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

Ultrasound Obstet Gynecol. 2025 Jun;65(6):729-737. doi: 10.1002/uog.29219. Epub 2025 Apr 14.

Abstract

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 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Keywords: Bayes' theorem; FMF; Fetal Medicine Foundation; SGA; algorithm; biomarker; fetal growth restriction; prediction model; small‐for‐gestational age; survival model.

Publication types

  • Multicenter Study
  • Comparative Study
  • Validation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Algorithms
  • Cohort Studies
  • Female
  • Fetal Growth Retardation* / diagnosis
  • Fetal Growth Retardation* / diagnostic imaging
  • Gestational Age
  • Humans
  • Infant, Newborn
  • Infant, Small for Gestational Age*
  • Logistic Models
  • Placenta Growth Factor / blood
  • Predictive Value of Tests
  • Pregnancy
  • Pregnancy Trimester, First
  • Pregnancy-Associated Plasma Protein-A / analysis
  • Pregnancy-Associated Plasma Protein-A / metabolism
  • Pulsatile Flow
  • Retrospective Studies
  • Risk Assessment / methods
  • Ultrasonography, Prenatal* / methods
  • Uterine Artery / diagnostic imaging

Substances

  • Pregnancy-Associated Plasma Protein-A
  • Placenta Growth Factor
  • PGF protein, human