Evidence map›Paper›PMID 30976098›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2019

Identifying occult maternal malignancies from 1.93 million pregnant women undergoing noninvasive prenatal screening tests.

Xing Ji, Jia Li, Yonghua Huang, Pi-Lin Sung, Yuying Yuan, Qiang Liu, Yan Chen, Jia Ju, Yafeng Zhou, Shujia Huang and 54 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
9.5field-weighted citation impact, top 2% of its field
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

24 citing papers in PubMed, 50 citations in OpenAlex.

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  7. Observational
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  11. Non-invasive prenatal testing: when results suggests maternal cancer.Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V · 2023
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  12. Review
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  15. Prenatal DNA Sequencing for Fetal Aneuploidy Also Detects Maternal Cancer: Importance of Timely Workup and Management in Pregnant Women.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2022
    Article
  16. Article
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  19. More than an Incidentaloma: The Nonreportable NIPT.Case reports in obstetrics and gynecology · 2022
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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

64 authors at 17 institutions in 7 countries.

Xing JiCenter for Clinical Genetics, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University, School of Medicine, Shanghai, China.
Jia LiBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China.
Yonghua HuangDepartment of Obstetrics and Gynecology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of Sun Yat-Sen University, Jiangmen, Guangdong, China.
Pi-Lin SungDepartment of Obstetrics and Gynecology, Taipei Veterans General Hospital, Taipei, Taiwan.
Yuying YuanBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China.
Qiang LiuBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China.
Yan ChenBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China.
Jia JuBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China.
Yafeng ZhouBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China.
Shujia HuangBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China.
Fang ChenBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China.
Yuan HanBGI-Wuhan, BGI-Shenzhen, Wuhan, Guangdong, China.
Wen YuanBGI-Wuhan, BGI-Shenzhen, Wuhan, Guangdong, China.
Cheng FanBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China.
Qiang ZhaoDepartment of Obstetrics and Gynecology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of Sun Yat-Sen University, Jiangmen, Guangdong, China.
Haitao WuReproductive Medicine Center, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of Sun Yat-Sen University, Jiangmen, Guangdong, China.
Suihua FengDepartment of Obstetrics and Gynecology, Jiangmen Central Hospital, Affiliated Jiangmen Hospital of Sun Yat-Sen University, Jiangmen, Guangdong, China.
Weiqiang LiuKey Laboratory for Major Obstetric Diseases of Guangdong, Key Laboratory for Reproduction and Genetics of Guangdong Higher Education Institutes, Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Zhihua LiDepartment of Prenatal Diagnosis and Fetal Medicine, Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Jingsi ChenDepartment of Prenatal Diagnosis and Fetal Medicine, Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Min ChenDepartment of Prenatal Diagnosis and Fetal Medicine, Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
Hong YaoPrenatal Diagnosis Center, Southwest Hospital, Chongqing, China.
Li ZengDepartment of Obstetrics and Gynecology, Bazhong Central Hospital, Bazhong, Sichuan, China.
Tao MaDepartment of Obstetrics and Gynecology, Sichuan Provincial People's Hospital, Chengdu, Sichuan, China.
Shushu FanGenetic Diagnosis Center and Reproductive Center, Yue Bei People's Hospital, Shaoguan, Guangdong, China.
Jinman ZhangFaculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China.
Ka Yiu YuenBGI HEALTH (HK), Hong Kong, China.
So Hin ChengBGI HEALTH (HK), Hong Kong, China.
Irene Wing Shan ChikBGI HEALTH (HK), Hong Kong, China.
Nien-Tzu LiuBGI HEALTH (HK), Hong Kong, China.
Jianyu ZhuBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China.
Siyuan LinBGI HEALTH (HK), Hong Kong, China.
Jeremy CaoBGI HEALTH (HK), Hong Kong, China.
Steve TongBGI HEALTH (HK), Hong Kong, China.
Zhiyuan ShanBGI Europe A/S, Copenhagen, Denmark.
Wenyan LiBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China.
Mohammad Reza HekmatDepartment of Medical Genetics, DeNA laboratory, Tehran, Iran.
Masoud GarshasbiDepartment of Medical Genetics, DeNA laboratory, Tehran, Iran.
Javier SuelaNIMGenetics, Madrid, Spain.
Yaima TorresNIMGenetics, Madrid, Spain.
Juan C CigudosaNIMGenetics, Madrid, Spain.
F J Pérez RuizServicio de Ginecología y Obstetricia, Hospital General San Jorge, Huesca, Spain.
Laura RodríguezLaboratorio de Genética Molecular AbaCid, Hospitales HM, Madrid, Spain.
Mónica GarcíaLaboratorio de Genética Molecular AbaCid, Hospitales HM, Madrid, Spain.
Janez BernikGenePlanet Ltd, Ljubljana, Slovenia.
Eva TravenGenePlanet Ltd, Ljubljana, Slovenia.
Uršula RešDravlje Health Center-IVF, Ljubljana, Slovenia.
Nataša TulDivision of Obstetrics and Gynecology, Department of Perinatology, University Medical Centre, Ljubljana, Slovenia.
Ching-Fong TsengGene Health Co Ltd, Taipei, Taiwan.
Depeng ZhaoDepartment of Prenatal Diagnosis and Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China.
Luming SunDepartment of Prenatal Diagnosis and Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China.
Qiong PanLaboratory of Clinical Genetics, Huai'an Maternity and Child Health Care Hospital of Jiangsu Province, Yangzhou University, Huai'an, Jiangsu, China.
Li ShenDepartment of Pathology, Shanghai Pu Nan Hospital, Shanghai, China.
Mengyao DaiCenter for Clinical Genetics, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University, School of Medicine, Shanghai, China.
Yuying WangBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China.
Jian WangBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China.
Huanming YangBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China.
Ye YinBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China.
Tao DuanDepartment of Prenatal Diagnosis and Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China.ORCID http://orcid.org/0000-0001-5320-4611
Baosheng ZhuFaculty of Environmental Science and Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China.
Mahesh ChoolaniDivision of Maternal Fetal Medicine, Department of Obstetrics and Gynecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Xin JinBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China. jinxin@genomics.cn.
Yingwei ChenCenter for Clinical Genetics, Xin Hua Hospital Affiliated to Shanghai Jiao Tong University, School of Medicine, Shanghai, China. chenyingwei@xinhuamed.com.cn.
Mao MaoBGI Genomics, BGI-Shenzhen, Shenzhen, Guangdong, China. maomao@genomics.cn.ORCID http://orcid.org/0000-0002-6318-3639
BGI Group (China) · CNThird Affiliated Hospital of Guangzhou Medical University · CNKunming University of Science and Technology · CNHM Hospitales · ESJiangmen Central Hospital · CNShanghai First Maternity and Infant Hospital · CNLjubljana Passenger Transport · SILjubljana University Medical Centre · SIShanghai Jiao Tong University · CNTarbiat Modares University · IRBGI Europe (Denmark) · DKHanzhong Central Hospital · CNHospital General San Jorge · ESNational Yang Ming Chiao Tung University · TWPunan Hospital · CNShantou University · CNSouthwest Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeMultiple chromosomal aneuploidies may be associated with maternal malignancies and can cause failure of noninvasive prenatal screening (NIPS) tests. However, multiple chromosomal aneuploidies show poor specificity and selectivity for diagnosing maternal malignancies.

