Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2018 Jul;288(1):47-54.
doi: 10.1148/radiol.2018171539. Epub 2018 Apr 3.

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

Elizabeth S Burnside  1 , Daniel Vulkan  1 , Roger G Blanks  1 , Stephen W Duffy  1
Affiliations

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

Elizabeth S Burnside et al. Radiology. 2018 Jul.

Abstract

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.

PubMed Disclaimer

Figures

Figure 1a:
Figure 1a:
Plots demonstrate association between recall to assessment rate and (a) interval cancer rate and (b) screening cancer detection rate. Points represent a year of screening mammograms in one of the 84 breast screening units. Line represents Poisson regression line.
Figure 1b:
Figure 1b:
Plots demonstrate association between recall to assessment rate and (a) interval cancer rate and (b) screening cancer detection rate. Points represent a year of screening mammograms in one of the 84 breast screening units. Line represents Poisson regression line.
Figure 2a:
Figure 2a:
Plots illustrate statistically significant association between recall to assessment rate and interval cancer rate for age-based subgroup analysis of women aged (a) 50–54 years, (b) 60–64 years, and (c) 65–69 years. Points represent a year of screening mammograms in one of the 84 breast screening units. Line represents Poisson regression line. Trade-off between an interval cancer and a recall is noted on each graph.
Figure 2b:
Figure 2b:
Plots illustrate statistically significant association between recall to assessment rate and interval cancer rate for age-based subgroup analysis of women aged (a) 50–54 years, (b) 60–64 years, and (c) 65–69 years. Points represent a year of screening mammograms in one of the 84 breast screening units. Line represents Poisson regression line. Trade-off between an interval cancer and a recall is noted on each graph.
Figure 2c:
Figure 2c:
Plots illustrate statistically significant association between recall to assessment rate and interval cancer rate for age-based subgroup analysis of women aged (a) 50–54 years, (b) 60–64 years, and (c) 65–69 years. Points represent a year of screening mammograms in one of the 84 breast screening units. Line represents Poisson regression line. Trade-off between an interval cancer and a recall is noted on each graph.
Figure 3a:
Figure 3a:
Plots illustrate statistically significant association between recall to assessment rate and interval cancer rate for (a) incident and (b) prevalent subgroup analysis. Points represent a year of screening mammograms in one of the 84 breast screening units. Line represents Poisson regression line. Trade-off between an interval cancer and a recall is noted on each graph.
Figure 3b:
Figure 3b:
Plots illustrate statistically significant association between recall to assessment rate and interval cancer rate for (a) incident and (b) prevalent subgroup analysis. Points represent a year of screening mammograms in one of the 84 breast screening units. Line represents Poisson regression line. Trade-off between an interval cancer and a recall is noted on each graph.
Figure 4:
Figure 4:
Bar graph shows number of interval cancers according to number of months since negative screening mammogram.
See this image and copyright information in PMC

References

    1. Bennett RL, Blanks RG. Should a standard be defined for the positive predictive value (PPV) of recall in the UK NHS Breast Screening Programme? Breast 2007;16(1):55–59. - PubMed
    1. Blanks RG, Moss SM, Wallis MG. Monitoring and evaluating the UK National Health Service Breast Screening Programme: evaluating the variation in radiological performance between individual programmes using PPV-referral diagrams. J Med Screen 2001;8(1):24–28. - PubMed
    1. Miglioretti DL, Ichikawa L, Smith RA, et al. Criteria for identifying radiologists with acceptable screening mammography interpretive performance on basis of multiple performance measures. AJR Am J Roentgenol 2015;204(4):W486–W491. - PMC - PubMed
    1. Yankaskas BC, Klabunde CN, Ancelle-Park R, et al. International comparison of performance measures for screening mammography: can it be done? J Med Screen 2004;11(4):187–193. - PubMed
    1. Grabler P, Sighoko D, Wang L, Allgood K, Ansell D. Recall and cancer detection rates for screening mammography: finding the sweet spot. AJR Am J Roentgenol 2017;208(1):208–213. - PubMed

Publication types

LinkOut - more resources