Evidence map›Paper›PMID 31742824›Full record

ArticleCancer science2020

Prevalence of hereditary breast and ovarian cancer (HBOC) predisposition gene mutations among 882 HBOC high-risk Chinese individuals.

Di Shao, Shaomin Cheng, Fengming Guo, Changbin Zhu, Yuying Yuan, Kunling Hu, Zhe Wang, Xuan Meng, Xin Jin, Yun Xiong and 6 more

Open access · goldAbstract read
In one paragraph

Article in Cancer science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 11% 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

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 38 citations in OpenAlex.

  1. Summary ofGenes · 2020
    Pooled it
  2. Article
  3. Article
  4. Article
  5. Prevalence of BRCA1 and BRCA2 mutations in ovarian cancer patients from Yunnan Province in southwest China.European journal of cancer prevention : the official journal of the European Cancer Prevention Organisation (ECP) · 2025
    Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Hereditary breast cancer and fertility preservation outcomes.Journal of assisted reproduction and genetics · 2022
    Article
  18. Review
  19. Article
  20. Article
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

16 authors at 2 institutions in 2 countries.

Di ShaoBGI Genomics, BGI-Shenzhen, Shenzhen, China.ORCID https://orcid.org/0000-0002-1485-2074
Shaomin ChengBGI Genomics, BGI-Shenzhen, Shenzhen, China.
Fengming GuoBGI Genomics, BGI-Shenzhen, Shenzhen, China.
Changbin ZhuBGI Genomics, BGI-Shenzhen, Shenzhen, China.
Yuying YuanBGI Genomics, BGI-Shenzhen, Shenzhen, China.
Kunling HuBGI Genomics, BGI-Shenzhen, Shenzhen, China.
Zhe WangBGI Genomics, BGI-Shenzhen, Shenzhen, China.
Xuan MengBGI Genomics, BGI-Shenzhen, Shenzhen, China.
Xin JinBGI Genomics, BGI-Shenzhen, Shenzhen, China.
Yun XiongBGI Genomics, BGI-Shenzhen, Shenzhen, China.
Xianghua ChaiBGI Genomics, BGI-Shenzhen, Shenzhen, China.
Hong LiBGI Genomics, BGI-Shenzhen, Shenzhen, China.
Yu ZhangBGI Genomics, BGI-Shenzhen, Shenzhen, China.
Hongyun ZhangBGI Genomics, BGI-Shenzhen, Shenzhen, China.
Jihong LiuDepartment of Gynecology, Sun Yat-sen University Cancer Center, Guangzhou, China.
Mingzhi YeBGI Genomics, BGI-Shenzhen, Shenzhen, China.
BGI Group (China) · CNSun Yat-sen University · CN

Funding

Guangzhou Science and Technology Plan Projects Health Medical Collaborative Innovation Program of Guangzhou 201400000004-5Guangzhou Science and Technology Plan Projects Health Medical Collaborative Innovation Program of Guangzhou 201803040019National Key R&D Program of China 0905400National Key R&D Program of China 2016YFCSpecial Foundation for High-level Talents of Guangdong 2016TX03R171
6 · The paper itself

Abstract

Identification of deleterious variants in hereditary breast and ovarian cancer (HBOC) susceptibility genes allows for increased clinical surveillance and early detection, and could predict the response to poly (ADP-ribose) polymerase (PARP) inhibitor in patients with advanced ovarian carcinomas. To determine the prevalence and clinical prediction factors for HBOC syndrome, 882 selected individuals underwent multigene panel testing for HBOC risk assessment during the period from January 2015 to March 2018. Overall, 176 deleterious mutations were observed in 19.50% (n = 172) of individuals. Twenty-six of 176 mutations could not be retrieved in related public databases and were considered to be novel. Among patients with ovarian cancer, 115 deleterious mutations were identified in 429 patients (48.6%) with significant enrichment for a family history of breast or ovarian cancer syndrome (P < .05). In the breast cancer subgroup, 31 deleterious mutations were identified in 261 patients. Besides BRCA1 (8; 25.8%) and BRCA2 (11; 35.5%), the most frequently occurring genes, an additional 12 deleterious mutations (38.7%) were found in seven other susceptibility genes. Higher mutation incidence (57.9%) was observed in subjects with histories of breast and ovarian cancer. Our results highlighted the genetic heterogeneity of HBOC and the efficiency of a multigene panel in carrying out risk assessment.

Indexed as

Genetic HeterogeneityMutationAdolescentAdultAgedAged, 80 and overAsian PeopleChinaEarly Detection of CancerFemaleGenetic Predisposition to DiseaseGenetic TestingHereditary Breast and Ovarian Cancer SyndromeHigh-Throughput Nucleotide SequencingHumansMiddle AgedBRCA1BRCA2HBOCmutationNGS

Identifiers

PMID31742824
PMCPMC7004523
OpenAlexW2990275766

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.