March of Dimes Study

The delivery of infants before 37 weeks gestation is a leading cause of perinatal mortality and morbidity in the US. Traditional methods of predicting women at risk relying on obstetrical history or premonitory symptoms (detected clinically or by tocodynamometry) are neither sensitive nor specific. Recent approaches to predicting preterm delivery have included sonographic measurement of cervical length and various biochemical assays. Although more sensitive than traditional methods, none exhibit sufficient accuracy to warrant widespread use. We contend that the failure of current approaches to predicting preterm delivery reflects an inadequate understanding of the underlying pathogenesis. Clinical and experimental evidence support the concept that most cases of preterm delivery reflect four pathogenic processes, which share a common final biological pathway leading to uterine contractions and cervical changes with or without premature rupture of membranes. These pathogeneses are: 1) activation of the maternal or fetal hypothalamic-pituitary-adrenal axis; 2) decidual-chorioamniotic or systemic inflammation; 3) decidual hemorrhage (i.e., abruption); and, 4) pathologic distention of the uterus. This study seeks to combine the most useful biophysical and biochemical markers of such processes with optimal clinical and epidemiologic predictors into a composite, easily applied risk tool. This integrated approach will identify at-risk asymptomatic patients with high sensitivity, specificity, and positive and negative predictive values, and also ascertain underlying pathogenic processes to facilitate targeted therapy. To accomplish these goals, we will employ logistic regression and artificial neural network models to assess and apply the appropriate weight to the following:

• Markers of maternal-fetal hypothalamic-pituitary-adrenal axis activation caused by stress and/or early onset of physiological initiators of parturition: maternal psychosocial and physiological indicators of stress; epidemiologic and biological markers of physiologic initiation or uteroplacental vascular dysfunction. These markers include: serum levels of estriol, insulin-like growth factor-1 binding protein, human chorionic gonadotropin, and corticotropin releasing hormone; and uterine artery Doppler flow studies;
• Markers of decidual-chorioamniotic or systemic inflammation caused by ascending genitourinary tract or systemic infection: plasma and/or cervicovaginal interleukin-6 and -8, colony stimulating factor-1, Fas ligand, and vaginal pH and other evidence of bacterial vaginosis;
• Markers of decidual hemorrhage caused by coagulopathy, hypertension, smoking, cocaine use, and vascular lesions: vaginal occult blood, plasma immunoreactive tissue factor; and plasma thrombin-antithrombin-III complexes;
• Markers of pathologic uterine distention due to polyhydramnios, multifetal pregnancy, or uterine anomaly: Sonographic assessment of fetal number and amniotic fluid index, as well as a history of in utero diethylstilbestrol exposure and Müllerian duct anomalies; and,
• Markers of the final common pathway leading to fetal membrane and/or cervical extracellular matrix degradation and myometrial activation: the matrix metalloproteinases MMP-1 and -9, fetal fibronectin, and sonographic evidence of cervical shortening and funneling.

By combining these markers, we expect to produce a predictive model which is more robust than any existing method, and which identifies the relative contribution of each pathogenic process. Further analysis of this model using a neural network will enable us to identify asymptomatic patients destined to deliver preterm with high sensitivity, specificity, positive and negative predictive values, and to assess the relative contribution of each of the four distinct pathogeneses to this preterm delivery risk.