Developing & Evaluating Models for Early Predicting Obstetrical Diseases in Pregnant Women by Non-invasive Prenatal Test
Developing and Evaluating Models for Early Prediction of Obstetrical Diseases: Preeclampsia, Spontaneous Preterm Birth, and Gestational Diabetes in The Pregnant Women Performed Non-invasive Prenatal Screening (NIPT)
1 other identifier
observational
1,105
1 country
1
Brief Summary
This is Observational study, aiming to investigate the potentiality of cffDNA and cfRNA by a non-invasive test, in combination with clinical characteristics, to establish models for early screening and predicting high-risk pregnancy of PE, SPB, and GDM in Vietnam.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started May 2024
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
April 22, 2024
CompletedFirst Posted
Study publicly available on registry
April 26, 2024
CompletedStudy Start
First participant enrolled
May 10, 2024
CompletedPrimary Completion
Last participant's last visit for primary outcome
November 6, 2025
CompletedStudy Completion
Last participant's last visit for all outcomes
November 6, 2025
CompletedJuly 16, 2025
July 1, 2025
1.5 years
April 22, 2024
July 12, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (5)
Characteristics of pregnant women at 1st trimester (9-13 weeks 6 days of gestation)
Observe the characteristics of pregnant women at 1st trimester (9-13 weeks 6 days of gestation): clinical features, cffDNA, cfRNA
12 months
Characteristics of pregnant women at recruitment
Characteristics of pregnant women at recruitment: clinical features, cffDNA, cfRNA
12 months
Define the significant differences between cases and controls
Comparison between clinical features, cffDNA, and cfRNA of early pregnancy and at recruitment, then defines the significant differences between cases and controls
12 months
The development of learning machine models
The development of learning machine models involved potential factors that help predict events of interest (PE, SPB, and GDM). From cfRNA and cfDNA data, factors that differ between the two groups will be identified and evaluated for their potentiality in predicting high-risk individuals. The Receiver Operating Characteristic (ROC) curve and values of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy were used to determine the validity of the constructed model.
12 months
Evaluation of the developed models
Evaluation of the developed models by determining their sensitivity, specificity, area under the ROC Curve (AUC), positive predictive value (PPV), negative predictive value (NPV), and accuracy.
12 months
Eligibility Criteria
This study population will include women with singleton pregnancies, who are diagnosed Preeclampsia/eclampsia, Preterm premature rupture of membranes (PPROM)/preterm labor leading to SPB, and/or gestational diabetes mellitus or who are healthy pregnancy at ≥ 37 weeks of gestation.
You may qualify if:
- At recruitment, women with singleton pregnancies must fulfill the conditions:
- Cases: diagnosis of Preeclampsia/eclampsia, Preterm premature rupture of membranes (PPROM)/preterm labor leading to SPB, and/or gestational diabetes mellitus.
- Controls: healthy pregnancy at ≥ 37 weeks of gestation
- History of undergoing non-invasive prenatal testing (NIPT) at 9-13 weeks 6 days of gestation at Gene Solutions Lab. NIPT report was at low-risk. No abnormal fetal and maternal conditions were confirmed at NIPT time.
- NIPT blood sample is available according to post-test sample storage procedures at Gene Solutions Lab.
- Consent to voluntarily participate in the study
You may not qualify if:
- Multiple pregnancies
- Pregnancy with any genetic abnormality
- Pregnancy with any fetal structural abnormality
- Pregnancy with indications for termination, miscarriage, or stillbirth due to other complications
- Maternal medical history of diabetes mellitus type 1/ type 2, chronic hypertension, and chronic kidney disease. Maternal abnormal uterus anatomy and history of cervical cone biopsy sample or loop electrocautery excision procedures (LEEP).
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- Gene Solutionslead
- Medical Genetics Institute (MGI)collaborator
Study Sites (1)
Medical Genetics Institute
Ho Chi Minh City, Hồ Chà Minh, Vietnam
Related Publications (19)
Brosens I, Pijnenborg R, Vercruysse L, Romero R. The "Great Obstetrical Syndromes" are associated with disorders of deep placentation. Am J Obstet Gynecol. 2011 Mar;204(3):193-201. doi: 10.1016/j.ajog.2010.08.009. Epub 2010 Nov 20.
