Evaluation of screening performance of first-trimester competing-risks prediction model for small-for-gestational age in Asian population

New first trimester circulating angiogenic biomarkers in predicting early-onset and late-onset fetal growth restriction: a case-control study

BACKGROUND

First trimester prediction of fetal growth restriction (FGR) remain suboptimal. We aimed to search for new circulating angiogenic biomarkers for improvement.

METHODS

This case-control study compared 73 singleton pregnancies with early or late-onset FGR based on Delphi consensus and 73 matched normal controls. Their maternal serum samples stored during 11-13 weeks were retrieved for measurement of 36 angiogenic biomarkers by MILLIPLEX® human angiogenesis magnetic bead panels. Those biomarkers that showed significant differences between the study groups were further analysed with receiver operating characteristic (ROC) curve.

RESULTS

In the early-onset FGR group, log10MoM of soluble neuropilin-1 (sNRP-1: 0.08 ± 0.11 vs. 0.00 ± 0.09, P < 0.001) and log10MoM of soluble platelet and endothelial cell adhesion molecule 1 (sPECAM-1: 0.05 ± 0.06 vs. 0.00 ± 0.09, P < 0.05) were significantly higher than the control group, while log10MoM of platelet-derived growth factor AB/BB (PDGF-AB/BB: -0.08 ± 0.13 vs. 0.00 ± 0.16, P < 0.05) and PAPP-A (-0.15 ± 0.28 vs. 0.05 ± 0.23, P < 0.001) were lower. Their combination achieved the highest area under the ROC curve (AUC) of 0.83 (95% CI: 0.74-0.95) with a higher sensitivity than that of PAPP-A alone (61.5% vs. 30.8% at 10% false positive rate, P < 0.001). Concerning the late-onset FGR group, only log10MoMs of sFlt-1 (-0.12 vs. 0.00, P < 0.001) and PAPP-A (-0.07 vs. 0.05, P < 0.05) were lower than the control group, but their AUC was only 0.68 (95% CI:0.59-0.78).

CONCLUSIONS

Three new first trimester biomarkers, sNRP-1, sPECAM-1 and PDGF-AB/BB are predictive of subsequent development of early-onset FGR.

External validation and comparison of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in the first trimester: multicenter cohort study

OBJECTIVES

To examine the predictive performance of the Fetal Medicine Foundation (FMF) competing-risks model for the first-trimester prediction of a small-for-gestational-age (SGA) neonate in a large, independent, unselected European cohort and to compare the competing-risks algorithm with previously published logistic-regression models.

METHODS

This was a retrospective, non-interventional, multicenter cohort study including 35 170 women with a singleton pregnancy who underwent a first-trimester ultrasound assessment between 11 + 0 and 13 + 6 weeks' gestation. We used the default FMF competing-risks model for the prediction of SGA combining maternal factors, uterine artery pulsatility index (UtA-PI), pregnancy-associated plasma protein-A (PAPP-A) and placental growth factor (PlGF) to obtain risks for different cut-offs of birth-weight percentile and gestational age at delivery. We examined the predictive performance in terms of discrimination and calibration and compared it with the published data on the model's development population and with published logistic-regression equations.

RESULTS

At a 10% false-positive rate, maternal factors and UtA-PI predicted 42.2% and 51.5% of SGA < 10th percentile delivered < 37 weeks and < 32 weeks, respectively. The respective values for SGA < 3rd percentile were 44.7% and 51.7%. Also at a 10% false-positive rate, maternal factors, UtA-PI and PAPP-A predicted 42.2% and 51.5% of SGA < 10th percentile delivered < 37 weeks and < 32 weeks, respectively. The respective values for SGA < 3rd percentile were 46.2% and 51.7%. At a 10% false-positive rate, maternal factors, UtA-PI, PAPP-A and PlGF predicted 47.6% and 66.7% of SGA < 10th percentile delivered < 37 weeks and < 32 weeks, respectively. The respective values for SGA < 3rd percentile were 50.0% and 69.0%. These data were similar to those reported in the original model's development study and substantially better than those calculated using pre-existing logistic-regression models (McNemar's test, P < 0.001). The FMF competing-risks model was well calibrated.

CONCLUSIONS

The FMF competing-risks model for the first-trimester prediction of SGA is reproducible in an independent, unselected low-risk cohort and superior to logistic-regression approaches. © 2025 International Society of Ultrasound in Obstetrics and Gynecology.

Implementation of First-Trimester Screening and Prevention of Preeclampsia: A Stepped Wedge Cluster-Randomized Trial in Asia

BACKGROUND

This trial aimed to assess the efficacy, acceptability, and safety of a first-trimester screen-and-prevent strategy for preterm preeclampsia in Asia.

METHODS

Between August 1, 2019, and February 28, 2022, this multicenter stepped wedge cluster randomized trial included maternity/diagnostic units from 10 regions in Asia. The trial started with a period where all recruiting centers provided routine antenatal care without study-related intervention. At regular 6-week intervals, one cluster was randomized to transit from nonintervention phase to intervention phase. In the intervention phase, women underwent first-trimester screening for preterm preeclampsia using a Bayes theorem-based triple-test. High-risk women, with adjusted risk for preterm preeclampsia ≥1 in 100, received low-dose aspirin from <16 weeks until 36 weeks.

