Competing risks model in early screening for preeclampsia by biophysical and biochemical markers

Abstract

Objective: To develop models for prediction of preeclampsia (PE) based on maternal characteristics, biophysical and biochemical markers at 11-13 weeks' gestation in which the gestation at the time of delivery for PE is treated as a continuous variable.

Methods: This was a screening study of singleton pregnancies at 11-13 weeks including 1,426 (2.4%) that subsequently developed PE and 57,458 that were unaffected by PE. We developed a survival time model for the time of delivery for PE in which Bayes' theorem was used to combine the prior information from maternal characteristics with uterine artery pulsatility index (PI), mean arterial pressure (MAP), serum pregnancy-associated plasma protein-A (PAPP-A) and placental growth factor (PLGF) multiple of the median (MoM) values.

Results: In pregnancies with PE, there was a linear correlation between MoM values of uterine artery PI, MAP, PAPP-A and PLGF with gestational age at delivery and therefore the deviation from normal was greater for early than late PE for all four biomarkers. Screening by maternal characteristics, biophysical and biochemical markers detected 96% of cases of PE requiring delivery before 34 weeks and 54% of all cases of PE at a fixed false-positive rate of 10%.

Conclusions: A new model has been developed for effective first-trimester screening for PE.