PMID: 21094932BACKGROUNDGabbay-Benziv R, Baschat AA. Gestational diabetes as one of the "great obstetrical syndromes"--the maternal, placental, and fetal dialog. Best Pract Res Clin Obstet Gynaecol. 2015 Feb;29(2):150-5. doi: 10.1016/j.bpobgyn.2014.04.025. Epub 2014 Aug 20.
PMID: 25225057BACKGROUNDChaemsaithong P, Sahota DS, Poon LC. First trimester preeclampsia screening and prediction. Am J Obstet Gynecol. 2022 Feb;226(2S):S1071-S1097.e2. doi: 10.1016/j.ajog.2020.07.020. Epub 2020 Jul 16.
PMID: 32682859BACKGROUNDRani PR, Begum J. Screening and Diagnosis of Gestational Diabetes Mellitus, Where Do We Stand. J Clin Diagn Res. 2016 Apr;10(4):QE01-4. doi: 10.7860/JCDR/2016/17588.7689. Epub 2016 Apr 1.
PMID: 27190902BACKGROUNDReicher L, Fouks Y, Yogev Y. Cervical Assessment for Predicting Preterm Birth-Cervical Length and Beyond. J Clin Med. 2021 Feb 7;10(4):627. doi: 10.3390/jcm10040627.
PMID: 33562187BACKGROUNDHod M, Lieberman N. Maternal-fetal medicine--how can we practically connect the "M" to the "F"? Best Pract Res Clin Obstet Gynaecol. 2015 Feb;29(2):270-83. doi: 10.1016/j.bpobgyn.2014.06.008. Epub 2014 Aug 21.
PMID: 25225060BACKGROUNDRoberge S, Nicolaides K, Demers S, Hyett J, Chaillet N, Bujold E. The role of aspirin dose on the prevention of preeclampsia and fetal growth restriction: systematic review and meta-analysis. Am J Obstet Gynecol. 2017 Feb;216(2):110-120.e6. doi: 10.1016/j.ajog.2016.09.076. Epub 2016 Sep 15.
PMID: 27640943BACKGROUNDFonseca EB, Celik E, Parra M, Singh M, Nicolaides KH; Fetal Medicine Foundation Second Trimester Screening Group. Progesterone and the risk of preterm birth among women with a short cervix. N Engl J Med. 2007 Aug 2;357(5):462-9. doi: 10.1056/NEJMoa067815.
PMID: 17671254BACKGROUNDBecking EC, Scheffer PG, Henrichs J, Bax CJ, Crombag NMTH, Weiss MM, Macville MVE, Van Opstal D, Boon EMJ, Sistermans EA, Henneman L, Schuit E, Bekker MN. Fetal fraction of cell-free DNA in noninvasive prenatal testing and adverse pregnancy outcomes: a nationwide retrospective cohort study of 56,110 pregnant women. Am J Obstet Gynecol. 2024 Aug;231(2):244.e1-244.e18. doi: 10.1016/j.ajog.2023.12.008. Epub 2023 Dec 12.
PMID: 38097030BACKGROUNDKarapetian capital A, Cyrilliccapital O, Cyrillic, Baev capital O, CyrillicR, Sadekova capital A, Cyrilliccapital A, Cyrillic, Krasnyi capital A, Cyrilliccapital EM, Cyrillic, Sukhikh GT. Cell-Free Foetal DNA as a Useful Marker for Preeclampsia Prediction. Reprod Sci. 2021 May;28(5):1563-1569. doi: 10.1007/s43032-021-00466-w. Epub 2021 Jan 21.
PMID: 33475978BACKGROUNDMunchel S, Rohrback S, Randise-Hinchliff C, Kinnings S, Deshmukh S, Alla N, Tan C, Kia A, Greene G, Leety L, Rhoa M, Yeats S, Saul M, Chou J, Bianco K, O'Shea K, Bujold E, Norwitz E, Wapner R, Saade G, Kaper F. Circulating transcripts in maternal blood reflect a molecular signature of early-onset preeclampsia. Sci Transl Med. 2020 Jul 1;12(550):eaaz0131. doi: 10.1126/scitranslmed.aaz0131.
PMID: 32611681BACKGROUNDZhou S, Li J, Yang W, Xue P, Yin Y, Wang Y, Tian P, Peng H, Jiang H, Xu W, Huang S, Zhang R, Wei F, Sun HX, Zhang J, Zhao L. Noninvasive preeclampsia prediction using plasma cell-free RNA signatures. Am J Obstet Gynecol. 2023 Nov;229(5):553.e1-553.e16. doi: 10.1016/j.ajog.2023.05.015. Epub 2023 May 19.
