Prediction of preeclampsia throughout gestation with maternal characteristics and biophysical and biochemical markers: a longitudinal study.

backgroundThe current approach to predict preeclampsia combines maternal risk factors and evidence from biophysical markers (mean arterial pressure, Doppler velocimetry of the uterine arteries) and maternal blood proteins (placental growth factor, soluble vascular endothelial growth factor receptor-1, pregnancy-associated plasma protein A). Such models require the transformation of biomarker data into multiples of the mean values by using population- and site-specific models. Previous studies have focused on a narrow window in gestation and have not included the maternal blood concentration of soluble endoglin, an important antiangiogenic factor up-regulated in preeclampsia.

objectiveThis study aimed (1) to develop models for the calculation of multiples of the mean values for mean arterial pressure and biochemical markers; (2) to build and assess the predictive models for preeclampsia based on maternal risk factors, the biophysical (mean arterial pressure) and biochemical (placental growth factor, soluble vascular endothelial growth factor receptor-1, and soluble endoglin) markers collected throughout pregnancy; and (3) to evaluate how prediction accuracy is affected by the presence of chronic hypertension and gestational age. STUDY

designThis longitudinal case-cohort study included 1150 pregnant women: women without preeclampsia with (n=49) and without chronic hypertension (n=871) and those who developed preeclampsia (n=166) or superimposed preeclampsia (n=64). Mean arterial pressure and immunoassay-based maternal plasma placental growth factor, soluble vascular endothelial growth factor receptor-1, and soluble endoglin concentrations were available throughout pregnancy (median of 5 observations per patient). A prior-risk model for preeclampsia was established by using Poisson regression based on maternal characteristics and obstetrical history. Next, multiple regression was used to fit biophysical and biochemical marker data as a function of maternal characteristics by using data collected at 8 to 15

results(1) The inclusion of soluble endoglin in prediction models for all preeclampsia, together with the prior-risk estimates, mean arterial pressure, placental growth factor, and soluble vascular endothelial growth factor receptor-1, increased the sensitivity (at a fixed false-positive rate of 10%) for early prediction of superimposed preeclampsia, with the largest increase (from 44% to 54%) noted at 20 to 23

conclusionWe introduced prediction models for preeclampsia throughout pregnancy. These models can be useful to identify women at risk during the first trimester who could benefit from aspirin treatment or later in pregnancy to inform patient management. Relative to prediction performance at 8 to 15