Objective: To examine the external validity of the Fetal Medicine Foundation (FMF) competing-risks model for the prediction of small-for-gestational age (SGA) at 11-14 weeks' gestation in an Asian population. Methods: This was a secondary analysis of a multicenter prospective cohort study in 10 120 women with a singleton pregnancy undergoing routine assessment at 11-14 weeks' gestation. We applied the FMF competing-risks model for the first-trimester prediction of SGA, combining maternal characteristics and medical history with measurements of mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI) and serum placental growth factor (PlGF) concentration. We calculated risks for different cut-offs of birth-weight percentile (< 10(th) , < 5(th) or < 3(rd) percentile) and gestational age at delivery (< 37 weeks (preterm SGA) or SGA at any gestational age). Predictive performance was examined in terms of discrimination and calibration. Results: The predictive performance of the competing-risks model for SGA was similar to that reported in the original FMF study. Specifically, the combination of maternal factors with MAP, UtA-PI and PlGF yielded the best performance for the prediction of preterm SGA with birth weight < 10(th) percentile (SGA < 10(th) ) and preterm SGA with birth weight < 5(th) percentile (SGA < 5(th) ), with areas under the receiver-operating-characteristics curve (AUCs) of 0.765 (95% CI, 0.720-0.809) and 0.789 (95% CI, 0.736-0.841), respectively. Combining maternal factors with MAP and PlGF yielded the best model for predicting preterm SGA with birth weight < 3(rd) percentile (SGA < 3(rd) ) (AUC, 0.797 (95% CI, 0.744-0.850)). After excluding cases with pre-eclampsia, the combination of maternal factors with MAP, UtA-PI and PlGF yielded the best performance for the prediction of preterm SGA < 10(th) and preterm SGA < 5(th) , with AUCs of 0.743 (95% CI, 0.691-0.795) and 0.762 (95% CI, 0.700-0.824), respectively. However, the best model for predicting preterm SGA < 3(rd) without pre-eclampsia was the combination of maternal factors and PlGF (AUC, 0.786 (95% CI, 0.723-0.849)). The FMF competing-risks model including maternal factors, MAP, UtA-PI and PlGF achieved detection rates of 42.2%, 47.3% and 48.1%, at a fixed false-positive rate of 10%, for the prediction of preterm SGA < 10(th) , preterm SGA < 5(th) and preterm SGA < 3(rd) , respectively. The calibration of the model was satisfactory. Conclusion: The screening performance of the FMF first-trimester competing-risks model for SGA in a large, independent cohort of Asian women is comparable with that reported in the original FMF study in a mixed European population. (c) 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

To examine the screening performance of a previously developed first-trimester prediction model for pre-eclampsia (PE) in an unselected Asian population. This was a prospective, multicentre study in 5445 singleton pregnancies at 11-13 weeks in seven recruiting centres in China, Hong Kong, Japan, Singapore, Taiwan and Thailand during January 2017 until January 2018. Maternal factors, and measurements of mean arterial pressure (MAP) by validated automated devices, mean uterine artery pulsatility index (UtPI) by transabdominal colour Doppler ultrasonography and maternal serum placental growth factor (PlGF) concentration were recorded. Previously published algorithms were used for converting the measured values of MAP, UtPI, and PlGF into multiples of median (MoMs). The FMF algorithm was used for the calculation of patient-specific risk of PE in each patient. The area under the receiver-operating characteristics curve (AUC), detection rates (DRs) and false positive rates (FPRs) for PE with delivery at < 37 (preterm-PE) and > 37 weeks (term-PE) were estimated based the algorithm. In the 5445 cases there were 113 (2.1%) cases that developed PE, including 32 cases (0.6%) of preterm-PE and 81 cases (1.4%) of term-PE. In screening by maternal factors, AUC and DR at 9.5% FPR for preterm-PE were 0.764 (95% CI 0.667-0.862) and 39.1% (95% CI 19.7-61.5), respectively. Using combined screening with maternal factors with biomarkers, the performance of screening improved to AUC 0.872 (95% CI 0.787-0.956) and DR 73.9% (95% CI 51.6-89.8) at 13.3% FPR. For term-PE, maternal factors alone achieved AUC of 0.718 (95% CI 0.648-0.788) and DR 30.8% (95% CI 18.7-45.1) at 9.0% FPR and combined screening achieved AUC of 0.802 (95% CI 0.749-0.854) and DR 44.2% (95% CI 30.5-58.7) at 10.2% FPR. This is the first study to validate PE prediction model in an unselected Asian population. Effective first-trimester screening for preterm-PE can be achieved with the use of the FMF model.

ABSTRACTObjectivesTo (i) evaluate the applicability of the European‐derived biomarker multiples of the median (MoM) formulae for risk assessment of preterm pre‐eclampsia (PE) in seven Asian populations, spanning the east, southeast and south regions of the continent, (ii) perform quality‐assurance (QA) assessment of the biomarker measurements and (iii) establish criteria for prospective ongoing QA assessment of biomarker measurements.MethodsThis was a prospective, non‐intervention, multicenter study in 4023 singleton pregnancies, at 11 to 13 + 6 weeks' gestation, in 11 recruiting centers in China, Hong Kong, India, Japan, Singapore, Taiwan and Thailand. Women were screened for preterm PE between December 2016 and June 2018 and gave written informed consent to participate in the study. Maternal and pregnancy characteristics were recorded and mean arterial pressure (MAP), mean uterine artery pulsatility index (UtA‐PI) and maternal serum placental growth factor (PlGF) were measured in accordance with The Fetal Medicine Foundation (FMF) standardized measurement protocols. MAP, UtA‐PI and PlGF were transformed into MoMs using the published FMF formulae, derived from a largely Caucasian population in Europe, which adjust for gestational age and covariates that affect directly the biomarker levels. Variations in biomarker MoM values and their dispersion (SD) and cumulative sum tests over time were evaluated in order to identify systematic deviations in biomarker measurements from the expected distributions.ResultsIn the total screened population, the median (95% CI) MoM values of MAP, UtA‐PI and PlGF were 0.961 (0.956–0.965), 1.018 (0.996–1.030) and 0.891 (0.861–0.909), respectively. Women in this largely Asian cohort had approximately 4% and 11% lower MAP and PlGF MoM levels, respectively, compared with those expected from normal median formulae, based on a largely Caucasian population, whilst UtA‐PI MoM values were similar. UtA‐PI and PlGF MoMs were beyond the 0.4 to 2.5 MoM range (truncation limits) in 16 (0.4%) and 256 (6.4%) pregnancies, respectively. QA assessment tools indicated that women in all centers had consistently lower MAP MoM values than expected, but were within 10% of the expected value. UtA‐PI MoM values were within 10% of the expected value at all sites except one. Most PlGF MoM values were systematically 10% lower than the expected value, except for those derived from a South Asian population, which were 37% higher.ConclusionsOwing to the anthropometric differences in Asian compared with Caucasian women, significant differences in biomarker MoM values for PE screening, particularly MAP and PlGF MoMs, were noted in Asian populations compared with the expected values based on European‐derived formulae. If reliable and consistent patient‐specific risks for preterm PE are to be reported, adjustment for additional factors or development of Asian‐specific formulae for the calculation of biomarker MoMs is required. We have also demonstrated the importance and need for regular quality assessment of biomarker values. Copyright © 2019 ISUOG. Published by John Wiley & Sons Ltd.