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

被引:34
|
作者
Pearce, B. D. [1 ]
Grove, J. [3 ]
Bonney, E. A. [4 ]
Bliwise, N. [2 ]
Dudley, D. J. [5 ]
Schendel, D. E. [6 ]
Thorsen, P. [7 ]
机构
[1] Emory Univ, Rollins Sch Publ Hlth, Dept Epidemiol, Atlanta, GA 30322 USA
[2] Emory Univ, Dept Psychol, Atlanta, GA 30322 USA
[3] Univ Aarhus, Inst Publ Hlth, Res Ctr, Dept Human Genet & Bioinformat, DK-8000 Aarhus C, Denmark
[4] Univ Vermont, Dept Obstet & Gynecol, Burlington, VT USA
[5] Univ Texas Hlth Sci Ctr San Antonio, Dept Obstet & Gynecol, San Antonio, TX 78229 USA
[6] Ctr Dis Control & Prevent NCBDDD, Atlanta, GA USA
[7] Drexel Univ, Dept Epidemiol & Biostat, Sch Publ Hlth, Philadelphia, PA 19104 USA
关键词
Stress; Corticotropin-releasing hormone; Inflammation; Neuroendocrine; Interleukin-6; MIGRATION INHIBITORY FACTOR; C-REACTIVE-PROTEIN; NECROSIS-FACTOR-ALPHA; EARLY-PREGNANCY; ASSOCIATION; WOMEN; MODEL; RISK;
D O I
10.1159/000284949
中图分类号
R71 [妇产科学];
学科分类号
100211 ;
摘要
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-alpha 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 cut-off. 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 (C) 2010 S. Karger AG, Basel
引用
收藏
页码:40 / 46
页数:7
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