Serum screening with Down's syndrome markers to predict pre-eclampsia and small for gestational age: systematic

Rachel K Morris1, Jeltsje S Cnossen, Marloes Langejans

  • 1Academic Department of Obstetrics and Gynaecology, University of Birmingham, Birmingham Women's Hospital, Birmingham, B15 2TG, UK. r.k.morris@bham.ac.uk

Insights

Down's serum screening analytes show low accuracy for predicting pre-eclampsia and small for gestational age. Combining these markers with other tests may improve risk assessment for better maternal and perinatal outcomes.

Area of Science:

  • Obstetrics and Gynecology
  • Maternal-Fetal Medicine
  • Biochemistry

Background:

  • Accurate antenatal prediction of pre-eclampsia and small for gestational age (SGA) is vital for resource allocation and timely intervention.
  • Improving maternal and perinatal outcomes relies on effective identification of high-risk pregnancies.

Purpose of the Study:

  • To systematically review the accuracy of five serum analytes, commonly used in Down's syndrome screening, for predicting pre-eclampsia and/or SGA.

Main Methods:

  • A systematic review of studies published up to February 2007, including Medline, Embase, and Cochrane databases.
  • Independent selection and data extraction by two reviewers for studies assessing serum analytes before 25 weeks' gestation.
  • Analysis of accuracy metrics, including likelihood ratios, for prediction of pre-eclampsia and SGA.

Main Results:

  • Evaluated five serum screening markers across 44 studies (169,637 women) for pre-eclampsia and 86 studies (382,005 women) for SGA.
  • Overall predictive accuracy for both conditions was low.
  • Inhibin A showed the best predictive value for pre-eclampsia, and AFP for SGA, but with wide confidence intervals due to study heterogeneity and limitations.

Conclusions:

  • Serum analytes used in Down's screening possess limited predictive accuracy for pre-eclampsia and SGA individually.
  • These markers may serve as a component of risk assessment strategies, particularly when integrated with other predictive tests.
Abstract

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