Screening for pre‐eclampsia early in pregnancy: performance of a multivariable model combining clinical characteristics and biochemical markers

Objective To investigate the performance of a multivariable model combining a priori clinical characteristics and biomarkers to detect, early in pregnancy, women at higher risk of developing pre‐eclampsia ( PE ). Design Nested case–control study. Setting University medical centre, Q uebec, C anada ( CHU de Q uébec). Population A total of 7929 pregnant women recruited between 10 and 18 weeks of gestation. In all, 350 developed hypertensive disorders of pregnancy ( HDP )—of which 139 had PE , comprising 68 with severe PE and 47 with preterm PE —and were matched with two women with a normal pregnancy. Methods We selected a priori clinical characteristics and promising markers to create multivariable logistic regression models: body mass index ( BMI ), mean arterial pressure ( MAP ), placental growth factor, soluble Fms‐like tyrosine kinase‐1, pregnancy‐associated plasma protein A and inhibin A. Main outcome measures PE , severe PE , preterm PE , HDP . Results At false‐positive rates of 5 and 10%, the estimated detection rates were between 15% (5–29%) and 32% (25–39%), and between 39% (19–59%) and 50% (34–66%), respectively. Considering the low prevalence of PE in this population, the positive predictive values were 7% (5–9%) to 10% (7–13%) for PE and 2% (1–4%) to 4% (3–6%) in the preterm and severe PE subgroups. The multivariable model yielded areas under the receiver operating characteristics curves ( AUC ) between 0.72 (0.61–0.81) and 0.78 (0.68–0.88). When only BMI and MAP were included in the model, the AUC were similar to those of the a priori model. Conclusions In a population with a low prevalence of preterm PE , a multivariable risk algorithm using an a priori combination of clinical characteristics and biochemical markers did not reach a performance justifying clinical implementation as screening test early in pregnancy.