Evidence map›Paper›PMID 42597109›Full record

ArticlePregnancy (Hoboken, N.J.)2025

Early pregnancy placental biomarkers as predictors of preeclampsia with severe features.

Ashten B Waks, Rebecca Post, Jenny Chang, Argyrios Ziogas, William A Grobman, Ronald J Wapner, Robert Silver, Judith Chung

Abstract read
In one paragraph

Article in Pregnancy (Hoboken, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Ashten B WaksDepartment of Obstetrics and Gynecology University of California Irvine Orange California USA.
Rebecca PostDepartment of Obstetrics and Gynecology University of California Irvine Orange California USA.
Jenny ChangDepartment of Medicine University of California Irvine School of Medicine Irvine California USA.
Argyrios ZiogasDepartment of Medicine University of California Irvine School of Medicine Irvine California USA.
William A GrobmanDepartment of Obstetrics and Gynecology The Warren Alpert Medical School of Brown University Providence Rhode Island USA.
Ronald J WapnerDepartment of Obstetrics and Gynecology Columbia University School of Medicine New York New York USA.
Robert SilverDepartment of Obstetrics and Gynecology University of Utah Salt Lake City Utah USA.
Judith ChungDepartment of Obstetrics and Gynecology University of California Irvine Orange California USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Multiple studies have evaluated late second and third trimester values for soluble Fms-like tyrosine kinase 1 (sFlt-1), placental-like growth factor (PlGF), and sFlt-1:PlGF ratio for preeclampsia risk stratification, but few studies have assessed sFlt-1:PlGF ratio earlier in pregnancy. Objective: To investigate the utility of early pregnancy sFlt-1:PlGF ratio for predicting preeclampsia with severe features, and to compare its predictive ability with that of the United States Preventive Services Task Force (USPSTF) risk assessment algorithm. Methods: This was a secondary analysis of the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be (nuMoM2b). Of 10,038 participants, 1977 (enriched for adverse outcomes) had blood, which had been drawn at the first (6w0d-13w6d) and second (16w0d-21w6d) visits, assayed for sFlt-1 and PlGF, allowing for the calculation of sFlt-1:PlGF ratios from both visits as well as the change between visits. The primary outcome for this analysis was preeclampsia with severe features. The predictive ability of the sFlt-1:PlGF ratio was compared to that of the USPSTF risk assessment algorithm using area under the receiver operating characteristic curves (AUROC). Youden indexes were used to identify optimal sFlt-1:PlGF ratio cut-points. The predictive characteristics of these cut-points were compared to those of a positive USPSTF risk assessment result. Results: Preeclampsia with severe features was diagnosed in 240 (12.1%) eligible participants, among whom the mean gestational age at delivery was 36w0d. The optimal sFlt-1:PlGF ratio for predicting this outcome was 19.1 at visit 1, 6.2 at visit 2, and a decrease of 15.0 between visits. The sFlt-1:PlGF ratio was inferior to the USPSTF risk assessment algorithm in predicting this diagnosis (AUROC: 0.51-0.60 vs. 0.60, Conclusions: Early pregnancy sFLt-1:PlGF ratio is a poor risk assessment tool for preeclampsia with severe features.

Indexed as

placental analytespreeclampsia predictionpreeclampsia risk screeningpreeclampsia risk stratificationpreeclampsia with severe featuressFlt‐1:PlGF

Identifiers

PMID42597109
PMCPMC13344568

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.