Evidence map›Paper›PMID 22143145›Full record

ReviewNature reviews. Clinical oncology2011

Clinical and epidemiological issues in mammographic density.

Valentina Assi, Jane Warwick, Jack Cuzick, Stephen W Duffy

Registry-linked trialAbstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Clinical oncology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02619123 (Tailored Screening for Breast Cancer in Premenopausal Women. A Translational, Randomized Population-based Trial), which is not on this map. Cited by 50 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 6 pooled it
–field-weighted citation impact
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.

NCT02619123 naunknown statusnot on this mapstarted 2013, after this paper: background citation

Tailored Screening for Breast Cancer in Premenopausal Women. A Translational, Randomized Population-based Trial

TypeinterventionalSponsorCancer Prevention and Research Institute, ItalyRan2013 to 2022Enrolled33,200ConditionsBreast CancerArmsTailored screening according to breast density, Annual invitation to mammography
3 · Its place in the literature

Who cites it

50 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. A meta-analysis on dose-response relationship between night shift work and the risk of breast cancer.Annals of oncology : official journal of the European Society for Medical Oncology · 2013
    Pooled it
  5. Pooled it
  6. A novel automated mammographic density measure and breast cancer risk.Journal of the National Cancer Institute · 2012
    Pooled it
  7. Article
  8. Education and mammographic breast density.Breast cancer research and treatment · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  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

4 authors.

Valentina AssiCenter for Cancer Prevention, Wolfson Institute of Preventive Medicine, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK.
Jane Warwick
Jack Cuzick
Stephen W Duffy

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High mammographic density is associated with an increased risk of breast cancer, and of all known breast cancer risk factors has the greatest attributable fraction. Mammographic density is estimated to account for 16% of all breast cancers, but can be altered by endogenous and exogenous hormonal factors, and generally declines with age. Confounding factors such as age, parity, menopausal status and BMI make the interpretation of mammographic density particularly challenging. Furthermore, none of the established means of measuring mammographic density are entirely satisfactory because they are time consuming or subjective. It is hoped that by adding information regarding mammographic density to existing models of breast cancer risk assessment, the accuracy of individual risk assessments can be improved. Although mammographic density has clearly been shown to be a powerful factor for predicting the risk of developing breast cancer, its potential role in assessing hormonal preventive regimens and helping to tailor screening algorithms cannot be fully realized until we have more-precise, simple and reproducible density measures.

Indexed as

Age FactorsBody Mass IndexBreast NeoplasmsEarly Detection of CancerFemaleHumansMammographyMenopauseRisk AssessmentRisk FactorsUnited States

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.