methodsThis multicenter retrospective analysis evaluated 639 pregnant women who tested positive for multiple chromosomal aneuploidies on initial NIPS test between January 2016 and December 2017. Women were assessed using genome profiling of copy-number variations, which was translated to cancer risk using a novel bioinformatics algorithm called the cancer detection pipeline (CDP). Sensitivity, specificity, and positive predictive value (PPV) of diagnosing maternal malignancies were compared for multiple chromosomal aneuploidies, the CDP model, and the combination of CDP and plasma tumor markers.

resultsOf the 639 subjects, 41 maternal malignant cancer cases were diagnosed. Multiple chromosomal aneuploidies predicted maternal malignancies with a PPV of 7.6%. Application of the CDP algorithm to women with multiple chromosomal aneuploidies allowed 34 of the 41 (83%) cancer cases to be identified, while excluding 422 of 501 (84.2%) of the false positive cases. Combining the CDP with plasma tumor marker testing gave PPV of 75.0%.

conclusionThe CDP algorithm can diagnose occult maternal malignancies with a reasonable PPV in multiple chromosomal aneuploidies-positive pregnant women in NIPS tests. This performance can be further improved by incorporating findings for plasma tumor markers.

Indexed as

AdultAlgorithmsAneuploidyChromosome DisordersComputational BiologyFemaleGenetic TestingHumansMaternal AgeMothersNeoplasmsNoninvasive Prenatal TestingPregnancyPrenatal DiagnosisRetrospective StudiesSensitivity and SpecificityCancer detectionMaternal malignancyMultiple chromosomal aneuploidiesNoninvasive prenatal screening testPlasma tumor marker

Identifiers

PMID30976098
OpenAlexW2938338736

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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.