Understanding recall rates in screening mammography: A conceptual framework review of the literature

Norsuddin, Norhashimah Mohd; Reed, Warren; Mello‐Thoms, Claudia; Lewis, Sarah

doi:10.1016/j.radi.2015.06.003

Cited by 2 publications

(3 citation statements)

References 71 publications

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“…International comparisons including and beyond the United States and the United Kingdom (4,10,33) demonstrate wide variability in RAR between programs, which is unlikely only due to patient population and program differences but also involves the health policy setting (11,12), medical-legal environment (ie, the importance of finding every cancer), and the tolerance of false-positive findings (32,33). Importantly, our methods for determining the trade-offs of RAR levels in terms of ICR transcends these factors and enables any program to determine the trade-offs.…”

Section: Discussionmentioning

confidence: 99%

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Association between Screening Mammography Recall Rate and Interval Cancers in the UK Breast Cancer Service Screening Program: A Cohort Study

et al. 2018

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Purpose To determine whether low levels of recall lead to increased interval cancers and the magnitude of this effect. Materials and Methods The authors retrospectively analyzed prospectively collected data from the UK National Health Service Breast Screening Programme during a 36-month period (April 1, 2005 to March 31, 2008), with 3-year follow-up in women aged 50-70 years. Data on recall, cancers detected at screening, and interval cancers were available for each of the 84 breast screening units and for each year (n = 252). The association between interval cancers and recalls was modeled by using Poisson regression on aggregated data and according to age (5-year intervals) and screening type (prevalent vs incident). Results The authors analyzed 5 126 689 screening episodes, demonstrating an average recall to assessment rate (RAR) of 4.56% (range, 1.64%-8.42%; standard deviation, 1.15%), cancer detection rate of 8.1 per 1000 women screened, and interval cancer rate (ICR) of 3.1 per 1000 women screened. Overall, a significant negative association was found between RAR and ICR (Poisson regression coefficient: -0.039 [95% confidence interval: -0.062, -0.017]; P = .001), with approximately one fewer interval cancer for every additional 80-84 recalls. Subgroup analysis revealed similar negative correlations in women aged 50-54 years (P = .002), 60-64 years (P = .01), and 65-69 years (P = .008) as well as in incident screens (P = .001) and prevalent screens (P = .04). No significant relationship was found in women aged 55-59 years (P = .46). Conclusion There was a statistically significant negative correlation between RAR and ICR, which suggests the merit of a minimum threshold for RAR. RSNA, 2018 Online supplemental material is available for this article.

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Section: Discussionmentioning

confidence: 99%

“…The RAR depends on many factors (12), such as prevalent versus incident screening round (2), patient population characteristics (13)(14)(15), and screening program factors (4,12,(16)(17)(18). The literature illustrates that two-view mammography led to simultaneous increases in RAR and CDR (17,18) and decreases in ICR (19,20).…”

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confidence: 99%

Association between Screening Mammography Recall Rate and Interval Cancers in the UK Breast Cancer Service Screening Program: A Cohort Study

et al. 2018

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“…(see Figures 6 and 7 and Table 3). Recall Rate (i.e., the percentage of mammograms that were reported to have abnormal findings) and PPV (i.e., the percentage of women recalled for further tests who have cancer) are important clinical metrics within breast cancer screening (e.g., Norsuddin et al, 2015;Rauscher et al, 2021;Taylor-Phillips et al, 2024) and were calculated as follows, in which TP stands for True Positive, FP stands for False Positive (false alarms), TN stands for True Negative and FN stands for False Negative:…”

Section: Miss Errorsmentioning

confidence: 99%

The Message Matters: Changes to Binary Computer Aided Detection Recommendations Affect Cancer Detection in Low Prevalence Search

Patterson,

Kunar

2024

Preprint

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Computer Aided Detection (CAD) has been used to help readers find cancers in mammograms. Although these automated systems have been shown to help cancer detection when accurate, the presence of CAD also leads to an over-reliance effect where miss errors and false alarms increase when the CAD system fails. Previous research investigated CAD systems which overlayed salient exogenous cues onto the image to highlight suspicious areas. These salient cues capture attention which may exacerbate the over-reliance effect. Furthermore, overlaying CAD cues directly on the mammogram occludes sections of breast tissue which may disrupt global statistics useful for cancer detection. In this study we investigated whether an over-reliance effect occurred with a binary CAD system, which instead of overlaying a CAD cue onto the mammogram, reported a message alongside the mammogram indicating the possible presence of a cancer. We manipulated the certainty of the message and whether it was presented only to indicate the presence of a cancer, or whether a message was displayed on every mammogram to state whether a cancer was present or absent. The results showed that although an over-reliance effect still occurred with binary CAD systems miss errors were reduced when the CAD message was more definitive and only presented to alert readers of a possible cancer.

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Understanding recall rates in screening mammography: A conceptual framework review of the literature

Cited by 2 publications

References 71 publications

Association between Screening Mammography Recall Rate and Interval Cancers in the UK Breast Cancer Service Screening Program: A Cohort Study

Association between Screening Mammography Recall Rate and Interval Cancers in the UK Breast Cancer Service Screening Program: A Cohort Study

The Message Matters: Changes to Binary Computer Aided Detection Recommendations Affect Cancer Detection in Low Prevalence Search

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