Evidence map›Paper›PMID 32241951›Full record

ArticleCancer research2020

Heritability of Mammographic Breast Density, Density Change, Microcalcifications, and Masses.

Natalie Holowko, Mikael Eriksson, Ralf Kuja-Halkola, Shadi Azam, Wei He, Per Hall, Kamila Czene

Open access · bronzeAbstract read
PubMed Publisher
In one paragraph

Article in Cancer research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.6field-weighted citation impact, top 8% 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

20 citing papers in PubMed, 37 citations in OpenAlex.

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  19. Predictors of mammographic microcalcifications.International journal of cancer · 2021
    Article
  20. Heritability of mammographic breast density.Quantitative imaging in medicine and surgery · 2020
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Natalie Holowko *Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. natalie.holowko@ki.se.ORCID 0000-0002-9124-3264
Mikael Eriksson *Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0001-8135-4270
Ralf Kuja-HalkolaDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0002-3765-2067
Shadi AzamDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0002-3273-1970
Wei HeDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Per HallDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.ORCID 0000-0002-5640-9126
Kamila CzeneDepartment of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
Karolinska Institutet · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mammographic features influence breast cancer risk and are used in risk prediction models. Understanding how genetics influence mammographic features is important because the mechanisms through which they are associated with breast cancer are not well known. Here, using mammographic screening history and detailed questionnaire data from 56,820 women from the KARMA prospective cohort study, we investigated the association between a genetic predisposition to breast cancer and mammographic features among women with a family history of breast cancer (

Indexed as

AdultAgedBreastBreast DensityBreast NeoplasmsCalcinosisCase-Control StudiesEarly Detection of CancerFemaleGenetic Predisposition to DiseaseHumansMammographyMedical History TakingMiddle AgedPolymorphism, Single NucleotideProspective Studies

Identifiers

PMID32241951
OpenAlexW3015182308

What OpenQuestion holds

Textmetadata
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.