Evidence map›Paper›PMID 37897646›Full record

ArticleBreast cancer research and treatment2024

Screening mammographic performance by race and age in the National Mammography Database: 29,479,665 screening mammograms from 13,181,241 women.

Cindy S Lee, Lenka Goldman, Lars J Grimm, Ivy Xinyue Liu, Michael Simanowith, Robert Rosenberg, Margarita Zuley, Linda Moy

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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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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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

3 citing papers in PubMed.

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4 · The record

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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

8 authors.

Cindy S LeeDepartment of Radiology, New York University Langone Health, New York, USA. Cindy.Lee3@stonybrookmedicine.edu.ORCID http://orcid.org/0000-0002-1893-961X
Lenka GoldmanAmerican College of Radiology, 1891 Preston Drive, Reston, VA, USA.
Lars J GrimmDepartment of Radiology, Duke University, Durham, NC, USA.
Ivy Xinyue LiuAmerican College of Radiology, 1891 Preston Drive, Reston, VA, USA.
Michael SimanowithAmerican College of Radiology, 1891 Preston Drive, Reston, VA, USA.
Robert RosenbergRadiology Associates of Albuquerque, Albuquerque, NM, USA.
Margarita ZuleyUniversity of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Linda MoyDepartment of Radiology, New York University Langone Health, New York, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThere are insufficient large-scale studies comparing the performance of screening mammography in women of different races. This study aims to compare the screening performance metrics across racial and age groups in the National Mammography Database (NMD).

methodsAll screening mammograms performed between January 1, 2008, and December 31, 2021, in women aged 30-100 years from 746 mammography facilities in 46 U.S. states in the NMD were included. Patients were stratified by 10-year age intervals and 5 racial groups (African American, American Indian, Asian, White, unknown). Incidence of risk factors (breast density, personal history, family history of breast cancer, age), and time since prior exams were compared. Five screening mammography metrics were calculated: recall rate (RR), cancer detection rate (CDR), positive predictive values for recalls (PPV

results29,479,655 screening mammograms performed in 13,181,241 women between January 1, 2008, and December 31, 2021, from the NMD were analyzed. The overall mean performance metrics were RR 10.00% (95% CI 9.99-10.02), CDR 4.18/1000 (4.16-4.21), PPV

conclusionsBenefits of screening mammography increase with age, including for women age > 70 and across all races. Screening mammography is effective; with lower RR and higher CDR, PPV

Indexed as

Breast NeoplasmsMammographyBiopsyEarly Detection of CancerFemaleHumansMass ScreeningPredictive Value of TestsAgeBreast cancerMammographyMetricsRaceScreening performance

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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.