title: Which Variables Are Useful for Predicting Severe Infection in Children With Febrile Neutropenia?
abstract: To distinguish children with chemotherapy-induced febrile neutropenia (FN) at low risk of severe infection, the variables that are significant risk factors must be identified. Our objective was to identify them by applying evidence-based standards. This retrospective 2-center cohort study included all episodes of chemotherapy-induced FN in children in 2005 and 2006. The medical history, clinical, and laboratory data available at admission were collected. Severe infection was defined by bacteremia, a positive culture of a normally sterile body fluid, invasive fungal infection, or localized infection at high risk of extension. Univariate analysis identified potential predictive variables. A generalized mixed model was used to determine the adjusted variables that predict severe infection. We analyzed 372 FN episodes. Severe infections occurred in 16.1% of them. Variables predictive of severe infection at admission were: disease with high risk of prolonged neutropenia (adjusted odds ratio [aOR]=2.5), blood cancer (aOR=1.9), fever ≥38.5°C (aOR=3.7), and C-reactive protein level ≥90 mg/L (aOR=4.5). Now that we have identified these variables significantly associated with the risk of severe infection, they must be validated prospectively before combining the best predictive variables in a decision rule that can be used to distinguish children at low risk.
authors.affiliation: *Lille-2 University and EA2694, Public Health, Epidemiology and Quality of Care †UDSL ‡Centre Hospitalier Régional Universitaire, CHRU Lille, Pediatric Hematology Unit §Pediatric Oncology Unit, Oscar Lambret Cancer Centre ∥CERIM (EA2694), Lille-2 University ¶Centre Hospitalier Régional Universitaire, CHRU Lille, Pediatric Emergency and Infectious Diseases Unit, Lille, France.
authors.forename: Mathilde
authors.initials: M
authors.lastname: Delebarre
authors.forename: Nathalie
authors.initials: N
authors.lastname: Garnier
authors.forename: Emilie
authors.initials: E
authors.lastname: Macher
authors.forename: Estelle
authors.initials: E
authors.lastname: Thebaud
authors.forename: Françoise
authors.initials: F
authors.lastname: Mazingue
authors.forename: Pierre
authors.initials: P
authors.lastname: Leblond
authors.forename: Alain
authors.initials: A
authors.lastname: Duhamel
authors.forename: Alain
authors.initials: A
authors.lastname: Martinot
authors.forename: François
authors.initials: F
authors.lastname: Dubos
mesh_terms: D000293:Adolescent; D000970:Antineoplastic Agents / Q000009:adverse effects; D015415:Biomarkers; D002097:C-Reactive Protein / Q000032:analysis; D016009:Chi-Square Distribution; D002648:Child; D002675:Child, Preschool; D066264:Datasets as Topic / Q000706:statistics & numerical data; D020000:Decision Support Systems, Clinical; D019317:Evidence-Based Medicine / Q000592:standards; D064147:Febrile Neutropenia / Q000097:blood / Q000139:chemically induced / Q000150:complications*; D005260:Female; D005602:France / Q000453:epidemiology; D006757:Hospital Units / Q000706:statistics & numerical data; D006785:Hospitals, University / Q000706:statistics & numerical data; D006801:Humans; D007223:Infant; D007239:Infections / Q000097:blood / Q000453:epidemiology* / Q000209:etiology; D008297:Male; D015999:Multivariate Analysis; D009369:Neoplasms / Q000150:complications / Q000188:drug therapy; D012372:ROC Curve; D012189:Retrospective Studies; D012306:Risk; D018709:Statistics, Nonparametric; D062606:Tertiary Care Centers / Q000706:statistics & numerical data
chemical_list: D000970:Antineoplastic Agents; D015415:Biomarkers; D002097:C-Reactive Protein