Evidence map›Paper›PMID 20300960›Full record

ReviewBreast cancer research and treatment2010

Predictors of interobserver agreement in breast imaging using the Breast Imaging Reporting and Data System.

Anna Liza M Antonio, Catherine M Crespi

Abstract readReview
In one paragraph

Review in Breast cancer research and treatment, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Measuring intrarater association between correlated ordinal ratings.Biometrical journal. Biometrische Zeitschrift · 2020
    Article
  5. Article
  6. Article
  7. Article
  8. Radiologist agreement for mammographic recall by case difficulty and finding type.Journal of the American College of Radiology : JACR · 2012
    Article
  9. 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

2 authors.

Anna Liza M AntonioDepartment of Biostatistics, UCLA School of Public Health, University of California, Los Angeles, CA, 90095-1776, USA. aantonio@ucla.edu
Catherine M Crespi

Funding

Women's CancersP30CA016042 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Melissa Fitzmaurice Neligan · 1985 to 2026
$134.5M
NCI NIH HHS CA 16042NCI NIH HHS P30 CA016042
6 · The paper itself

Abstract

The Breast Imaging Reporting and Data System (BI-RADS) was introduced in 1993 to standardize the interpretation of mammograms. Though many studies have assessed the validity of the system, fewer have examined its reliability. Our objective is to identify predictors of reliability as measured by the kappa statistic. We identified studies conducted between 1993 and 2009 which reported kappa values for interpreting mammograms using any edition of BI-RADS. Bivariate and multivariate multilevel analyses were used to examine associations between potential predictors and kappa values. We identified ten eligible studies, which yielded 88 kappa values for the analysis. Potential predictors of kappa included: whether or not the study included negative cases, whether single- or two-view mammograms were used, whether or not mammograms were digital versus screen-film, whether or not the fourth edition of BI-RADS was utilized, the BI-RADS category being evaluated, whether or not readers were trained, whether or not there was an overlap in readers' professional activities, the number of cases in the study and the country in which the study was conducted. Our best multivariate model identified training, use of two-view mammograms and BI-RADS categories (masses, calcifications, and final assessments) as predictors of kappa. Training, use of two-view mammograms and focusing on mass description may be useful in increasing reliability in mammogram interpretation. Calcification and final assessment descriptors are areas for potential improvement. These findings are important for implementing policies in BI-RADS use before introducing the system in different settings and improving current implementations.

Indexed as

MammographyObserver VariationFemaleHumansMultivariate AnalysisRadiographic Image Interpretation, Computer-AssistedReproducibility of Results

Identifiers

PMID20300960
PMCPMC2843585

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.