- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06385366
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)
Study Overview
Status
Detailed Description
This study is estimated to enroll 663 pregnant women with adverse pregnancy complications, including 221 cases of PE/eclampsia, 221 cases of SPB due to Preterm premature rupture of membranes (PPROM) or preterm labor, and 221 cases of GDM. Furthermore, the control group will enroll 442 participants, who are healthy pregnancies, ≥ 37 weeks of gestation. Study subjects who participate should meet the study inclusion and exclusion criteria:
As part of the protocol, demographic data, medical and family history, outcomes at delivery, and any relevant prior concomitant medication data will be recorded during follow-up visits. All participants are to be followed until birth delivery.
SAMPLE COLLECTION
- 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.
- A case report forms (CRF-1 and CRF-2) are used to collect demographic data, medical and family history, any relevant prior concomitant medication data, and outcomes at delivery.
The study end date of a participant is estimated within 7 months since her enrollment date.
Study Type
Enrollment (Estimated)
Contacts and Locations
Study Locations
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Hồ Chí Minh
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Ho Chi Minh City, Hồ Chí Minh, Vietnam
- Medical Genetics Institute
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Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
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
Exclusion Criteria:
- 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).
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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Characteristics of pregnant women at 1st trimester (9-13 weeks 6 days of gestation)
Time Frame: 12 months
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Observe the characteristics of pregnant women at 1st trimester (9-13 weeks 6 days of gestation): clinical features, cffDNA, cfRNA
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12 months
|
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Characteristics of pregnant women at recruitment
Time Frame: 12 months
|
Characteristics of pregnant women at recruitment: clinical features, cffDNA, cfRNA
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12 months
|
|
Define the significant differences between cases and controls
Time Frame: 12 months
|
Comparison between clinical features, cffDNA, and cfRNA of early pregnancy and at recruitment, then defines the significant differences between cases and controls
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12 months
|
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The development of learning machine models
Time Frame: 12 months
|
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.
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12 months
|
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Evaluation of the developed models
Time Frame: 12 months
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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
|
Collaborators and Investigators
Sponsor
Collaborators
Investigators
- Principal Investigator: Hoa Giang, PhD, MGI
Publications and helpful links
General Publications
- Fonseca 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.
- Hajian-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.
- Roberge 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.
- 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.
- Camunas-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.
- Gabbay-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.
- Chaemsaithong 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.
- Rani 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.
- Reicher 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.
- Hod 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.
- Karapetian 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.
- Munchel 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.
- Zhou 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.
- Dugoff 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.
- Darghahi 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.
- Weiner 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.
- Guo 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.
- Del 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.
- Becking 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.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
- Urogenital Diseases
- Endocrine System Diseases
- Female Urogenital Diseases and Pregnancy Complications
- Metabolic Diseases
- Obstetric Labor, Premature
- Obstetric Labor Complications
- Glucose Metabolism Disorders
- Diabetes Mellitus
- Hypertension, Pregnancy-Induced
- Premature Birth
- Diabetes, Gestational
- Pre-Eclampsia
- Pregnancy Complications
Other Study ID Numbers
- GS_NP1
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
IPD Sharing Time Frame
IPD Sharing Access Criteria
IPD Sharing Supporting Information Type
- STUDY_PROTOCOL
- SAP
- ICF
- CSR
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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