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

ObjectiveTo 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. DesignMulticentre prospective cohort. SettingThirty-six midwifery practices and six hospitals (in the Netherlands). PopulationPregnant women were recruited at <16weeks of gestation between 1 July 2013 and 31 December 2015. MethodsPrediction 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 measuresPredictive performance was assessed by means of discrimination (C-statistic) and calibration. ResultsThe 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. ConclusionThe 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.