title: Mathematical Modeling of the Biomarker Milieu to Characterize Preterm Birth and Predict Adverse Neonatal Outcomes.
abstract: OBJECTIVE
  To identify preterm neonates at risk for adverse neonatal outcomes.
  
  
  METHODS
  A nested case-control study from the prospectively followed Boston Birth Cohort of mother-neonate pairs was performed. A classification model for preterm-born neonates was derived from 27 cord blood biomarkers using orthogonal projections to latent structures discriminant analysis. Predictive relationships were made between biomarkers and adverse outcomes using logistic regression.
  
  
  RESULTS
  From 926 births (53% of which were preterm), using weighted values for 27 biomarkers, a score was created that classified 73% of preterm deliveries. Soluble TNF-R1, NT-3, MCP-1, BDNF, IL-4, MMP-9, TREM-1, TNF-α, IL-5 and IL-10 were most influential. Our model was more sensitive for birth <34 weeks (sensitivity 89.5%, specificity 76.9%). IL-10, TNF-α, BDNF, NT-3, MMP-9, sTNF-R1 and MCP-1 were significantly predictive of NEC, IVH, sepsis and infections.
  
  
  CONCLUSIONS
  We developed a novel mathematical model of 27 biomarkers associated with adverse neonatal outcomes in neonates born preterm.
authors.affiliation: Integrated Research Center for Fetal Medicine, Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors.forename: Christina N
authors.initials: CN
authors.lastname: Cordeiro
authors.affiliation: Center for Child and Community Health Research, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors.forename: Yulia
authors.initials: Y
authors.lastname: Savva
authors.affiliation: Johns Hopkins University School of Medicine, Baltimore, MD, USA.|Department of Medicine, Department of Population, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA.
authors.forename: Dhananjay
authors.initials: D
authors.lastname: Vaidya
authors.affiliation: Integrated Research Center for Fetal Medicine, Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors.forename: Cynthia H
authors.initials: CH
authors.lastname: Argani
authors.affiliation: Department of Medicine, Department of Population, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA.
authors.forename: Xiumei
authors.initials: X
authors.lastname: Hong
authors.affiliation: Department of Medicine, Department of Population, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA.
authors.forename: Xiaobin
authors.initials: X
authors.lastname: Wang
authors.affiliation: Integrated Research Center for Fetal Medicine, Department of Gynecology and Obstetrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors.forename: Irina
authors.initials: I
authors.lastname: Burd
mesh_terms: D015415:Biomarkers / Q000378:metabolism; D016022:Case-Control Studies; D015331:Cohort Studies; D020345:Enterocolitis, Necrotizing / Q000175:diagnosis*; D006801:Humans; D007231:Infant, Newborn; D007232:Infant, Newborn, Diseases / Q000175:diagnosis*; D016753:Interleukin-10 / Q000378:metabolism; D008962:Models, Theoretical; D047928:Premature Birth / Q000175:diagnosis*; D011379:Prognosis; D011446:Prospective Studies; D047888:Receptors, Tumor Necrosis Factor, Type I / Q000378:metabolism; D012680:Sensitivity and Specificity; D018805:Sepsis / Q000175:diagnosis*
chemical_list: D015415:Biomarkers; D047888:Receptors, Tumor Necrosis Factor, Type I; D016753:Interleukin-10
keywords: Cytokines; mathematical model; neonatal brain injury; neonatal sepsis; preterm birth