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Published on: June 21, 2018
External validation and clinical usefulness of first-trimester prediction models for small- and
Lje Meertens1, Ljm Smits1, Smj van Kuijk2
1Department of Epidemiology, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, the Netherlands.
Insights
First-trimester prediction models for small- and large-for-gestational-age infants show limited clinical relevance due to moderate predictive performance. Models predicting hypertensive disorders and gestational diabetes may offer greater specificity for fetal growth deviations.
Area of Science:
- Obstetrics and Gynecology
- Perinatal Medicine
- Reproductive Health
Background:
- Accurate prediction of fetal growth deviations, specifically small-for-gestational-age (SGA) and large-for-gestational-age (LGA) infants, is crucial for optimizing perinatal outcomes.
- Existing first-trimester prediction models utilizing routinely collected maternal data aim to identify pregnancies at risk for SGA and LGA.
Purpose of the Study:
- To evaluate the external validity of published first-trimester prediction models for SGA and LGA infant risk.
- To assess the clinical utility of the best-performing models in a real-world setting.
Main Methods:
- A multicentre prospective cohort study was conducted in 36 midwifery practices and 6 hospitals in the Netherlands.
- Prediction models were systematically identified from existing literature, with predictor data collected via web-based questionnaires.
- Predictive performance was evaluated using discrimination (C-statistic) and calibration, with birthweight centiles adjusted for gestational age, parity, fetal sex, and ethnicity.
Main Results:
- The validation cohort included 2582 pregnant women, with SGA (<10th percentile) and LGA (>90th percentile) observed in 203 and 224 cases, respectively.
- The C-statistics for SGA ranged from 0.52 to 0.64, and for LGA from 0.60 to 0.69, with improved performance for more extreme definitions (<5th percentile SGA, >95th percentile LGA).
- Initial calibration showed poor-to-moderate agreement, which significantly improved after recalibration.
Conclusions:
- The current prediction models for SGA and LGA infants demonstrate limited clinical relevance due to their moderate predictive accuracy.
- The definitions of SGA and LGA do not adequately account for constitutional variations in infant size.
- Prediction models focusing on vascular or metabolic factors, such as those for hypertensive disorders and gestational diabetes, are likely to provide more specific identification of clinically relevant fetal growth abnormalities.
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.
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