New Tool Helps Predict Preterm Birth, Neonatal Problems

By Megan Brooks

January 20, 2021

NEW YORK (Reuters Health) - Progesterone metabolites in plasma coupled with patient factors can help identify pregnant women at risk for preterm delivery and neonatal morbidity, researchers report.

This research "breaks new ground," by demonstrating that 11-deoxycorticosterone (DOC) and 16-alpha-hydroxyprogesterone (16-alpha-OHP) in plasma can predict the extent of preterm delivery-associated neonatal morbidity and length of neonatal hospitalization when measured early in pregnancy, Dr. Avinash Patil of the University of Arizona College of Medicine in Phoenix told Reuters Health by email.

"Previously, much of the research in obstetrics focused purely on predicting gestational age at delivery as a surrogate (estimate) for neonatal outcomes," he said. "The findings of this research are particularly applicable to value-based healthcare models, which are increasingly prevalent for maternity care. The ability to screen a population of pregnancies and identify those at risk for poor neonatal outcomes can decrease healthcare costs while improving the health of newborns."

An imbalance of progesterone metabolism has been linked to an increased risk of preterm delivery. In a prior study, Dr. Patil and his colleagues found that DOC and 16-alpha-OHP, when measured during the late first trimester/early second trimester, can predict a woman's risk for spontaneous preterm delivery prior to 32 weeks.

In the new study in PLOS ONE, they set out to determine if obstetric and demographic variables known during the pregnancy, when combined with these steroid-metabolite biomarkers obtained early in pregnancy, could predict the risk of preterm-delivery-associated neonatal morbidity in a low-risk population of pregnant women.

The researchers quantified the two progesterone metabolites using mass spectroscopy from plasma of 58 pregnant women collected in the late first trimester or early second trimester. They combined the steroid-level data with patient demographic and obstetric history data in multivariable logistic regression models.

Forty of the pregnant women delivered preterm (<37 weeks) and 18 delivered at term (greater than or equal to 37 weeks). Ten women had elevated Hassan scores of 2 or higher, with the remaining 48 had scores of zero to one.

Women delivering babies with an elevated Hassan score of two to four were more likely to have a higher BMI and deliver at a lower gestational age than peers delivering babies with a low Hassan score.

Neonates with an elevated Hassan score were born at a lower gestational age and birthweight, were more likely to receive antenatal corticosteroids, have a lower five-minute Apgar score, and require resuscitative measures at birth compared to babies with a low Hassan score.

The final neonatal morbidity model, which incorporated antenatal corticosteroid exposure and fetal sex, was able to predict high morbidity (a Hassan scale score of 2 or higher) with an area under the ROC curve (AUROC) of 0.975, with an optimal sensitivity of 90% and specificity of 96%. The final model characteristics included a positive predictive value (PPV) of 0.82 and negative predictive value (NPV) of 0.98.

With the addition of the two biomarkers to the final model, the positive likelihood ratio for neonatal morbidity as measured with a Hassan Score of two to four was 21.6 (95% confidence interval, 5.48 to 85.21) for women with a positive test result.

Newborns of women who screened positive with the model had significantly longer median length of hospital stays compared with newborns of women who screened negative (53 days vs. 4.5 days; P=0.0017).

The researchers caution that this "discovery work and findings need to be validated in an independent cohort before we can fully implicate the changes in these biomarkers with preterm birth and neonatal morbidity."

"The test is not yet clinic ready," Dr. Patil told Reuters Health. "Steps that remain include validation of the results and meeting federal guidelines for development of new tests. The biomarkers in the study are very promising, so we are pushing forward to accomplish these milestones and make a new test reality.

Dr. Patil is founder and CEO of Nixxi, a company focused on improving women's health and pregnancy outcomes, and is an inventor on a related patent application.

SOURCE: PLOS ONE, online January 6, 2021.