Competing risks model in screening for preeclampsia by maternal characteristics and medical history

Abstract

Objective: The purpose of this study was to develop a model for preeclampsia based on maternal demographic characteristics and medical history.

Study design: This was a screening study of 120,492 singleton pregnancies at 11-13 weeks' gestation, including 2704 pregnancies (2.2%) that experienced preeclampsia. A survival-time model for the gestational age at delivery with preeclampsia was developed from variables of maternal characteristics and history. This approach assumes that, if the pregnancy was to continue indefinitely, all women would experience preeclampsia and that whether they do so or not before a specified gestational age depends on competition between delivery before or after development of preeclampsia. A 5-fold cross validation study was conducted to compare the performance of the new model with the National Institute for Health and Clinical Excellence (NICE) guidelines.

Results: In the new model, increased risk for preeclampsia, with a consequent shift in the Gaussian distribution of the gestational age at delivery with preeclampsia to the left, is provided by advancing maternal age, increasing weight, Afro-Caribbean and South Asian racial origin, medical history of chronic hypertension, diabetes mellitus and systemic lupus erythematosus or antiphospholipid syndrome, family history and personal history of preeclampsia, and conception by in vitro fertilization. The risk for preeclampsia decreases with increasing maternal height and in parous women with no previous preeclampsia; in the latter, the protective effect, which is related inversely to the interpregnancy interval, persists beyond 15 years. At a screen-positive rate of 11%, as defined by NICE, the new model predicted 40%, 48%, and 54% of cases of total preeclampsia and preeclampsia requiring delivery at <37 and <34 weeks' gestation, respectively, which were significantly higher than the respective values of 35%, 40%, and 44% achieved by application of NICE guidelines.

Conclusion: A new model that is based on maternal characteristics and medical history has been developed for the estimation of patient-specific risks for preeclampsia. Such estimation of the a priori risk for preeclampsia is an essential first step in the use of Bayes theorem to combine maternal factors with biomarkers for the continuing development of more effective methods of screening for the disease.

Keywords: Bayes theorem; preeclampsia; pregnancy; screening; survival-time model.