Analysis of Predictive Information From Biomarkers Added to Clinical Models of Preeclampsia: Consideration of PAPP-A2, Activin A, and sFlt-1:PlGF Ratio.

Background: Preeclampsia remains a major cause of maternal and fetal adverse outcomes in pregnancy; however, accurate and universally acceptable predictive tools remain elusive. We investigated whether a panel of biomarkers could improve risk prediction for preeclampsia when measured at various pregnancy time points.

Methods: In this prospective cohort study, 192 women with first-trimester high-risk singleton pregnancies were consecutively recruited from tertiary obstetrics clinics in Montréal, Canada. Clinical information (height, pre-pregnancy weight, personal and family medical history, medication use) was collected at baseline. Blood pressure was measured and blood samples collected at each trimester to quantify soluble Fms-like tyrosine kinase 1 (sFlt-1), placental growth factor (PlGF), pregnancy-associated plasma protein A2 (PAPP-A2), PAPP-A, activin A, inhibin A, follistatin, and glycosylated fibronectin. A random-effects hierarchic logistic regression model was used to relate change in biomarker levels to incidence of preeclampsia.

Results: When added to a clinical model composed of maternal age, pre-pregnancy body mass index, race, and mean arterial pressure, a positive third-trimester result for both PAPP-A2 and activin A had a better positive predictive value than the sFlt-1:PlGF ratio added to the clinical model (91.67% [95% confidence interval (CI) 78.57%-100%] vs 66.67% [57.14%-100%]), while maintaining a comparable high negative predictive value (97.69% [95% CI 95.34%-100%] vs 96.00% [92.19%-99.21%]).

Conclusions: Whereas the third-trimester sFlt-1:PlGF ratio can predict short-term absence of preeclampsia, PAPP-A2 and activin A had both high positive and negative predictive values and therefore could serve as biomarkers to predict the occurrence (and absence) of preeclampsia; these findings will be validated in future studies.