Evidence map›Paper›PMID 28621548›Full record

ArticleThe British journal of radiology2017

An investigation into the mammographic appearances of missed breast cancers when recall rates are reduced.

Norhashimah Mohd Norsuddin, Claudia Mello-Thoms, Warren Reed, Mary Rickard, Sarah Lewis

Abstract read
In one paragraph

Article in The British journal of radiology, 2017. 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

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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

5 authors.

Norhashimah Mohd Norsuddin1 Medical Image Optimisation and Perception Group (MIOPeG), Discipline of Medical Radiation Sciences, Faculty of Health Sciences, University of Sydney, Sydney, NSW, Australia.
Claudia Mello-Thoms1 Medical Image Optimisation and Perception Group (MIOPeG), Discipline of Medical Radiation Sciences, Faculty of Health Sciences, University of Sydney, Sydney, NSW, Australia.
Warren Reed1 Medical Image Optimisation and Perception Group (MIOPeG), Discipline of Medical Radiation Sciences, Faculty of Health Sciences, University of Sydney, Sydney, NSW, Australia.
Mary Rickard3 Sydney Breast Clinic, Sydney, NSW, Australia.
Sarah Lewis1 Medical Image Optimisation and Perception Group (MIOPeG), Discipline of Medical Radiation Sciences, Faculty of Health Sciences, University of Sydney, Sydney, NSW, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study investigated whether certain mammographic appearances of breast cancer are missed when radiologists read at lower recall rates.

methods5 radiologists read 1 identical test set of 200 mammographic (180 normal cases and 20 abnormal cases) 3 times and were requested to adhere to 3 different recall rate conditions: free recall, 15% and 10%. The radiologists were asked to mark the locations of suspicious lesions and provide a confidence rating for each decision. An independent expert radiologist identified the various types of cancers in the test set, including the presence of calcifications and the lesion location, including specific mammographic density.

resultsRadiologists demonstrated lower sensitivity and receiver operating characteristic area under the curve for non-specific density/asymmetric density (H = 6.27, p = 0.04 and H = 7.35, p = 0.03, respectively) and mixed features (H = 9.97, p = 0.01 and H = 6.50, p = 0.04, respectively) when reading at 15% and 10% recall rates. No significant change was observed on cancer characterized with stellate masses (H = 3.43, p = 0.18 and H = 1.23, p = 0.54, respectively) and architectural distortion (H = 0.00, p = 1.00 and H = 2.00, p = 0.37, respectively). Across all recall conditions, stellate masses were likely to be recalled (90.0%), whereas non-specific densities were likely to be missed (45.6%).

conclusionCancers with a stellate mass were more easily detected and were more likely to continue to be recalled, even at lower recall rates. Cancers with non-specific density and mixed features were most likely to be missed at reduced recall rates. Advances in knowledge: Internationally, recall rates vary within screening mammography programs considerably, with a range between 1% and 15%, and very little is known about the type of breast cancer appearances found when radiologists interpret screening mammograms at these various recall rates. Therefore, understanding the lesion types and the mammographic appearances of breast cancers that are affected by readers' recall decisions should be investigated.

Indexed as

MammographyBreastBreast NeoplasmsDiagnostic ErrorsFemaleHumansReferral and ConsultationReproducibility of ResultsSensitivity and Specificity

Identifiers

PMID28621548
PMCPMC5603949

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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.