Objective: To examine the diagnostic accuracy of a previously developed model for prediction of pre-eclampsia (PE) by a combination of maternal factors and biomarkers at 11-13 weeks' gestation.
Methods: This was a prospective first-trimester multicenter study of screening for PE in 8775 singleton pregnancies. A previously published algorithm was used for the calculation of patient-specific risk of PE in each individual. The detection rates (DRs) and false-positive rates (FPRs) for delivery with PE < 32, < 37 and ≥ 37 weeks were estimated and compared with those for the dataset used for development of the algorithm.
Results: In the study population, 239 (2.7%) cases developed PE, of which 17 (0.2%), 59 (0.7%) and 180 (2.1%) developed PE < 32, < 37 and ≥ 37 weeks, respectively. With combined screening by maternal factors, mean arterial pressure, uterine artery pulsatility index and serum placental growth factor, the DR was 100% (95% CI, 80-100%) for PE < 32 weeks, 75% (95% CI, 62-85%) for PE < 37 weeks and 43% (95% CI, 35-50%) for PE ≥ 37 weeks, at a 10% FPR. These DRs were similar to the estimated rates for the dataset used for development of the model: 89% (95% CI, 79-96%) for PE < 32 weeks, 75% (95% CI, 70-80%) for PE < 37 weeks and 47% (95% CI, 44-51%) for PE ≥ 37 weeks.
Conclusion: Assessment of a combination of maternal factors and biomarkers at 11-13 weeks provides effective first-trimester screening for preterm PE. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.
Keywords: Bayes' theorem; first-trimester screening; mean arterial pressure; placental growth factor; pre-eclampsia; pregnancy-associated plasma protein-A; pyramid of pregnancy care; survival model; uterine artery Doppler.
Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.