Competing‐risks model for prediction of small‐for‐gestational‐age neonate from biophysical and biochemical markers at 11–13 weeks' gestation

Abstract

What are the novel findings of this work? This study presents a new competing-risks model for the prediction of a small-for-gestational-age (SGA) neonate by maternal factors and biomarkers at 11-13 weeks' gestation. This approach involves a joint prior distribution of gestational age (GA) at delivery and birth-weight Z-score, updated by the biomarkers' likelihood according to Bayes' theorem. The pattern of change, conditional to GA at delivery and birth-weight Z-score, is similar for all biomarkers and is captured by the same folded-plane regression modeling. The best biophysical predictor of preterm SGA was uterine artery pulsatility index and the best biochemical marker was placental growth factor. The prediction of SGA was consistently better for increasing degree of prematurity, greater severity of smallness, coexistence of pre-eclampsia and increasing number of biomarkers. What are the clinical implications of this work? A single continuous two-dimensional model provides early risk stratification, for any desired cutoffs of smallness and GA at delivery, laying the ground for a personalized antenatal plan for predicting and managing SGA, in the milieu of a new inverted pyramid of prenatal care.

Competing‐risks model for prediction of small‐for‐gestational‐age neonate from estimated fetal weight at 19–24 weeks' gestation

“…The EFW likelihood updates the prior distribution of birth‐weight Z ‐score and GA at delivery. In the high‐risk cases, the joint distribution is shifted towards earlier GAs and lower birth weights, resulting in a higher risk for SGA, as we have demonstrated previously 11–14 .…”

“…In the competing-risks model for prediction of SGA, the performance of screening by maternal characteristics and medical history is improved by the addition of second-trimester EFW. This study provides further evidence that SGA is a spectrum disorder [11][12][13][14] . The Z-score of EFW has a continuous association with Z-score of birth weight and GA at delivery; EFW and birth weight are correlated linearly, and this association becomes steeper for earlier GAs.…”

“…The first step was a maternal history model that defined a patient-specific joint distribution of Z-scores of birth weight and GA at delivery 11 . The second step was the addition of the first-trimester biomarkers' multivariate likelihood according to Bayes' theorem [12][13][14] . The model enables us to compute risks for any chosen cut-off.…”

“…We have proposed recently a new competing-risks model for the prediction of SGA [11][12][13][14] . This new approach is based on the concept that SGA is a two-dimensional spectrum disorder whose severity is reflected continuously in both gestational age (GA) at delivery and Z-score of birth weight for GA.…”

Prediction of Adverse Pregnancy Outcome Related to Placental Dysfunction Using the sFlt-1/PlGF Ratio: A Narrative Review

“…Studies on the screening of high and low-risk groups during pregnancy to predict early or late-onset PE/FGR will not be discussed in this review. However, the advances in PE/FGR prediction models in the first and second trimester are immanent 21 , 22 , 23 and efforts to extract the best prediction models from large datasets are ongoing 24 . It should be mentioned that this review is not a systematic analysis of the existing literature but a selective presentation of articles related to this topic the authors considered interesting.…”