Evidence map›Paper›PMID 42131411›Full record

ReviewTzu chi medical journal

Blood-based predictive biomarkers for preterm birth: Redefining risk stratification in modern perinatal care.

Wiku Andonotopo, Muhammad Adrianes Bachnas, Julian Dewantiningrum, Mochammad Besari Adi Pramono, I Nyoman Hariyasa Sanjaya, Ernawati Darmawan, Dudy Aldiansyah, Milan Stanojevic, Asim Kurjak

Abstract readReview
In one paragraph

Review in Tzu chi medical journal. 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

9 authors.

Wiku AndonotopoDivision of Fetomaternal, Women Health Center, Department of Obstetrics and Gynecology, Ekahospital BSD City, Tangerang, Banten, Indonesia.
Muhammad Adrianes BachnasDivision of Fetomaternal, Department of Obstetrics and Gynecology, Medical Faculty of Sebelas Maret University, Dr. Moewardi Hospital, Solo, Surakarta, Indonesia.
Julian DewantiningrumDivision of Fetomaternal, Department of Obstetrics and Gynecology, Medical Faculty of Diponegoro University, Dr. Kariadi Hospital, Semarang, Indonesia.
Mochammad Besari Adi PramonoDivision of Fetomaternal, Department of Obstetrics and Gynecology, Medical Faculty of Diponegoro University, Dr. Kariadi Hospital, Semarang, Indonesia.
I Nyoman Hariyasa SanjayaDivision of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Faculty of Medicine, Universitas Udayana, Prof. Dr. I.G.N.G. Ngoerah General Hospital, Bali, Indonesia.
Ernawati DarmawanDivision of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Faculty of Medicine, Universitas Airlangga, Dr. Soetomo Hospital, Surabaya, Indonesia.
Dudy AldiansyahDivision of Fetomaternal, Department of Obstetrics and Gynecology, Faculty of Medicine, Universitas Sumatera Utara, H. Adam Malik General Hospital, Medan, Sumatera Utara, Indonesia.
Milan StanojevicDepartment of Neonatology and Rare Diseases, Medical University of Warsaw, Warsaw, Poland.
Asim KurjakDepartment of Obstetrics and Gynecology, Medical School University of Zagreb, Zagreb, Croatia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Spontaneous preterm birth (sPTB) remains a leading cause of neonatal morbidity and mortality worldwide, with current screening tools - such as cervical length measurement and fetal fibronectin - showing limited predictive value, particularly in asymptomatic women. Recent advances in molecular diagnostics have identified blood-based biomarkers that capture transcriptomic, proteomic, and metabolomic changes preceding labor. This systematic review synthesizes recent high-quality studies published between 2018 and 2025, selected through a Preferred Reporting Items for Systematic Reviews and Meta-analyses-guided search and appraised using AMSTAR-2 and the Newcastle-Ottawa Scale. Transcriptomic signatures, including cell-free RNA profiles, demonstrate area-under-the-curve (AUC) values up to 0.94 when measured in early gestation (10-20 weeks). Proteomic panels targeting inflammatory mediators and matrix-remodeling proteins achieve AUCs of 0.80-0.89, while metabolomic assays identify arginine derivatives and lipid shifts with AUCs of 0.78-0.84. Multiomic models integrating these molecular layers with machine-learning algorithms further improve prediction, reaching AUCs above 0.93 across diverse cohorts. Optimal sampling windows range from 10 to 24 weeks, with the strongest evidence for use in high-risk women or as part of universal mid-trimester screening. Emerging clinical pathways outline how these assays could integrate into prenatal care to enable timely interventions such as progesterone therapy, cervical cerclage, or intensified monitoring. Key barriers to implementation include assay standardization, cost, regulatory approval, and ethical considerations in patient counseling. Standardized protocols, multicenter validation, and equitable deployment strategies will be critical to translating these promising technologies into practice. If successfully implemented, blood-based predictive models could help shift obstetric care toward more personalized and preventive management of sPTB.

Indexed as

Blood-based testingPerinatal riskPrecision obstetricsPredictive biomarkersPreterm birth

Identifiers

PMID42131411
PMCPMC13167092

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

None linked

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.