Evidence map›Paper›PMID 39230626›Full record

ArticleBreast cancer research and treatment2024

Microcalcifications in benign breast biopsies: association with lesion type and risk.

Sarah Schrup, Heather Hardway, Robert A Vierkant, Stacey J Winham, Matthew R Jensen, Bryan McCauley, Tanya Hoskin, Lisa Seymour, Denice Gehling, Jessica Fischer and 7 more

Abstract read
In one paragraph

Article in Breast cancer research and treatment, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
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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

17 authors.

Sarah SchrupMayo Clinic Graduate School of Biomedical Sciences, Rochester, MN, USA. schrup.sarah@mayo.edu.
Heather HardwayDepartment of Dermatology, Mayo Clinic, Rochester, MN, USA.
Robert A VierkantQuantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Stacey J WinhamQuantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Matthew R JensenQuantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Bryan McCauleyQuantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Tanya HoskinQuantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Lisa SeymourDepartment of Surgery, Mayo Clinic, Rochester, MN, USA.
Denice GehlingDepartment of Surgery, Mayo Clinic, Rochester, MN, USA.
Jessica FischerDepartment of Surgery, Mayo Clinic, Rochester, MN, USA.
Celine M VachonQuantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
Santo MaimoneDepartment of Radiology, Mayo Clinic, Jacksonville, FL, USA.
Laura Pacheco-SpannQuantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA.
Derek C RadiskyCancer Biology, Mayo Clinic, Jacksonville, FL, USA.
Jodi M CarterDepartment of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB, Canada.
Amy C DegnimDepartment of Surgery, Mayo Clinic, Rochester, MN, USA.
Mark E ShermanQuantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA.

Funding

Women's Cancer ProgramP30CA015083 · NCI · MAYO CLINIC ROCHESTER · PI AKHILESH PANDEY · 1985 to 2026
$151.3M
Mayo Clinic Center for Clinical and Translational Science (CCaTS UL1 Supplement - Dr. Timothy Curry)UL1TR002377 · NCATS · MAYO CLINIC ROCHESTER · PI VESNA D GAROVIC · 2017 to 2026
$78.4M
The Role of CHFR in Tumorigenesis and Paclitaxel-Sensitivity in Breast CancerP50CA116201 · NCI · MAYO CLINIC ROCHESTER · PI Fergus Joseph Couch · 2005 to 2026
$49.9M
Predicting Breast Cancer Risk after Benign Percutaneous BiopsyR01CA229811 · NCI · MAYO CLINIC JACKSONVILLE · PI DEGNIM, AMY C, SHERMAN, MARK E · 2018 to 2022
$3.5M
Involution-based biomarkers of breast cancer riskR01CA237602 · NCI · MAYO CLINIC JACKSONVILLE · PI DEGNIM, AMY C, RADISKY, DEREK C · 2020 to 2024
$2.8M
NCATS NIH HHS UL1 TR002377NCATS NIH HHS UL1TR002377NCI NIH HHS P30 CA015083NCI NIH HHS P50 CA116201NCI NIH HHS R01 CA229811NCI NIH HHS R01 CA237602
6 · The paper itself

Abstract

purposeTo characterize associations of microcalcifications (calcs) with benign breast disease lesion subtypes and assess whether tissue calcs affect risks of ductal carcinoma in situ (DCIS) and invasive breast cancer (IBC).

methodsWe analyzed detailed histopathologic data for 4,819 BBD biopsies from a single institution cohort (2002-2013) followed for DCIS or IBC for a median of 7.4 years for cases (N = 338) and 11.2 years for controls. Natural language processing was used to identify biopsies containing calcs based on pathology reports. Univariable and multivariable regression models were applied to assess associations with BBD lesion type and age-adjusted Cox proportional hazard regressions were performed to model risk of IBC or DCIS stratified by the presence or absence of calcs.

resultsCalcs were identified in 2063 (42.8%) biopsies. Calcs were associated with older age at BBD diagnosis (56.2 versus 49.0 years; P < 0.001). Overall, the risk of developing IBC or DCIS did not differ significantly between patients with calcs (HR 1.13, 95% CI 0.90, 1.41) as compared to patients without calcs. Stratification by BBD severity or subtype, age at BBD biopsy, outcomes of IBC versus DCIS, and mammography technique (screen-film versus full-field digital mammography) did not significantly alter association between calcs and risk.

conclusionOur analysis of calcs in BBD biopsies did not find a significant association between calcs and risk of breast cancer.

Indexed as

Breast NeoplasmsCalcinosisCarcinoma, Intraductal, NoninfiltratingAdultAgedBiopsyBreastBreast DiseasesFemaleHumansMiddle AgedProportional Hazards ModelsRisk FactorsBreast cancer riskHistopathologyMicrocalcificationsNatural language processing

Identifiers

PMID39230626
PMCPMC11574978

What OpenQuestion holds

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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.