Evidence map›Paper›PMID 30561789›Full record

ArticleInternational journal of cancer2019

The relationship between terminal duct lobular unit features and mammographic density among Chinese breast cancer patients.

Hyuna Sung, Changyuan Guo, Erni Li, Jing Li, Ruth M Pfeiffer, Jennifer L Guida, Renata Cora, Nan Hu, Joseph Deng, Jonine D Figueroa and 4 more

Open access · bronzeAbstract read
In one paragraph

Article in International journal of cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
0.9field-weighted citation impact, top 22% 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

12 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Associations of Stem Cell Markers with Lobular Involution in Benign Breast Tissue.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025
    Article
  3. Review
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Automated Quantitative Measures of Terminal Duct Lobular Unit Involution and Breast Cancer Risk.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020
    Article
  11. Article
  12. 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

14 authors at 4 institutions in 3 countries.

Hyuna SungDivision of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.ORCID 0000-0002-8021-5997
Changyuan GuoNational Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Erni LiNational Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Jing LiNational Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Ruth M PfeifferDivision of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Jennifer L GuidaDivision of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Renata CoraIndependent Contractor, CT(ASCP), MB(ASCP), Stamford, Connecticut, USA.
Nan HuDivision of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Joseph DengDivision of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Jonine D FigueroaDivision of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Mark E ShermanDivision of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Gretchen L GierachDivision of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.
Ning LuNational Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Xiaohong R YangDivision of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA.ORCID 0000-0003-4451-8664
National Institutes of Health · USChinese Academy of Medical Sciences & Peking Union Medical College · CNAmerican Cancer Society · USIndependent Sector · US

Funding

Intramural NIH HHS Z99 CA999999
6 · The paper itself

Abstract

Extensive mammographic density (MD), a well-established breast cancer risk factor, is a radiological representation of stromal and epithelial breast tissue content. In studies conducted predominantly among Caucasian women, histologic measures of reduced terminal duct lobular unit (TDLU) involution have been correlated with extensive MD, but independently associated with breast cancer risk. We therefore examined associations between TDLU measures and MD among Chinese women, a low-risk population but with high prevalence of dense breasts. Diagnostic pre-treatment digital mammograms were obtained from 144 breast cancer cases at a tertiary hospital in Beijing and scored using the Breast Imaging Reporting and Data System (BI-RADS) density classification. TDLU features were assessed using three standardized measures (count/100 mm

Indexed as

AdultAgedAge FactorsAsian PeopleBreast DensityBreast NeoplasmsFemaleHumansMammary Glands, HumanMammographyMiddle AgedTriple Negative Breast NeoplasmsYoung AdultBI-RADSbreast cancerChinamammographic densityterminal ductal lobular unit (TDLU) involution

Identifiers

PMID30561789
PMCPMC6488407
OpenAlexW2904869424

What OpenQuestion holds

Textmetadata
LicenceTDM
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.