B Leticia Fernandez-Carballo1, Camille Escadafal2, Emily MacLean3, Anokhi J Kapasi2, Sabine Dittrich4. 1. Foundation for Innovative New Diagnostics (FIND), Chemin des Mines 9, Geneva, Switzerland. Electronic address: Leticia.fernandez@finddx.org. 2. Foundation for Innovative New Diagnostics (FIND), Chemin des Mines 9, Geneva, Switzerland. 3. Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, 1020 av des Pins O, Montreal, QC H3A 1A2, Canada. 4. Foundation for Innovative New Diagnostics (FIND), Chemin des Mines 9, Geneva, Switzerland; Nuffield Department of Medicine, University of Oxford, Oxford, UK.
Abstract
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.
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 humanparticipants 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.
Authors: Arjun Chandna; Melissa Richard-Greenblatt; Richard Tustin; Sue J Lee; Kevin C Kain; Sakib Burza; Yoel Lubell; Paul Turner Journal: Am J Trop Med Hyg Date: 2022-04-18 Impact factor: 3.707
Authors: Jan Torzewski; Patrizia Brunner; Wolfgang Ries; Christoph D Garlichs; Stefan Kayser; Franz Heigl; Ahmed Sheriff Journal: J Clin Med Date: 2022-03-23 Impact factor: 4.241