Department of Epidemiology, Care and Public Health Research Institute (CAPHRI), Maastricht University, Maastricht, the Netherlands.
Department of Clinical Epidemiology and Medical Technology Assessment (KEMTA), Maastricht University Medical Centre, Maastricht, the Netherlands.
BJOG. 2019 Mar;126(4):472-484. doi: 10.1111/1471-0528.15516. Epub 2019 Jan 17.
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.
Multicentre prospective cohort.
Thirty-six midwifery practices and six hospitals (in the Netherlands).
Pregnant women were recruited at <16 weeks of gestation between 1 July 2013 and 31 December 2015.
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.
Predictive performance was assessed by means of discrimination (C-statistic) and calibration.
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.
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.
The clinical relevance of prediction models for the risk of small- and large-for-gestational-age is limited.
评估所有基于常规收集的产妇预测因素预测小胎龄儿和大胎龄儿(SGA 和 LGA)风险的一期预测模型的外部有效性。此外,还评估了表现最佳的模型的临床潜力。
多中心前瞻性队列研究。
36 家助产士诊所和 6 家医院(荷兰)。
孕妇于 2013 年 7 月 1 日至 2015 年 12 月 31 日期间在<16 周妊娠时被招募。
系统地从文献中选择预测模型。通过网络问卷获得预测因素信息。采用校正了胎龄、产次、胎儿性别和种族的出生体重百分位数。
通过判别(C 统计量)和校准评估预测性能。
验证队列由 2582 名孕妇组成。SGA <第 10 百分位数和 LGA >第 90 百分位数的发生率分别为 203 例和 224 例。纳入模型的 C 统计量范围分别为 SGA(n=6)的 0.52-0.64 和 LGA(n=6)的 0.60-0.69。所有模型对 SGA(<第 5 百分位数)和 LGA(>第 95 百分位数)更严重的情况,C 统计量更高。初步校准显示预测概率与观察结果之间的一致性较差,但经过重新校准后,一致性得到了显著提高。
由于预测模型的预测性能中等,且 SGA 和 LGA 的定义不排除胎儿的固有大小,因此模型的临床相关性有限。由于大多数与临床相关的胎儿生长偏差与“血管”或“代谢”因素有关,因此预测高血压疾病和妊娠期糖尿病的模型可能更具特异性。
预测小胎龄儿和大胎龄儿风险的模型的临床相关性有限。