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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 (< 10th, < 5th or < 3rd 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 < 10th percentile (SGA < 10th) and preterm SGA with birth weight < 5th percentile (SGA < 5th), 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 < 3rd percentile (SGA < 3rd) (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 < 10th and preterm SGA < 5th, 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 < 3rd 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 < 10th, preterm SGA < 5th and preterm SGA < 3rd, 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. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR]

This article discusses a study that evaluated the performance of a machine learning model for predicting pre-eclampsia (PE) in a large Asian population. The study used data from 10,935 women with singleton pregnancies and applied the machine learning model for first trimester screening. The results showed that after adjusting for biochemical marker analyzers, the predictive performance of the model was comparable to that of the Fetal Medicine Foundation competing risk model in Asian populations. This study suggests that the machine learning model could be a useful tool for predicting PE in Asian populations. [Extracted from the article]

Objectives: To (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.Methods: This 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.Results: In 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.Conclusions: Owing 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. [ABSTRACT FROM AUTHOR]