RESULTS

Overall, 88.04% (42 897 of 48 725) of women agreed to undergo first-trimester screening for preterm preeclampsia. Among those identified as high-risk in the intervention phase, 82.39% (2919 of 3543) received aspirin prophylaxis. There was no significant difference in the incidence of preterm preeclampsia between the intervention and non-intervention phases (adjusted odds ratio [aOR], 1.59 [95% CI, 0.91-2.77]). However, among high-risk women in the intervention phase, aspirin prophylaxis was significantly associated with a 41% reduction in the incidence of preterm preeclampsia (aOR, 0.59 [95% CI, 0.37-0.92]). In addition, it correlated with 54%, 55%, and 64% reduction in the incidence of preeclampsia with delivery at <34 weeks (aOR, 0.46 [95% CI, 0.23-0.93]), spontaneous preterm birth <34 weeks (aOR, 0.45 [95% CI, 0.22-0.92]), and perinatal death (aOR, 0.34 [95% CI, 0.12-0.91]), respectively. There was no significant between-group difference in the incidence of aspirin-related severe adverse events.

CONCLUSIONS

The implementation of the screen-and-prevent strategy for preterm preeclampsia is not associated with a significant reduction in the incidence of preterm preeclampsia. However, low-dose aspirin effectively reduces the incidence of preterm preeclampsia by 41% among high-risk women. The screen-and-prevent strategy for preterm preeclampsia is highly accepted by a diverse group of women from various ethnic backgrounds beyond the original population where the strategy was developed. These findings underpin the importance of the widespread implementation of the screen-and-prevent strategy for preterm preeclampsia on a global scale.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT03941886.

Comparison of competing-risks model with angiogenic factors in midgestation screening for preterm growth-related neonatal morbidity

OBJECTIVES

First, to evaluate the predictive performance for preterm growth-related neonatal morbidity of a high soluble fms-like tyrosine kinase-1 (sFlt-1)/placental growth factor (PlGF) ratio or low PlGF at midgestation and, second, to compare the performance of a high sFlt-1/PlGF ratio or low PlGF with that of the competing-risks model for small-for-gestational age (SGA), utilizing a combination of maternal risk factors, sonographic estimated fetal weight and uterine artery pulsatility index.

METHODS

This was a prospective observational study in women attending for a routine hospital visit at 19-24 weeks' gestation in two maternity hospitals in England. The visit included recording of maternal demographic characteristics and medical history, carrying out an ultrasound scan and measuring serum PlGF and sFlt-1. The primary outcome was delivery < 32 and < 37 weeks' gestation of a SGA neonate with birth weight < 10th or < 3rd percentile, combined with neonatal unit (NNU) admission for ≥ 48 h or a composite of major neonatal morbidity. The detection rates in screening by PlGF < 10th percentile, sFlt-1/PlGF ratio > 90th percentile and the competing-risks model for SGA were estimated and then compared using McNemar's test.

RESULTS

In the study population of 40 241 women, prediction of preterm growth-related neonatal morbidity provided by the competing-risks model for SGA was superior to that of screening by low PlGF concentration or high sFlt-1/PlGF ratio. For example, at a screen-positive rate of 10.0%, as defined by the sFlt-1/PlGF ratio > 90th percentile, the competing-risks model predicted 70.1% (95% CI, 61.0-79.2%) of SGA < 10th percentile and 76.9% (95% CI, 67.6-86.3%) of SGA < 3rd percentile with NNU admission for ≥ 48 h delivered < 32 weeks' gestation. The respective values for SGA with major neonatal morbidity were 73.8% (95% CI, 64.4-83.2%) and 77.9% (95% CI, 68.0-87.8%). These were significantly higher than the respective values of 35.1% (95% CI, 25.6-44.6%), 35.9% (95% CI, 25.3-46.5%), 38.1% (95% CI, 27.7-48.5%) and 39.7% (95% CI, 28.1-51.3%) achieved by the application of the sFlt-1/PlGF ratio > 90th percentile (all P < 0.0001).

CONCLUSION

At midgestation, the prediction of growth-related neonatal morbidity by the competing-risks model for SGA is superior to that of a high sFlt-1/PlGF ratio or low PlGF. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Evaluation of angiogenic factors in prediction of growth-related neonatal morbidity at term and comparison with competing-risks model

OBJECTIVES

First, to describe the distribution of biomarkers of impaired placentation in small-for-gestational-age (SGA) pregnancies with neonatal morbidity; second, to examine the predictive performance for growth-related neonatal morbidity of a high soluble fms-like tyrosine kinase-1 (sFlt-1)/placental growth factor (PlGF) ratio or low PlGF; and, third, to compare the performance of a high sFlt-1/PlGF ratio or low PlGF with that of the competing-risks model for SGA in predicting growth-related neonatal morbidity.

