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.
Background: The vigilance decrement and prevalence effect both describe changes to speed and accuracy with time on task. Whilst there is much laboratory based research on these effects, little is known about whether they occur in real world mammography practice. Methods: The Changing Case Order to Optimise Patterns of Performance in Screening (CO-OPS) trial randomised 37,724 batches containing 1.2 million women attending breast screening to intervention or control (222,208 from the Midlands of England). In the control arm the batch was examined in the same order by both readers, in the intervention arm it was examined in a different order by both readers. Time taken, recall decision by both readers, and cancers detected were recorded for each case, and used to examine patterns of performance with time on task. Results: 49,575 women were recalled and 10,484 had cancer detected. Median time taken to examine each case was 35 seconds (out of cases where time taken was 10 minutes or less). The intervention did not affect overall cancer detection rates or recall rates. A more detailed analysis of the Midlands data indicates cancer detection rate did not change when reading up to 60 cases in a batch, but recall rate reduced. Time taken per case reduced with time on task, from a median 41 seconds when examining the second case in the batch to 28.5 seconds examining the 60th case. Conclusion: Reader behavior and performance systematically changes with time on task in breast screening.
KEYWORDS: Cancer, Mammography, Breast cancer, Breast, Radiology, Image analysis, Medical imaging, Image compression, Current controlled current source, Visualization
Background: The interpretation of screening mammograms is influenced by factors such as reader experience and their annual interpretative volume. There is some evidence that time of day can also have an effect, with better diagnostic accuracy for readings conducted early in the day. This is not a consistent finding, however. The aim of our study is to provide further evidence on whether there is an effect of time of day on recall- and breast cancer detection rates. Method: We analysed breast screening data from 222,577 women from the Midlands of England. Data were split into three eight hour periods: 0900-1700, 1700-0100, 0100-0900. Differences in recall- and cancer detection rates were analysed using multilevel logistic regression models. Results: Recall rates were lowest for mammograms read between the 1700-0100 time period. Cancer detection rates were lowest during the 0100-0900 time period. Conclusions: Our findings suggest that there are fluctuations in recall- and cancer detection rates over the course of the day.
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