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Updated: Jun 18, 2026
Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Accuracy of prenatal and postnatal biomarkers for estimating gestational age: a systematic review and meta-analysis
Elizabeth Bradburn1, Agustin Conde-Agudelo2, Nia W Roberts3
1Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK.
Insights
Accurate gestational age estimation is crucial. While postnatal metabolomic profiling shows promise, no prenatal biomarker reliably predicts pregnancy duration, necessitating further research for improved antenatal care.
Area of Science:
- Obstetrics and Gynecology
- Biomarker Discovery
- Perinatal Medicine
Background:
- Accurate gestational age (GA) is vital for obstetric management and population health metrics.
- Current gold standard (crown rump length ultrasound) is unavailable for late-presenting pregnancies or in resource-limited settings.
- Need exists for reliable, accessible biomarkers to estimate GA.
Purpose of the Study:
- To systematically review and assess the accuracy of prenatal and postnatal biomarkers for estimating gestational age (GA).
Main Methods:
- Systematic review (PROSPERO registered, PRISMA-DTA reported) of studies reporting biomarker accuracy for GA estimation.
- Searched multiple databases (Medline, Embase, etc.) and other sources until September 2023.
- Calculated pooled correlation coefficients and root mean square error (RMSE) to assess accuracy.
Main Results:
- Thirty-nine studies included: 20 on prenatal (hormones, proteomics, etc.) and 19 on postnatal biomarkers (metabolomics, DNA methylation).
- Maternal serum human chorionic gonadotrophin (4-9 weeks) showed highest prenatal correlation (0.88).
- Newborn blood spot metabolomic profiling yielded the most accurate postnatal GA estimate (RMSE 1.03 weeks), best for term infants.
Conclusions:
- No current prenatal biomarker accurately predicts GA across a wide gestational window.
- Postnatal metabolomic profiling is accurate but not useful for antenatal care.
- Further research is essential to identify reliable prenatal biomarkers, individually or in panels, for improved GA estimation.
Background:
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).
Methods:
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.
Findings:
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.
Interpretation:
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.
Funding:
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.
