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BJOG. 2019 Mar;126(4):472-484. doi: 10.1111/1471-0528.15516. Epub 2019 Jan 17.

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

Author information

1
Department of Epidemiology, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, the Netherlands.
2
Department of Clinical Epidemiology and Medical Technology Assessment (KEMTA), Maastricht University Medical Centre, Maastricht, the Netherlands.
3
Department of Obstetrics and Gynaecology, Zuyderland Medical Centre, Heerlen, the Netherlands.
4
Department of Obstetrics and Gynaecology, Sint Jans Gasthuis Weert, Weert, the Netherlands.
5
Department of Obstetrics and Gynaecology, Laurentius Hospital, Roermond, the Netherlands.
6
Department of Obstetrics and Gynaecology, School for Oncology and Developmental Biology (GROW), Maastricht University Medical Centre, Maastricht, the Netherlands.

Abstract

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 ABSTRACT:

The clinical relevance of prediction models for the risk of small- and large-for-gestational-age is limited.

KEYWORDS:

Decision curve analysis; externsal validation; fetal growth; first trimester; large for gestational age; prediction; risk assessment; small for gestational age

PMID:
30358080
PMCID:
PMC6590121
DOI:
10.1111/1471-0528.15516
[Indexed for MEDLINE]
Free PMC Article

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