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

Abstract

ObjectivesTo evaluate the new 36 weeks’ 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.MethodsThis is a retrospective multi‐center cohort study of prospectively collected data on 3,012 women with singleton pregnancies undergoing ultrasound examination at 30+0 ‐ 34+0 weeks’ gestation, as part of a universal screening program. We used the default 36 weeks’ FMF competing risks model for prediction of SGA, combining maternal factors (age, obstetric and medical history, weight, height, smoking, race, 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 model's accuracy by means of discrimination and calibration.ResultsThe prediction of SGA<3rd percentile improves with the addition of UtA‐PI and with shorter examination‐to‐delivery interval. For 10% false positive rate, maternal factors, EFW and UtA‐PI predicted 88.0%, 74.4% and 72.8% of SGA <3rd percentile delivered <37, <40 and <42 weeks, respectively. The corresponding figures for SGA 10th percentile were 83.9%, 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 <10thpercentile, then 10.8% of the population should be scanned within two weeks after the initial assessment, an additional 7.2% (total screen positive rate, SPR 18%) should be scanned within two and four weeks after the initial assessment and an additional 11.7% (total SPR 29.7%) should be examined within four and six weeks after the initial assessment. The new model was well calibrated.ConclusionsThe 36 weeks’ FMF competing risks model for SGA is also applicable and accurate at 30+0 ‐ 34+0 weeks’ gestation, providing effective risk stratification, especially for cases leading to birth <37 weeks.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] .…”