Presentation + Paper
4 March 2019 Blinding of the second reader in mammography screening: impact on behaviour and cancer detection
Author Affiliations +
Abstract
Background: The policy of the NHS Breast Cancer Screening Programme is for each woman’s mammograms to be examined by two separate readers, working independently. In practice, sometimes the second reader (reader 2) can see the decision of the first reader (reader 1). The National Breast Screening Service (NBSS) computer software automatically records whether the second reader can see the decision of the first reader or whether they are ‘blinded’. This study aimed to determine the effect of blinding the second reader on the recall rate and cancer detection rate of reader 2. Methods: Data were from eight screening centers based in the Midlands area in England participating in the 'Changing Case Order to Optimize Patterns of Performance in Screening (CO-OPS)' clinical trial. A three-level Markov Chain Monte Carlo multilevel model was fitted to determine the effect of blinding reader 2 on recall rate and cancer detection. Results: 207,595 women were included in the analysis, of whom 1,796 had cancer detected. Reader 2 was blinded to reader 1’s decisions for 54.5% (113,029/207,595) cases. If reader 2 is blinded, there is a high probability that they are more likely to recall than if they were not blinded for a prevalent case but less likely to recall an incident case. The interaction effects on reader 2’s cancer detection rate were not significant. Conclusion: If the second reader is not blinded to the decision of the first reader, they appear to be influenced by the first reader’s decision suggesting that reading is not independent.
Conference Presentation
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jennifer Anne Cooper, David Jenkinson, and Sian Taylor-Phillips "Blinding of the second reader in mammography screening: impact on behaviour and cancer detection", Proc. SPIE 10952, Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment, 109520T (4 March 2019); https://doi.org/10.1117/12.2512090
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KEYWORDS
Cancer

Mammography

Breast

Breast cancer

Data modeling

Statistical analysis

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