An analysis of 11.3 million screening tests examining the association between recall and cancer detection rates in the English NHS breast cancer screening programme

Development and quality appraisal of a new English breast screening linked data set as part of the age, test threshold, and frequency of mammography screening (ATHENA-M) study

OBJECTIVES

To build a data set capturing the whole breast cancer screening journey from individual breast cancer screening records to outcomes and assess data quality.

METHODS

Routine screening records (invitation, attendance, test results) from all 79 English NHS breast screening centres between January 1, 1988 and March 31, 2018 were linked to cancer registry (cancer characteristics and treatment) and national mortality data. Data quality was assessed using comparability, validity, timeliness, and completeness.

RESULTS

Screening records were extracted from 76/79 English breast screening centres, 3/79 were not possible due to software issues. Data linkage was successful from 1997 after introduction of a universal identifier for women (NHS number). Prior to 1997 outcome data are incomplete due to linkage issues, reducing validity. Between January 1, 1997 and March 31, 2018, a total of 11 262 730 women were offered screening of whom 9 371 973 attended at least one appointment, with 139 million person-years of follow-up (a median of 12.4 person years for each woman included) with 73 810 breast cancer deaths and 1 111 139 any-cause deaths. Comparability to reference data sets and internal validity were demonstrated. Data completeness was high for core screening variables (>99%) and main cancer outcomes (>95%).

CONCLUSIONS

The ATHENA-M project has created a large high-quality and representative data set of individual women's screening trajectories and outcomes in England from 1997 to 2018, data before 1997 are lower quality.

ADVANCES IN KNOWLEDGE

This is the most complete data set of English breast screening records and outcomes constructed to date, which can be used to evaluate and optimize screening.

Radiological review of prior screening mammograms of screen-detected breast cancer

OBJECTIVE

To perform a radiological review of mammograms from prior screening and diagnosis of screen-detected breast cancer in BreastScreen Norway, a population-based screening program.

METHODS

We performed a consensus-based informed review of mammograms from prior screening and diagnosis for screen-detected breast cancers. Mammographic density and findings on screening and diagnostic mammograms were classified according to the Breast Imaging-Reporting and Data System®. Cases were classified based on visible findings on prior screening mammograms as true (no findings), missed (obvious findings), minimal signs (minor/non-specific findings), or occult (no findings at diagnosis). Histopathologic tumor characteristics were extracted from the Cancer Registry of Norway. The Bonferroni correction was used to adjust for multiple testing; p < 0.001 was considered statistically significant.

RESULTS

The study included mammograms for 1225 women with screen-detected breast cancer. Mean age was 62 years ± 5 (SD); 46% (567/1225) were classified as true, 22% (266/1225) as missed, and 32% (392/1225) as minimal signs. No difference in mammographic density was observed between the classification categories. At diagnosis, 59% (336/567) of true and 70% (185/266) of missed cancers were classified as masses (p = 0.004). The percentage of histological grade 3 cancers was higher for true (30% (138/469)) than for missed (14% (33/234)) cancers (p < 0.001). Estrogen receptor positivity was observed in 86% (387/469) of true and 95% (215/234) of missed (p < 0.001) cancers.

CONCLUSIONS

We classified 22% of the screen-detected cancers as missed based on a review of prior screening mammograms with diagnostic images available. One main goal of the study was quality improvement of radiologists' performance and the program. Visible findings on prior screening mammograms were not necessarily indicative of screening failure.

KEY POINTS

• After a consensus-based informed review, 46% of screen-detected breast cancers were classified as true, 22% as missed, and 32% as minimal signs. • Less favorable prognostic and predictive tumor characteristics were observed in true screen-detected breast cancer compared with missed. • The most frequent mammographic finding for all classification categories at the time of diagnosis was mass, while the most frequent mammographic finding on prior screening mammograms was a mass for missed cancers and asymmetry for minimal signs.

Optimum screening mammography reading volumes: evidence from the NHS Breast Screening Programme

OBJECTIVES

Minimum caseload standards for professionals examining breast screening mammograms vary from 480 (US) to 5000 (Europe). We measured the relationship between the number of women's mammograms examined per year and reader performance.

METHODS

We extracted routine records from the English NHS Breast Screening Programme for readers examining between 1000 and 45,000 mammograms between April 2014 and March 2017. We measured the relationship between the volume of cases read and screening performance (cancer detection rate, recall rate, positive predictive value of recall (PPV) and discrepant cancers) using linear logistic regression. We also examined the effect of reader occupational group on performance.

