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Competing risks model in screening for preeclampsia by maternal factors and biomarkers at 11-13 weeks gestation
Neil O'Gorman1, David Wright2, Argyro Syngelaki1
1Harris Birthright Research Centre for Fetal Medicine, King's College, London, UK.
Insights
This study developed an effective first-trimester screening model for preeclampsia using maternal factors and biomarkers. The combined approach significantly improves detection rates for preterm-preeclampsia.
Area of Science:
- Obstetrics and Gynecology
- Maternal-Fetal Medicine
- Biomarker Discovery
Background:
- Preeclampsia affects 3% of pregnancies, causing significant maternal and perinatal mortality.
- Early screening aims to reduce preeclampsia prevalence through first-trimester pharmacologic intervention.
- Developing effective screening tools is crucial for managing this high-risk condition.
Purpose of the Study:
- To develop a predictive model for preeclampsia.
- The model integrates maternal demographic characteristics, medical history (maternal factors), and specific biomarkers.
- The goal is to enable early identification of high-risk pregnancies.
Main Methods:
- Prospective screening of 35,948 singleton pregnancies at 11-13 weeks gestation.
- Utilized Bayes theorem to combine maternal risk factors with biomarkers: uterine artery pulsatility index, mean arterial pressure, pregnancy-associated plasma protein-A, and placental growth factor.
- Assessed model performance using five-fold cross-validation for preterm and term preeclampsia detection.
Main Results:
- Combined screening with maternal factors, uterine artery pulsatility index, mean arterial pressure, and placental growth factor achieved 75% detection for preterm-preeclampsia and 47% for term-preeclampsia (at 10% false-positive rate).
- These detection rates surpass those from screening with maternal factors alone (49% and 38%, respectively).
- Pregnancy-associated plasma protein-A inclusion did not enhance screening performance; deviations in biomarkers were more pronounced in early-onset preeclampsia.
Conclusions:
- Combining maternal factors with specific biomarkers offers an effective method for first-trimester screening of preeclampsia, particularly for preterm cases.
- The developed model demonstrates superior predictive performance compared to traditional screening methods.
- This approach supports early intervention strategies for high-risk pregnancies.
Background:
Preeclampsia affects approximately 3% of all pregnancies and is a major cause of maternal and perinatal morbidity and death. In the last decade, extensive research has been devoted to early screening for preeclampsia with the aim of reducing the prevalence of the disease through pharmacologic intervention in the high-risk group starting from the first trimester of pregnancy.
Objective:
The purpose of this study was to develop a model for preeclampsia based on maternal demographic characteristics and medical history (maternal factors) and biomarkers.
Study Design:
The data for this study were derived from prospective screening for adverse obstetric outcomes in women who attended for their routine first hospital visit at 11-13 weeks gestation in 2 maternity hospitals in England. We screened 35,948 singleton pregnancies that included 1058 pregnancies (2.9%) that experienced preeclampsia. Bayes theorem was used to combine the a priori risk from maternal factors with various combinations of uterine artery pulsatility index, mean arterial pressure, serum pregnancy-associated plasma protein-A, and placental growth factor multiple of the median values. Five-fold cross validation was used to assess the performance of screening for preeclampsia that delivered at <37 weeks gestation (preterm-preeclampsia) and ≥37 weeks gestation (term-preeclampsia) by models that combined maternal factors with individual biomarkers and their combination with screening by maternal factors alone.
Results:
In pregnancies that experienced preeclampsia, the values of uterine artery pulsatility index and mean arterial pressure were increased, and the values of serum pregnancy-associated plasma protein-A and placental growth factor were decreased. For all biomarkers, the deviation from normal was greater for early than late preeclampsia; therefore, the performance of screening was related inversely to the gestational age at which delivery became necessary for maternal and/or fetal indications. Combined screening by maternal factors, uterine artery pulsatility index, mean arterial pressure, and placental growth factor predicted 75% (95% confidence interval, 70-80%) of preterm-preeclampsia and 47% (95% confidence interval, 44-51%) of term-preeclampsia, at a false-positive rate of 10%; inclusion of pregnancy-associated plasma protein-A did not improve the performance of screening. Such detection rates are superior to the respective values of 49% (95% confidence interval, 43-55%) and 38% (34-41%) that were achieved by screening with maternal factors alone.
Conclusion:
Combination of maternal factors and biomarkers provides effective first-trimester screening for preterm-preeclampsia.
