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. 2017 Jan 9;12(1):e0169311.
doi: 10.1371/journal.pone.0169311. eCollection 2017.

Prediction of Small for Gestational Age Infants in Healthy Nulliparous Women Using Clinical and Ultrasound Risk Factors Combined with Early Pregnancy Biomarkers

Lesley M E McCowan  1   2   3 , John M D Thompson  1   4 , Rennae S Taylor  1 , Philip N Baker  5 , Robyn A North  6 , Lucilla Poston  6 , Claire T Roberts  7 , Nigel A B Simpson  8 , James J Walker  8 , Jenny Myers  9 , Louise C Kenny  10   11 ; SCOPE consortium
Affiliations
Free PMC article

Prediction of Small for Gestational Age Infants in Healthy Nulliparous Women Using Clinical and Ultrasound Risk Factors Combined with Early Pregnancy Biomarkers

Lesley M E McCowan et al. PLoS One. .
Free PMC article

Abstract

Objective: Most small for gestational age pregnancies are unrecognised before birth, resulting in substantial avoidable perinatal mortality and morbidity. Our objective was to develop multivariable prediction models for small for gestational age combining clinical risk factors and biomarkers at 15±1 weeks' with ultrasound parameters at 20±1 weeks' gestation.

Methods: Data from 5606 participants in the Screening for Pregnancy Endpoints (SCOPE) cohort study were divided into Training (n = 3735) and Validation datasets (n = 1871). The primary outcomes were All-SGA (small for gestational age with birthweight <10th customised centile), Normotensive-SGA (small for gestational age with a normotensive mother) and Hypertensive-SGA (small for gestational age with an hypertensive mother). The comparison group comprised women without the respective small for gestational age phenotype. Multivariable analysis was performed using stepwise logistic regression beginning with clinical variables, and subsequent additions of biomarker and then ultrasound (biometry and Doppler) variables. Model performance was assessed in Training and Validation datasets by calculating area under the curve.

Results: 633 (11.2%) infants were All-SGA, 465(8.2%) Normotensive-SGA and 168 (3%) Hypertensive-SGA. Area under the curve (95% Confidence Intervals) for All-SGA using 15±1 weeks' clinical variables, 15±1 weeks' clinical+ biomarker variables and clinical + biomarkers + biometry /Doppler at 20±1 weeks' were: 0.63 (0.59-0.67), 0.64 (0.60-0.68) and 0.69 (0.66-0.73) respectively in the Validation dataset; Normotensive-SGA results were similar: 0.61 (0.57-0.66), 0.61 (0.56-0.66) and 0.68 (0.64-0.73) with small increases in performance in the Training datasets. Area under the curve (95% Confidence Intervals) for Hypertensive-SGA were: 0.76 (0.70-0.82), 0.80 (0.75-0.86) and 0.84 (0.78-0.89) with minimal change in the Training datasets.

Conclusion: Models for prediction of small for gestational age, which combine biomarkers, clinical and ultrasound data from a cohort of low-risk nulliparous women achieved modest performance. Incorporation of biomarkers into the models resulted in no improvement in performance of prediction of All-SGA and Normotensive-SGA but a small improvement in prediction of Hypertensive-SGA. Our models currently have insufficient reliability for application in clinical practice however, they have potential utility in two-staged screening tests which include third trimester biomarkers and or fetal biometry.

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Conflict of interest statement

The Alere funding was used for sample retrieval and shipping, database sharing, and the time university employed researchers spent on the project. Alere developed the immunoassays and performed the biomarker measurements, but was blinded to clinical data and endpoints. In addition, Alere and other funders had no role in study design, data collection and analysis, and decision to publish or the data included in this publication. This does not alter our adherence to PLOS ONE policies on sharing data and materials.” (as detailed online in the guide for authors http://www.PLOSone.org/static/editorial.action#competing).

Figures

Fig 1
Fig 1. Flow chart of study population.
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Grants and funding

The New Zealand SCOPE study was funded by the New Enterprise Research Fund, Foundation for Research Science and Technology; Health Research Council (04/198) http://www.hrc.govt.nz/; Evelyn Bond Fund, Auckland District Health Board Charitable Trust (http://www.adhb.govt.nz/researchoffice/A+Grant-Cmtee/ADHB_Grants_Committee.htm#ABOUT_THE_ADHB_CHARITABLE_TRUST), The Australian SCOPE study was funded by the Premier’s Science and Research Fund, South Australian Government (http://www.statedevelopment.sa.gov.au/science/premiers-research-and-industry-fund), The Irish SCOPE study was funded by the Health Research Board of Ireland (CSA/2007/2; http://www.hrb.ie), The UK SCOPE study was funded by National Health Service NEAT Grant (Neat Grant FSD025), Biotechnology and Biological Sciences Research council (www.bbsrc.ac.uk/funding; GT084) and University of Manchester Proof of Concept Funding (University of Manchester); Guy’s and St. Thomas’ Charity (King’s College London) and Tommy’s charity (http://www.tommys.org/; King’s College London and University of Manchester); and Cerebra UK (www.cerebra.org.uk; University of Leeds). The biomarker study was funded by an unrestricted research grant from Alere Inc, San Diego, CA (www.alere.com), to the universities in the SCOPE consortium. L.C. Kenny is supported by a Science Foundation Ireland Program Grant for INFANT (12/RC/2272). C.T. Roberts is supported by a National Health and Medical Research Council (NHMRC) Senior Research Fellowship GNT1020749. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.