Clinical, ultrasound and molecular biomarkers for early prediction of large for gestational age infants in nulliparous women: An international prospective cohort study - Vieira, Matias C. (PLoS One, 2017)
OBJECTIVE: To develop a prediction model for term infants born large for gestational age (LGA) by customised birthweight centiles. METHODS: International prospective cohort of nulliparous women with singleton pregnancy recruited to the Screening for Pregnancy Endpoints (SCOPE) study. LGA was defined as birthweight above the 90(th) customised centile, including adjustment for parity, ethnicity, maternal height and weight, fetal gender and gestational age. Clinical risk factors, ultrasound parameters and biomarkers at 14–16 or 19–21 weeks were combined into a prediction model for LGA infants at term using stepwise logistic regression in a training dataset. Prediction performance was assessed in a validation dataset using area under the Receiver Operating Characteristics curve (AUC) and detection rate at fixed false positive rates. RESULTS: The prevalence of LGA at term was 8.8% (n = 491/5628). Clinical and ultrasound factors selected in the prediction model for LGA infants were maternal birthweight, gestational weight gain between 14–16 and 19–21 weeks, and fetal abdominal circumference, head circumference and uterine artery Doppler resistance index at 19–21 weeks (AUC 0.67; 95%CI 0.63–0.71). Sensitivity of this model was 24% and 49% for a fixed false positive rate of 10% and 25%, respectively. The addition of biomarkers resulted in selection of random glucose, LDL-cholesterol, vascular endothelial growth factor receptor-1 (VEGFR1) and neutrophil gelatinase-associated lipocalin (NGAL), but with minimal improvement in model performance (AUC 0.69; 95%CI 0.65–0.73). Sensitivity of the full model was 26% and 50% for a fixed false positive rate of 10% and 25%, respectively. CONCLUSION: Prediction of LGA infants at term has limited diagnostic performance before 22 weeks but may have a role in contingency screening in later pregnancy.