Trial reportAJR. American journal of roentgenology2012
Is confidence of mammographic assessment a good predictor of accuracy?
Trial report in AJR. American journal of roentgenology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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.
Who cites it
6 citing papers in PubMed, 16 citations in OpenAlex.
- MRI of early rectal cancer; bisacodyl micro-enema increases submucosal width, reader confidence, and tumor conspicuity.Abdominal radiology (New York) · 2025Article
- Breast cancer detection across dense and non-dense breasts: Markers of diagnostic confidence and efficacy.Acta radiologica open · 2022Article
- Characteristics and diagnostic performance of pathologists who enjoy interpreting melanocytic lesions.Dermatology online journal · 2018Article
- Comparison of digital mammography and digital breast tomosynthesis in the detection of architectural distortion.European radiology · 2018Article
- Demographic and practice characteristics of pathologists who enjoy breast tissue interpretation.Breast (Edinburgh, Scotland) · 2015Article
- Collective intelligence meets medical decision-making: the collective outperforms the best radiologist.PloS one · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 5 institutions in 1 country.
Funding
Abstract
objectiveInterpretive accuracy varies among radiologists, especially in mammography. This study examines the relationship between radiologists' confidence in their assessments and their accuracy in interpreting mammograms. MATERIALS AND
methodsIn this study, 119 community radiologists interpreted 109 expert-defined screening mammography examinations in test sets and rated their confidence in their assessment for each case. They also provided a global assessment of their ability to interpret mammograms. Positive predictive value (PPV) and negative predictive value (NPV) were modeled as functions of self-rated confidence on each examination using log-linear regression estimated with generalized estimating equations. Reference measures were cancer status and expert-defined need for recall. Effect modification by weekly mammography volume was examined.
resultsRadiologists who self-reported higher global interpretive ability tended to interpret more mammograms per week (p = 0.08), were more likely to specialize (p = 0.02) and to have completed a fellowship in breast or women's imaging (p = 0.05), and had a higher PPV for cancer detection (p = 0.01). Examinations for which low-volume radiologists were "very confident" had a PPV of 2.93 times (95% CI, 2.01-4.27) higher than examinations they rated with neutral confidence. Trends of increasing NPVs with increasing confidence were significant for low-volume radiologists relative to noncancers (p = 0.01) and expert nonrecalls (p < 0.001). A trend of significantly increasing NPVs existed for high-volume radiologists relative to expert nonrecall (p = 0.02) but not relative to noncancer status (p = 0.32).
conclusionConfidence in mammography assessments was associated with better accuracy, especially for low-volume readers. Asking for a second opinion when confidence in an assessment is low may increase accuracy.
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What OpenQuestion holds
Registered trials
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.