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

Abstract

ObjectivesTo examine the external validity of the new Fetal Medicine Foundation (FMF) competing risk model for the prediction of small for gestational age (SGA) at 11‐14 weeks of gestation in Asian population.MethodsThis is a secondary analysis of a multicenter prospective cohort study in 10,120 women with singleton pregnancies undergoing routine assessment at 11‐14 weeks of gestation. We applied the FMF competing risk 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). We obtained 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.ResultsThe predictive performance of the competing risk model for SGA was similar to that reported in the FMF study. Specifically, the combination of maternal factors with MAP, UtA‐PI, and PlGF yielded the best performance for the prediction of preterm SGA <10th percentile (SGA<10th) and preterm SGA <5th percentile (SGA<5th), with the areas under the curves (AUCs) of 0.765 (95% confidence interval [CI], 0.720‐0.809) and 0.789 (95%CI, 0.736‐0.841), respectively. Combining maternal factors, MAP, and PlGF yielded the best model for predicting preterm SGA <3rd percentile (SGA<3rd), with an AUC of 0.797 (95%CI, 0.744‐0.850). After excluding preeclampsia (PE) cases, the combination of maternal factors with MAP, UtA‐PI, and PlGF yielded the best performance for the prediction of preterm SGA<10th and 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 PE was the combination of maternal factors and PlGF, with an AUC of 0.786 (95%CI, 0.723‐0.849). The FMF competing risk model including maternal factors, MAP, UtA‐PI, PlGF achieved DRs of 42.2%, 47.3%, and 48.1%, at the fixed FPR of 10%, for the prediction of preterm SGA with birth weight <10th, 5th and 3rd percentiles, respectively. The calibration of the new model was satisfactory.ConclusionThe screening performance of the new FMF first trimester competing risk model for SGA in an independent large cohort of Asian women is comparable to that reported in the original FMF study on a mixed European population.This article is protected by copyright. All rights reserved.

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

“…Only a few small, heterogeneous studies have evaluated the use of the sFlt-1/PlGF ratio in predicting prognosis and for management of pregnancies with a small-for-gestational-age (SGA) fetus [4][5][6] . An alternative approach to identify SGA is a competing-risks model, which is effective, demonstrates superior performance compared with the traditional methods and has been internally and externally validated at all pregnancy stages [7][8][9][10][11][12][13][14] . The Bayesian structure of this model, which has birth weight and gestational age at delivery as two continuous dimensions, allows the inclusion of any desired biomarker at any stage of pregnancy [7][8][9][10] .…”

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

“…The individual characteristics and the biomarker levels define a pregnancy-specific joint distribution of birth weight and gestational age that enable calculation of the risk of delivery of a baby with birth weight and gestational age at delivery below the desired combinations of cut-offs [10][11][12][13][14][15][16][17][18][19][20] . We can take the same model at any stage of pregnancy with any available set of biomarkers [10][11][12][13][14][15][16][17][18][19][20] . Using these capabilities, we computed risks for different cut-offs of SGA at midgestation 10 .…”

“…The competing‐risks model for SGA has two continuous dimensions: birth weight and gestational age at delivery. The individual characteristics and the biomarker levels define a pregnancy‐specific joint distribution of birth weight and gestational age that enable calculation of the risk of delivery of a baby with birth weight and gestational age at delivery below the desired combinations of cut‐offs 10–20 . We can take the same model at any stage of pregnancy with any available set of biomarkers 10–20 .…”

“…Several relatively small studies have proposed that an increase in the sFlt-1/PlGF ratio is not only predictive of PE but also useful in the management of growth-restricted and SGA fetuses [6][7][8][9] . Our approach to prediction of delivery of a SGA neonate, stillbirth and growth-related neonatal morbidity is the use of a competing-risks model, which combines maternal risk factors, sonographic estimated fetal weight (EFW) and MoM values of biomarkers [10][11][12][13][14][15][16][17][18][19][20] .…”

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

“…The Fetal Medicine Foundation (FMF) has recently developed a new method for predicting SGA throughout pregnancy 8,12,13,[16][17][18][19][20][21][22][23] . This approach considers growth restriction as a spectrum condition consisting of two continuous variables; namely birth weight and gestational age at delivery.…”