Distinguishing bacterial versus non-bacterial causes of febrile illness – A systematic review of host biomarkers. Issue 4 (April 2021) - Leticia Fernandez-Carballo, B.; Escadafal, Camille; MacLean, Emily; Kapasi, Anokhi J.; Dittrich, Sabine
Highlights: 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. Graphical abstract: Image, graphical abstract