A new model for screening for early-onset preeclampsia

Abstract

Background: Early identification of women with an increased risk for preeclampsia is of utmost importance to minimize adverse perinatal events. Models developed until now (mainly multiparametric algorithms) are thought to be overfitted to the derivation population, which may affect their reliability when applied to other populations. Options allowing adaptation to a variety of populations are needed.

Objective: The objective of the study was to assess the performance of a first-trimester multivariate Gaussian distribution model including maternal characteristics and biophysical/biochemical parameters for screening of early-onset preeclampsia (delivery <34 weeks of gestation) in a routine care low-risk setting.

Study design: Early-onset preeclampsia screening was undertaken in a prospective cohort of singleton pregnancies undergoing routine first-trimester screening (8 weeks 0/7 days to 13 weeks 6/7 days of gestation), mainly using a 2-step scheme, at 2 hospitals from March 2014 to September 2017. A multivariate Gaussian distribution model including maternal characteristics (a priori risk), serum pregnancy-associated plasma protein-A and placental growth factor assessed at 8 weeks 0/7 days to 13 weeks 6/7 days and mean arterial pressure and uterine artery pulsatility index measured at 11.0-13.6 weeks was used.

Results: A total of 7908 pregnancies underwent examination, of which 6893 were included in the analysis. Incidence of global preeclampsia was 2.3% (n = 161), while of early-onset preeclampsia was 0.2% (n = 17). The combination of maternal characteristics, biophysical parameters, and placental growth factor showed the best detection rate, which was 59% for a 5% false-positive rate and 94% for a 10% false-positive rate (area under the curve, 0.96, 95% confidence interval, 0.94-0.98). The addition of placental growth factor to biophysical markers significantly improved the detection rate from 59% to 94%.

Conclusion: The multivariate Gaussian distribution model including maternal factors, early placental growth factor determination (at 8 weeks 0/7 days to 13 weeks 6/7 days), and biophysical variables (mean arterial pressure and uterine artery pulsatility index) at 11 weeks 0/7 days to 13 weeks 6/7 days is a feasible tool for early-onset preeclampsia screening in the routine care setting. Performance of this model should be compared with predicting models based on regression analysis.

Keywords: Gaussian model; aspirin; biomarkers; early-onset preeclampsia; first-trimester screening; mean arterial pressure; placental growth factor; preeclampsia; pregnancy; pregnancy associated plasmatic protein-A; prevention; prospective cohort study; uterine artery pulsatility index.