Evidence map›Paper›PMID 28725051›Full record

ArticleScientific reports2017

Mammographic density, blood telomere length and lipid peroxidation.

Natalie J Erdmann, Lea A Harrington, Lisa J Martin

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 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.

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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. 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

3 authors.

Natalie J ErdmannPrincess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2M9, Canada.
Lea A HarringtonInstitute for Research in Immunology & Cancer, Départment de Médécine, Université de Montréal, Montréal, QC, H3T 1J4, Canada.
Lisa J MartinPrincess Margaret Cancer Centre, University Health Network, Toronto, ON M5G 2M9, Canada. lmartin@uhnres.utoronto.ca.

Funding

A unique murine model for human agingR01AG024398 · NIA · UNIVERSITY HEALTH NETWORK · PI HARRINGTON, LEA A · 2004 to 2008
$1.4M
Howard Hughes Medical InstituteNIA NIH HHS R01 AG024398Wellcome Trust
6 · The paper itself

Abstract

Extensive mammographic density is a strong risk factor for breast cancer, but may also be an indicator of biological age. In this study we examined whether mammographic density is related to blood telomere length, a potential marker of susceptibility to age-related disease. We measured mammographic density by a computer assisted method and blood telomere length using a validated PCR method. Urinary malondialdehyde (MDA), a marker of lipid peroxidation, was measured in 24 hour urine collections. In the 342 women examined telomere length was negatively correlated with age, was lower in postmenopausal compared to premenopausal women and in smokers compared to non-smokers, and was positively correlated with urinary MDA. Telomere length was not associated with percent mammographic density or dense area, before or after adjustment for risk factors and MDA. However, there was a significant interaction between telomere length and MDA in their association with mammographic density. At lower levels of MDA, mammographic density and telomere length were inversely associated; while at high levels of MDA, there was evidence of a J-shaped association between mammographic density and telomere length. Further work is need to replicate these results and to examine the association of mammographic density with age-related chronic disease and mortality.

Indexed as

Lipid PeroxidationMammographyAdultBloodBreast DensityFemaleHumansMalondialdehydeMiddle AgedTelomereMalondialdehyde

Identifiers

PMID28725051
PMCPMC5517610

What OpenQuestion holds

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Registered trials

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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.