Evidence map›Paper›PMID 41629900›Full record

SynthesisBMC medicine2026

Early gestational prediction of spontaneous preterm birth using a validated three-protein serum biomarker panel.

Qiong Luo, Juan Wei, Yun Ding, Yixuan Chen, Linlin Wu, C James Chou, Xiaohua Luo, Negin Ghafourian, Jian Tao, Bo Jin and 22 more

Abstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in BMC medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

32 authors.

Qiong Luo *Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, China. luoq@zju.edu.cn.
Juan Wei *Women's Hospital, Zhejiang University School of Medicine, Hangzhou, 310006, China.
Yun Ding *School of Medicine, Stanford University, Stanford, CA, 94305, USA.
Yixuan ChenShenzhen Maternity & Child Healthcare Hospital, Shenzhen, 518028, China.
Linlin WuShenzhen Maternity & Child Healthcare Hospital, Shenzhen, 518028, China.
C James ChouOncoOmicsDx Clinical Laboratory, Rockville, MD, 20850, USA.
Xiaohua LuoThe Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China.
Negin GhafourianOncoOmicsDx Clinical Laboratory, Rockville, MD, 20850, USA.
Jian TaoOncoOmicsDx Clinical Laboratory, Rockville, MD, 20850, USA.
Bo JinOncoOmicsDx Clinical Laboratory, Rockville, MD, 20850, USA.
Kuo-Jung SuOncoOmicsDx Clinical Laboratory, Rockville, MD, 20850, USA.
Richard D MortensenOncoOmicsDx Clinical Laboratory, Rockville, MD, 20850, USA.
James SchillingOncoOmicsDx Clinical Laboratory, Rockville, MD, 20850, USA.
Zhi HanSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Naoto OzawaSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Takumi IchikawaSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Ruben Y LuoSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Karl G SylvesterSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Scott R CeresnakSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Ronald J WongSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Lu TianSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Ivana MarićSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Nima AghaeepourSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Brice GaudilliereSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Martin S AngstSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Gary M ShawSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Doff McElhinneySchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Harvey J CohenSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Gary L DarmstadtSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Jianmin NiuShenzhen Maternity & Child Healthcare Hospital, Shenzhen, 518028, China.
David K StevensonSchool of Medicine, Stanford University, Stanford, CA, 94305, USA.
Xuefeng B LingSchool of Medicine, Stanford University, Stanford, CA, 94305, USA. bxling@stanford.edu.

Funding

The National Key Research and Development Program of China No. SQ2022YFC2700013, 2022YFC2704601
6 · The paper itself

Abstract

backgroundSpontaneous preterm birth (sPTB) remains a major contributor to neonatal morbidity and mortality, with limited reliable early prediction tools. Existing biomarkers, such as the insulin-like growth factor-binding protein 4 (IBP4) to sex hormone-binding globulin (SHBG) ratio, offer modest predictive performance and are restricted to mid-gestation use (18-20 weeks), limiting their utility for timely intervention. We aimed to develop and validate a novel serological test based on early-gestational sampling to predict the risk of sPTB.

methodsWe conducted a meta-analysis of 18 placental transcriptomic datasets to identify candidate genes associated with sPTB, resulting in 21 protein candidates tested by targeted proteomics. We developed a three-protein panel (glutathione peroxidase 3, GPX3; nidogen-1, NID1; and pappalysin-2, PAPPA2) and validated it in four independent cohorts (456 subjects and 1048 serum specimens) from the USA and Asia. Longitudinal serum samples were collected from 5 weeks and were analyzed using mass spectrometry and ELISA platforms. Predictor performance was compared to the IBP4/SHBG ratio.

resultsThe three-protein predictor (GPX3, NID1, and PAPPA2) demonstrated reproducible and superior performance across cohorts: AUC 0.74 (95% CI 0.59-0.88) in Alabama, 0.93 (95% CI 0.88-0.99) in California, 0.80 (95% CI 0.75-0.85) in Asia 1, and 0.83 (95% CI 0.70-0.95) in Asia 2. This outperformed the IBP4/SHBG ratio, which achieved AUCs of 0.68 (95% CI 0.50-0.89), 0.77 (95% CI 0.67-0.88), 0.59 (95% CI 0.52-0.65), and 0.61 (95% CI 0.50-0.75), respectively. Across obstetric trimesters, the three-protein panel maintained high predictive accuracy in the first and second trimesters (AUROC 0.82-0.97), the window when preventive interventions such as progesterone, cerclage, and low-dose aspirin are most effective. Kaplan-Meier analyses confirmed significantly earlier delivery among high-risk pregnancies identified by the three-protein panel.

conclusionsThis maternal serum test provides a reliable approach for early risk assessment of sPTB. The three-protein panel demonstrated reproducible performance across cohorts and across PPROM-positive and PPROM-negative phenotypes, with the strongest discrimination in the first and second trimesters, when preventive therapies such as progesterone or cerclage are most effective. These findings support its potential as an early, clinically actionable screening tool for improving pregnancy outcomes.

Indexed as

BiomarkersPremature BirthAdultFemaleGestational AgeHumansPregnancyPregnancy-Associated Plasma Protein-AProteomicsBiomarkersPAPPA2 protein, humanPregnancy-Associated Plasma Protein-AAnd Risk predictionPregnancyProteomicsSerum biomarkersSpontaneous preterm birth

Identifiers

PMID41629900
PMCPMC12955166

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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.