METHODS

This was a prospective observational study of women attending for a routine hospital visit at 35 + 0 to 36 + 6 weeks' gestation in two maternity hospitals in England. The visit included recording of maternal demographic characteristics and medical history, an ultrasound scan and measurement of serum PlGF and sFlt-1. The primary outcome was delivery within 4 weeks after assessment and at < 42 weeks' gestation of a SGA neonate with birth weight < 10th or < 3rd percentile, combined with neonatal unit (NNU) admission for ≥ 48 h or a composite of major neonatal morbidity. The detection rates in screening by PlGF < 10th percentile, sFlt-1/PlGF ratio > 90th percentile, sFlt-1/PlGF ratio > 38 and the competing-risks model for SGA, using combinations of maternal risk factors and Z-scores of estimated fetal weight (EFW) with multiples of the median values of uterine artery pulsatility index, PlGF and sFlt-1, were estimated. The detection rates by the different methods of screening were compared using McNemar's test.

RESULTS

In the study population of 29 035 women, prediction of growth-related neonatal morbidity at term provided by the competing-risks model was superior to that of screening by low PlGF concentration or a high sFlt-1/PlGF concentration ratio. For example, at a screen-positive rate (SPR) of 13.1%, as defined by the sFlt-1/PlGF ratio > 38, the competing-risks model using maternal risk factors and EFW predicted 77.5% (95% CI, 71.7-83.3%) of SGA < 10th percentile and 89.3% (95% CI, 83.7-94.8%) of SGA < 3rd percentile with NNU admission for ≥ 48 h delivered within 4 weeks after assessment. The respective values for SGA with major neonatal morbidity were 71.4% (95% CI, 56.5-86.4%) and 90.0% (95% CI, 76.9-100%). These were significantly higher than the respective values of 41.0% (95% CI, 34.2-47.8%) (P < 0.0001), 48.8% (95% CI, 39.9-57.7%) (P < 0.0001), 37.1% (95% CI, 21.1-53.2%) (P = 0.003) and 55.0% (95% CI, 33.2-76.8%) (P = 0.035) achieved by the application of the sFlt-1/PlGF ratio > 38. At a SPR of 10.0%, as defined by PlGF < 10th percentile, the competing-risks model using maternal factors and EFW predicted 71.5% (95% CI, 65.2-77.8%) of SGA < 10th percentile and 84.3% (95% CI, 77.8-90.8%) of SGA < 3rd percentile with NNU admission for ≥ 48 h delivered within 4 weeks after assessment. The respective values for SGA with major neonatal morbidity were 68.6% (95% CI, 53.1-83.9%) and 85.0% (95% CI, 69.4-100%). These were significantly higher than the respective values of 36.5% (95% CI, 29.8-43.2%) (P < 0.0001), 46.3% (95% CI, 37.4-55.2%) (P < 0.0001), 37.1% (95% CI, 21.1-53.2%) (P = 0.003) and 55.0% (95% CI, 33.2-76.8%) (P = 0.021) achieved by the application of PlGF < 10th percentile.

CONCLUSION

At 36 weeks' gestation, the prediction of growth-related neonatal morbidity by the competing-risks model for SGA, using maternal risk factors and EFW, is superior to that of a high sFlt-1/PlGF ratio or low PlGF. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Validation of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in early third trimester

OBJECTIVE

To evaluate the new 36-week Fetal Medicine Foundation (FMF) competing-risks model for the prediction of small-for-gestational age (SGA) at an earlier gestation of 30 + 0 to 34 + 0 weeks.

METHODS

This was a retrospective multicenter cohort study of prospectively collected data on 3012 women with a singleton pregnancy undergoing ultrasound examination at 30 + 0 to 34 + 0 weeks' gestation as part of a universal screening program. We used the default FMF competing-risks model for prediction of SGA at 36 weeks' gestation combining maternal factors (age, obstetric and medical history, weight, height, smoking status, race, mode of conception), estimated fetal weight (EFW) and uterine artery pulsatility index (UtA-PI) to calculate risks for different cut-offs of birth-weight percentile and gestational age at delivery. We examined the accuracy of the model by means of discrimination and calibration.

RESULTS

The prediction of SGA < 3rd percentile improved with the addition of UtA-PI and with a shorter examination-to-delivery interval. For a 10% false-positive rate, maternal factors, EFW and UtA-PI predicted 88.0%, 74.4% and 72.8% of SGA < 3rd percentile delivered at < 37, < 40 and < 42 weeks' gestation, respectively. The respective values for SGA < 10th percentile were 86.1%, 69.3% and 66.2%. In terms of population stratification, if the biomarkers used are EFW and UtA-PI and the aim is to detect 90% of SGA < 10th percentile, then 10.8% of the population should be scanned within 2 weeks after the initial assessment, an additional 7.2% (total screen-positive rate (SPR), 18.0%) should be scanned within 2-4 weeks after the initial assessment and an additional 11.7% (total SPR, 29.7%) should be examined within 4-6 weeks after the initial assessment. The new model was well calibrated.

CONCLUSIONS

The 36-week FMF competing-risks model for SGA is also applicable and accurate at 30 + 0 to 34 + 0 weeks and provides effective risk stratification, especially for cases leading to delivery < 37 weeks of gestation. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.