PMID: 37211139BACKGROUNDDugoff L, Barberio A, Whittaker PG, Schwartz N, Sehdev H, Bastek JA. Cell-free DNA fetal fraction and preterm birth. Am J Obstet Gynecol. 2016 Aug;215(2):231.e1-7. doi: 10.1016/j.ajog.2016.02.009. Epub 2016 Feb 11.
PMID: 26875947BACKGROUNDDarghahi R, Mobaraki-Asl N, Ghavami Z, Pourfarzi F, Hosseini-Asl S, Jalilvand F. Effect of cell-free fetal DNA on spontaneous preterm labor. J Adv Pharm Technol Res. 2019 Jul-Sep;10(3):117-120. doi: 10.4103/japtr.JAPTR_371_18.
PMID: 31334093BACKGROUNDCamunas-Soler J, Gee EPS, Reddy M, Mi JD, Thao M, Brundage T, Siddiqui F, Hezelgrave NL, Shennan AH, Namsaraev E, Haverty C, Jain M, Elovitz MA, Rasmussen M, Tribe RM. Predictive RNA profiles for early and very early spontaneous preterm birth. Am J Obstet Gynecol. 2022 Jul;227(1):72.e1-72.e16. doi: 10.1016/j.ajog.2022.04.002. Epub 2022 Apr 6.
PMID: 35398029BACKGROUNDWeiner CP, Cuckle H, Weiss ML, Buhimschi IA, Dong Y, Zhou H, Ramsey R, Egerman R, Buhimschi CS. Evaluation of a Maternal Plasma RNA Panel Predicting Spontaneous Preterm Birth and Its Expansion to the Prediction of Preeclampsia. Diagnostics (Basel). 2022 May 27;12(6):1327. doi: 10.3390/diagnostics12061327.
PMID: 35741140BACKGROUNDGuo Z, Yang F, Zhang J, Zhang Z, Li K, Tian Q, Hou H, Xu C, Lu Q, Ren Z, Yang X, Lv Z, Wang K, Yang X, Wu Y, Yang X. Whole-Genome Promoter Profiling of Plasma DNA Exhibits Diagnostic Value for Placenta-Origin Pregnancy Complications. Adv Sci (Weinh). 2020 Feb 18;7(7):1901819. doi: 10.1002/advs.201901819. eCollection 2020 Apr.
PMID: 32274292BACKGROUNDDel Vecchio G, Li Q, Li W, Thamotharan S, Tosevska A, Morselli M, Sung K, Janzen C, Zhou X, Pellegrini M, Devaskar SU. Cell-free DNA Methylation and Transcriptomic Signature Prediction of Pregnancies with Adverse Outcomes. Epigenetics. 2021 Jun;16(6):642-661. doi: 10.1080/15592294.2020.1816774. Epub 2020 Oct 13.
PMID: 33045922BACKGROUNDHajian-Tilaki K. Sample size estimation in diagnostic test studies of biomedical informatics. J Biomed Inform. 2014 Apr;48:193-204. doi: 10.1016/j.jbi.2014.02.013. Epub 2014 Feb 26.
PMID: 24582925BACKGROUND
Related Links
Biospecimen
At recruitment, 10 mL of peripheral blood is collected for cffDNA and cfRNA analyses. An available NIPT sample at 1st trimester is processed for cffDNA and cfRNA analyses.
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Study Design
- Study Type
- observational
- Observational Model
- COHORT
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- INDUSTRY
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
April 22, 2024
First Posted
April 26, 2024
Study Start
May 10, 2024
Primary Completion
November 6, 2025
Study Completion
November 6, 2025
Last Updated
July 16, 2025
Record last verified: 2025-07
Data Sharing
- IPD Sharing
- Will share
- Shared Documents
- STUDY PROTOCOL, SAP, ICF, CSR
- Time Frame
- December 2025
- Access Criteria
- GS\ NP1
Anonymized data of this study may be requested for publication by the journals. Sharing anonymized data with suitable study will be decided by the Sponsor, Principles Investigator and the authority agency. No identifiable information will be share with any other person or organization than authorized in this study.