EP17.07: Comparison of different methods of screening for preterm pre‐eclampsia

To compare the predictive performance for pre-eclampsia (PE) of 3 different first trimester mathematical models of screening, which combine maternal risk factors with mean arterial pressure (MAP), uterine artery pulsatility index (UtPI) and serum placental growth factor (PlGF), and 2 risk scoring systems, the NICE and ACOG recommendations. Prospective cohort study performed in 8 Spanish hospitals. All women with singleton, non-malformed live fetuses attending their 11-13 weeks scan were invited to participate. Maternal factors were recorded, measurements of MAP, UtPI, PlGF and PAPP-A were converted into MoM. Risks for term, preterm-PE(< 37 wks) and early-PE(< 34 wks) were calculated according to the FMF competing risks model, the Crovetto et al, logistic regression model, and Serra et al, Gaussian model. Patient classification based on NICE and ACOG guidelines was performed. We estimated detection rates (DR) at a fixed 10% screen positive rate (SPR), and the area under the receiver operating characteristic curve for preterm-PE, early-PE, and all PE for the 3 mathematical models. For the scoring systems, we calculated DR and SPR. Risk calibration was also assessed. 10110 singleton pregnancies were included, 32 (0.3%) developed early-PE, 72 (0.7%) preterm-PE, and 230 (2.3%) any PE. At fixed 10% SPR, the FMF, Crovetto, and Serra, detected 82.7% (95% CI 69.6-95.8%), 73.8% (95% CI 58.7-88.9%), and 79.8% (95% CI 66.1-93.5%) of early-PE; 72.7% (95% CI 62.9-82.6%), 69.2% (95% CI 58.8-79.6%), and 74.1% (95% CI 64.2-83.9%) of preterm-PE and 55.1% (95% CI 48.8-61.4%), 47.1% (95% CI 40.6-53.5%), and 53.9% (95% CI 47.4-60.4%) of all PE, respectively. The FMF model achieved the best correlation between predicted and observed cases. The NICE criteria identified 46.7% (95% CI 35.3-58.0%) of preterm-PE at 11% SPR and ACOG criteria identified 65.9% (95% CI 55.4-76.4%) of preterm-PE at 33.8% SPR. While all 3 algorithms show similar results in terms of overall prediction and outperformed the scoring systems, the FMF model showed the best performance at the individual level.