Bradburn Elizabeth, Conde-Agudelo Agustin, Roberts Nia W, Villar Jose, Papageorghiou Aris T
Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.
Oxford Maternal & Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK.
EClinicalMedicine. 2024 Mar 8;70:102498. doi: 10.1016/j.eclinm.2024.102498. eCollection 2024 Apr.
Knowledge of gestational age (GA) is key in clinical management of individual obstetric patients, and critical to be able to calculate rates of preterm birth and small for GA at a population level. Currently, the gold standard for pregnancy dating is measurement of the fetal crown rump length at 11-14 weeks of gestation. However, this is not possible for women first presenting in later pregnancy, or in settings where routine ultrasound is not available. A reliable, cheap and easy to measure GA-dependent biomarker would provide an important breakthrough in estimating the age of pregnancy. Therefore, the aim of this study was to determine the accuracy of prenatal and postnatal biomarkers for estimating gestational age (GA).
Systematic review prospectively registered with PROSPERO (CRD42020167727) and reported in accordance with the PRISMA-DTA. Medline, Embase, CINAHL, LILACS, and other databases were searched from inception until September 2023 for cohort or cross-sectional studies that reported on the accuracy of prenatal and postnatal biomarkers for estimating GA. In addition, we searched Google Scholar and screened proceedings of relevant conferences and reference lists of identified studies and relevant reviews. There were no language or date restrictions. Pooled coefficients of correlation and root mean square error (RMSE, average deviation in weeks between the GA estimated by the biomarker and that estimated by the gold standard method) were calculated. The risk of bias in each included study was also assessed.
Thirty-nine studies fulfilled the inclusion criteria: 20 studies (2,050 women) assessed prenatal biomarkers (placental hormones, metabolomic profiles, proteomics, cell-free RNA transcripts, and exon-level gene expression), and 19 (1,738,652 newborns) assessed postnatal biomarkers (metabolomic profiles, DNA methylation profiles, and fetal haematological components). Among the prenatal biomarkers assessed, human chorionic gonadotrophin measured in maternal serum between 4 and 9 weeks of gestation showed the highest correlation with the reference standard GA, with a pooled coefficient of correlation of 0.88. Among the postnatal biomarkers assessed, metabolomic profiling from newborn blood spots provided the most accurate estimate of GA, with a pooled RMSE of 1.03 weeks across all GAs. It performed best for term infants with a slightly reduced accuracy for preterm or small for GA infants. The pooled RMSEs for metabolomic profiling and DNA methylation profile from cord blood samples were 1.57 and 1.60 weeks, respectively.
We identified no antenatal biomarkers that accurately predict GA over a wide window of pregnancy. Postnatally, metabolomic profiling from newborn blood spot provides an accurate estimate of GA, however, as this is known only after birth it is not useful to guide antenatal care. Further prenatal studies are needed to identify biomarkers that can be used in isolation, as part of a biomarker panel, or in combination with other clinical methods to narrow prediction intervals of GA estimation.
The research was funded by the Bill and Melinda Gates Foundation (INV-000368). ATP is supported by the Oxford Partnership Comprehensive Biomedical Research Centre with funding from the NIHR Biomedical Research Centre funding scheme. The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR, the Department of Health, or the Department of Biotechnology. The funders of this study had no role in study design, data collection, analysis or interpretation of the data, in writing the paper or the decision to submit for publication.
孕周(GA)的知识是产科个体患者临床管理的关键,对于在人群层面计算早产率和小于胎龄儿发生率至关重要。目前,妊娠日期确定的金标准是在妊娠11 - 14周时测量胎儿头臀长度。然而,对于首次在妊娠晚期就诊的女性,或在无法进行常规超声检查的情况下,这是不可能的。一种可靠、廉价且易于测量的依赖孕周的生物标志物将为估计妊娠年龄提供重要突破。因此,本研究的目的是确定产前和产后生物标志物估计孕周(GA)的准确性。
前瞻性注册于PROSPERO(CRD42020167727)的系统评价,并按照PRISMA - DTA报告。从数据库建立至2023年9月,检索了Medline、Embase、CINAHL、LILACS及其他数据库,以查找报告产前和产后生物标志物估计GA准确性的队列研究或横断面研究。此外,我们还搜索了谷歌学术,并筛选了相关会议的论文集以及已识别研究和相关综述的参考文献列表。没有语言或日期限制。计算合并相关系数和均方根误差(RMSE,生物标志物估计的GA与金标准方法估计的GA之间的平均周偏差)。还评估了每项纳入研究的偏倚风险。
39项研究符合纳入标准:20项研究(2050名女性)评估产前生物标志物(胎盘激素、代谢组学谱、蛋白质组学、游离RNA转录本和外显子水平基因表达),19项研究(1738652名新生儿)评估产后生物标志物(代谢组学谱、DNA甲基化谱和胎儿血液成分)。在所评估的产前生物标志物中,妊娠4至9周时母体血清中测量的人绒毛膜促性腺激素与参考标准GA的相关性最高,合并相关系数为0.88。在所评估的产后生物标志物中,新生儿血斑的代谢组学分析提供了最准确的GA估计,所有孕周的合并RMSE为1.03周。对足月儿表现最佳,对早产儿或小于胎龄儿的准确性略有降低。脐血样本代谢组学分析和DNA甲基化谱的合并RMSE分别为1.57周和1.60周。
我们未发现能在广泛孕周范围内准确预测GA的产前生物标志物。产后,新生儿血斑的代谢组学分析可准确估计GA,然而,由于这仅在出生后才已知,所以对指导产前护理并无用处。需要进一步的产前研究来确定可单独使用、作为生物标志物组合的一部分或与其他临床方法结合使用以缩小GA估计预测区间的生物标志物。
该研究由比尔及梅琳达·盖茨基金会(INV - 000368)资助。ATP得到牛津伙伴关系综合生物医学研究中心的支持,该中心由NIHR生物医学研究中心资助计划提供资金。所表达的观点是作者的观点,不一定代表英国国家医疗服务体系、NIHR、卫生部或生物技术部的观点。本研究的资助者在研究设计、数据收集、数据分析或解释、撰写论文或提交发表的决定中没有任何作用。