non-bacterial causes of AFI.
Data sources |
The PubMed database was systematically searched for relevant studies published between 2015 and 2019.
Study eligibility criteria |
Studies comparing diagnostic performances of host biomarkers in patients with bacterial versus non-bacterial infections were included.
Participants |
Studies involving human participants and/or human samples were included.
Methods |
We collected information following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A risk of bias assessment was performed, based on a modified QUADAS-2 (Quality Assessment of Diagnostic Accuracy Score 2).
Results |
We identified 1107 publications. Following screening, 55 publications were included, with 265 biomarker entries. Entries mostly comprised protein biomarkers (58.9%), followed by haematological, RNA, and metabolite biomarkers (15.5%, 8.7%, 12.5%). Sensitivity/specificity was reported for 45.7% of biomarker entries. We assessed a high overall risk of bias for most entries (75.8%). In studies with low/medium risk of bias, four biomarker entries tested in blood samples had sensitivity/specificity of more than 0.90/0.80. Only 12 additional biomarker entries were identified with sensitivity/specificity of more than 0.65/0.65.
Conclusions |
Most recently assessed biomarkers represent well-known biomarkers, e.g. C-reactive protein and procalcitonin. Some protein biomarkers with the highest reported performances include a combined biomarker signature (CRP, IP-10, and TRAIL) and human neutrophil lipocalin (HNL). Few new biomarkers are in the pipeline; however, some RNA signatures show promise. Further high-quality studies are needed to confirm these findings.
Le texte complet de cet article est disponible en PDF.Graphical abstract |
Plan
Vol 82 - N° 4
P. 1-10 - avril 2021 Retour au numéro
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- Editorial Board
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