External validation and clinical usefulness of first‐trimester prediction models for small‐ and large‐for‐gestational‐age infants: a prospective cohort study

• Published in: BJOG : an international journal of obstetrics and gynaecology Vol. 126; no. 4; pp. 472 - 484
• Main Authors: Meertens, LJE, Smits, LJM, Kuijk, SMJ, Aardenburg, R, Dooren, IMA, Langenveld, J, Zwaan, IM, Spaanderman, MEA, Scheepers, HCJ
• Format: Journal Article
• Language: English
• Published: England Wiley Subscription Services, Inc 01-03-2019; John Wiley and Sons Inc
• Subjects: Adult; Age; Birth weight; Cohort analysis; Cohort Studies; Decision curve analysis; Diabetes mellitus; Epidemiology; externsal validation; Female; fetal growth; Fetal Macrosomia - epidemiology; Fetuses; first trimester; Gestational age; Gestational diabetes; Health risk assessment; Humans; Infant, Newborn; Infant, Small for Gestational Age; Infants; large for gestational age; Minority & ethnic groups; Models, Statistical; Netherlands - epidemiology; prediction; Prediction models; Pregnancy; Pregnancy Trimester, First; Prospective Studies; Reproducibility of Results; risk assessment; small for gestational age; Statistical analysis; Statistics; Netherlands; risk assessment; externsal validation; first trimester; small for gestational age; prediction; large for gestational age; Decision curve analysis; fetal growth
• DOI: 10.1111/1471-0528.15516
• EISSN: 1471-0528
• ISSN: 1470-0328

Objective
To assess the external validity of all published first‐trimester prediction models based on routinely collected maternal predictors for the risk of small‐ and large‐for‐gestational‐age (SGA and LGA) infants. Furthermore, the clinical potential of the best‐performing models was evaluated.
Design
Multicentre prospective cohort.
Setting
Thirty‐six midwifery practices and six hospitals (in the Netherlands).
Population
Pregnant women were recruited at <16 weeks of gestation between 1 July 2013 and 31 December 2015.
Methods
Prediction models were systematically selected from the literature. Information on predictors was obtained by a web‐based questionnaire. Birthweight centiles were corrected for gestational age, parity, fetal sex, and ethnicity.
Main outcome measures
Predictive performance was assessed by means of discrimination (C‐statistic) and calibration.
Results
The validation cohort consisted of 2582 pregnant women. The outcomes of SGA <10th percentile and LGA >90th percentile occurred in 203 and 224 women, respectively. The C‐statistics of the included models ranged from 0.52 to 0.64 for SGA (n = 6), and from 0.60 to 0.69 for LGA (n = 6). All models yielded higher C‐statistics for more severe cases of SGA (<5th percentile) and LGA (>95th percentile). Initial calibration showed poor‐to‐moderate agreement between the predicted probabilities and the observed outcomes, but this improved substantially after recalibration.
Conclusion
The clinical relevance of the models is limited because of their moderate predictive performance, and because the definitions of SGA and LGA do not exclude constitutionally small or large infants. As most clinically relevant fetal growth deviations are related to ‘vascular’ or ‘metabolic’ factors, models predicting hypertensive disorders and gestational diabetes are likely to be more specific.
Tweetable
The clinical relevance of prediction models for the risk of small‐ and large‐for‐gestational‐age is limited.
Tweetable
The clinical relevance of prediction models for the risk of small‐ and large‐for‐gestational‐age is limited.