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A Novel Framework for Phenotyping Children With Suspected or Confirmed Infection for Future Biomarker Studies
Ruud G Nijman1,2, Rianne Oostenbrink3, Henriette A Moll3
1Section of Pediatric Infectious Disease, Department of Infectious Disease, Faculty of Medicine, Imperial College of Science, Technology and Medicine, London, United Kingdom.
Frontiers in Pediatrics
|August 16, 2021
Summary
A new PERFORM classification algorithm improved biomarker accuracy for diagnosing serious bacterial infections (SBI) in children. This system offers a better framework for identifying bacterial infections in pediatric patients compared to current methods.
Area of Science:
- Pediatric Infectious Diseases
- Biomarker Discovery
- Clinical Diagnostics
Background:
- Accurate diagnosis of serious bacterial infections (SBI) in children is challenging due to limitations in current diagnostic standards.
- Biomarker accuracy for SBI detection in pediatric populations may be improved with refined classification systems.
- Existing methods for classifying infections in children often struggle with diagnostic uncertainty.
Purpose of the Study:
- To evaluate the diagnostic performance of a novel classification algorithm, PERFORM, for biomarker discovery in children at risk of SBI.
- To compare the efficacy of the PERFORM algorithm against traditional SBI classification using biomarkers like procalcitonin (PCT), NGAL, and resistin.
- To establish a new framework for phenotyping pediatric infections to enhance future biomarker studies.
Main Methods:
- Data from five prospective observational studies involving 3,582 children (0- <16 years) were analyzed.
- Biomarkers including procalcitonin (PCT), neutrophil gelatinase-associated lipocalin-2 (NGAL), and resistin were assessed.
- The PERFORM algorithm, with 11 categories based on clinical phenotype and test results, was compared to dichotomous SBI vs. non-SBI classification.
Main Results:
- The PERFORM classification system demonstrated higher diagnostic accuracy (AUCs) for biomarkers compared to the traditional SBI classification.
- For PCT, AUCs were 0.77 (PERFORM) vs. 0.70 (SBI); for NGAL, 0.80 vs. 0.70; and for resistin, 0.68 vs. 0.64.
- Combined biomarkers achieved an AUC of 0.83 for distinguishing definite bacterial from definite viral infections using the PERFORM algorithm.
Conclusions:
- Biomarkers for bacterial infection show strong association with diagnostic categories defined by the PERFORM classification system.
- The PERFORM algorithm provides a more nuanced and accurate framework for phenotyping children with suspected infections.
- This novel approach enhances the potential for reliable biomarker discovery and application in pediatric infectious disease diagnostics.
