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Author Notes:

Brad D. Pearce, PhD, 1518-002-4AA (RSPH: Epidemiology), Grace C. Rollins Bldg, Emory University, Rollins School of Public Health, Atlanta, GA 30322 (USA), Tel. +1 404 727 4914, Fax +1 404 727 8737, E-Mail bpearce@emory.edu

Subject:

Research Funding:

This study was supported by a National Institute of Mental Health grant, 5 R21 MH068513-3 (to B.D.P.), a grant from the March of Dimes Foundation, New York (PERI-98), and a grant from NARSAD (B.D.P.).

Keywords:

  • Stress
  • Corticotropin-releasing hormone
  • Inflammation
  • Neuroendocrine
  • Interleukin-6

Interrelationship of Cytokines, Hypothalamic-Pituitary-Adrenal Axis Hormones, and Psychosocial Variables in the Prediction of Preterm Birth

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Journal Title:

Gynecologic and Obstetric Investigation

Volume:

Volume 70, Number 1

Publisher:

, Pages 40-46

Type of Work:

Article | Post-print: After Peer Review

Abstract:

Background/Aims To examine the relationship of biological mediators (cytokines, stress hormones), psychosocial, obstetric history, and demographic factors in the early prediction of preterm birth (PTB) using a comprehensive logistic regression model incorporating diverse risk factors. Methods In this prospective case-control study, maternal serum biomarkers were quantified at 9–23 weeks’ gestation in 60 women delivering at <37 weeks compared to 123 women delivering at term. Biomarker data were combined with maternal sociodemographic factors and stress data into regression models encompassing 22 preterm risk factors and 1st-order interactions. Results Among individual biomarkers, we found that macrophage migration inhibitory factor (MIF), interleukin-10, C-reactive protein (CRP), and tumor necrosis factor-α were statistically significant predictors of PTB at all cutoff levels tested (75th, 85th, and 90th percentiles). We fit multifactor models for PTB prediction at each biomarker cutoff. Our best models revealed that MIF, CRP, risk-taking behavior, and low educational attainment were consistent predictors of PTB at all biomarker cutoffs. The 75th percentile cutoff yielded the best predicting model with an area under the ROC curve of 0.808 (95% CI 0.743–0.874). Conclusion Our comprehensive models highlight the prominence of behavioral risk factors for PTB and point to MIF as a possible psychobiological mediator.

Copyright information:

© 2010 by S. Karger AG, Basel

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