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Updated: May 20, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
A competing risks model in early screening for preeclampsia
David Wright1, Ranjit Akolekar, Argyro Syngelaki
1School of Computing and Mathematics, Plymouth University, Plymouth, UK.
Objective:
It was the aim of this study to develop models for the prediction of preeclampsia (PE) based on maternal characteristics and biophysical markers at 11-13 weeks' gestation in which 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%) cases that subsequently developed PE and 57,458 cases 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 the uterine artery pulsatility index (PI) and the mean arterial pressure (MAP), using multiple of the median values.
Results:
The risk for PE increased with maternal age, weight, Afro-Caribbean and South Asian racial origin, previous pregnancy with PE, conception by in vitro fertilization and a medical history of chronic hypertension, type 2 diabetes mellitus as well as systemic lupus erythematosus or antiphospholipid syndrome. In pregnancies with PE, there was an inverse correlation between multiple of the median values of the uterine artery PI and MAP with gestational age at delivery. Screening by maternal characteristics, uterine artery PI and MAP detected 90% of PE cases requiring delivery before 34 weeks and 57% of all PE cases at a fixed false-positive rate of 10%.
Conclusions:
A new model has been developed for effective first-trimester screening for PE.
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