Competing risks model in screening for preeclampsia by maternal factors and biomarkers at 30-34 weeks’ gestation

Background:Preeclampsia (PE) affects 2-3% of all pregnancies and is a major cause of maternal and perinatal morbidity and mortality. We have proposed a two-stage strategy for identification of pregnancies at high-risk of developing PE. The objective of the first stage, at 11-13 weeks’ gestation, is reduction in the prevalence of the disease through pharmacological intervention in the high-risk group. The objective of the second-stage, during the second and / or third trimesters, is to improve perinatal outcome through close monitoring of the high-risk group for earlier diagnosis of the clinical signs of the disease and selection of the appropriate, time, place and method of delivery. 
Objective:To examine the performance of screening for PE by a combination of maternal factors with early third-trimester biomarkers. Study Design This was a cohort study and data were derived from consecutive women with singleton pregnancies attending for their routine hospital visit at 30-34 weeks’ gestation in three maternity hospitals in England between March 2011 and December 2014. In the first phase of the study, only uterine artery pulsatility index (UTPI) was measured, then measurement of mean arterial pressure (MAP) was added and in the final phase serum concentration of placental growth factor (PLGF) was measured and then soluble fms-like tyrosine kinase-1 (SFLT) was added. We had data on UTPI, MAP, PLGF and SFLT from 30,935, 29,042, 10,123 and 8,264 pregnancies, respectively. Bayes theorem was used to combine the a priori risk from maternal factors with various combinations of biomarker multiple of the median (MoM) values. Ten-fold cross validation was used to estimate the performance of screening for PE requiring delivery at <37 weeks’ gestation (preterm-PE) and those delivering at >37 weeks (term-PE). The empirical performance was compared to model predictions. 
Results:In pregnancies that developed PE, the values of MAP, UTPI and SFLT were increased and PLGF was decreased. For all biomarkers the deviation from normal was greater for preterm-PE than term-PE and therefore the performance of screening was inversely related to the gestational age at which delivery become necessary for maternal and or fetal indications. Combined screening by maternal factors, MAP, UTPI, PLGF and SFLT predicted 98% (95% confidence interval 88 to 100%) of preterm-PE and 49% (95% confidence interval 42 to 57%) of term-PE, at false positive rate (FPR) of 5%. These empirical detection rates are compatible with the respective model-based rates of 98% and 54%, but the latter were optimistically biased. 
Conclusion:Combination of maternal factors and biomarkers in the early third-trimester could predict nearly all cases of preterm-PE and half of those with term-PE, at 5% FPR.