RESULTS

In total, 759 eligible mammography readers (445 consultant radiologists, 235 radiography advanced practitioners, 79 consultant radiographers) examined 6.1 million women's mammograms during the study period. PPV increased from 12.9 to 14.4 to 17.0% for readers examining 2000, 5000 and 10000 cases per year respectively. This was driven by decreases in recall rates from 5.8 to 5.3 to 4.5 with increasing volume read, and no change in cancer detection rate (from 7.6 to 7.6 to 7.7). There was no difference in cancer detection rate with reader occupational group. Consultant radiographers had higher recall rate and lower PPV compared to radiologists (OR 1.105, p = 0.012; OR 0.874, p = 0.002, unadjusted).

CONCLUSION

Positive predictive value of screening increases with the total volume of cases examined per reader, through decreases in numbers of cases recalled with no concurrent change in numbers of cancers detected.

KEY POINTS

• In the English Breast Screening Programme, readers who examined a larger number of cases per year had a higher positive predictive value, because they recalled fewer women for further tests but detected the same number of cancers. • Reader type did not affect cancer detection rate, but consultant radiographers had a higher recall rate and lower positive predictive value than consultant radiologists, although this was not adjusted for length of experience.

The "Sweet Spot" Revisited: Optimal Recall Rates for Cancer Detection With 2D and 3D Digital Screening Mammography in the Metro Chicago Breast Cancer Registry

OBJECTIVE. One central question pertaining to mammography quality relates to discerning the optimal recall rate to maximize cancer detection while minimizing unnecessary downstream diagnostic imaging and breast biopsies. We examined the trade-offs for higher recall rates in terms of biopsy recommendations and cancer detection in a single large health care organization. MATERIALS AND METHODS. We included 2D analog, 2D digital, and 3D digital (tomosynthesis) screening mammography examinations among women 40-79 years old performed between January 1, 2005, and December 31, 2017, with cancer follow-up through 2018. There were 36, 67, and 38 radiologists who read at least 1000 2D analog examinations, 2D digital examinations, and 3D tomosynthesis examinations, respectively, who were included in these analyses. Using logistic regression with marginal standardization, we estimated radiologist-specific mean recall (abnormal interpretations/1000 mammograms), biopsy recommendation, cancer detection (screening-detected in situ and invasive cancers/1000 mammograms), and minimally invasive cancer detection rates while adjusting for differences in patient characteristics. RESULTS. Among 1,060,655 screening mammograms, the mean recall rate was 10.7%, the cancer detection rate was 4.0/1000 mammograms, and the biopsy recommendation rate was 1.60%. Recall rates between 7% and 9% appeared to maximize cancer detection while minimizing unnecessary biopsies. CONCLUSION. The results of this investigation are in contrast to those of a recent study suggesting appropriateness of higher recall rates. The "sweet spot" for optimal cancer detection appears to be in the recall rate range of 7-9% for both 2D digital mammography and 3D tomosynthesis. Too many women are being called back for diagnostic imaging, and new benchmarks could be set to reduce this burden.

The Revised Champion's Health Belief Model Scale: Predictive Validity Among Brazilian Women

Mammography screening is provided free of charge for the recommended target population in Brazil but participation rates have remained low, and breast cancer mortality has continued to increase. Thus, it is important to identify factors that are associated with poor participation in mammography screening so that service providers can target health promotion messages and screening programs more effectively. Objective: To evaluate the predictive validity of the Revised Champion’s Health Belief Model scale (RCHBMS) for identifying women at high risk of not adhering to national guidelines for mammography screening in Brazil. Methods: We used a longitudinal survey design with a 1-year follow-up data from 194 women living in northeastern Brazil, in the city of Fortaleza, Ceará, participants completed the RCHBMS at baseline, and mammography uptake was measured 1 year later. Hierarchical logistic regression was used to determine the predictive validity of the RCHBMS for identifying women who had not adhered to recommendations for mammography screening, after accounting for the women’s sociodemographic and clinical characteristics. The sensitivity and specificity of various cut-off points were calculated to determine the optimal cut-off point for identifying women at high risk of not adhering to mammography screening guidelines. Results: Two subscales of the RCHBMS uniquely predicted nonadherence: susceptibility and barriers, along with race and family history of cancer. The total scale score (with barriers reverse coded) was also highly predictive. For our sample, using only the RCHBMS with a cutoff of ≤ 3.67 (out of a total possible range of 1–5) yielded a high sensitivity and specificity for predicting nonadherence. Conclusion: Study findings support the validity and clinical utility of the RCHBM for identifying women at risk of not adhering to national guidelines for mammography screening in Brazil.

Association between radiologists' and facilities' characteristics and mammography screening detection of ductal carcinoma in situ

PURPOSE

The aim of our study was, first, to measure association between radiologists and facilities characteristics and DCIS detection. Second, to assess whether those characteristics affect differently the likelihood of detection of DCIS versus invasive breast cancer. When applicable, we examined whether the identified characteristics were similarly associated with low-grade and high-grade DCIS detection.

METHODS

This retrospective cohort study included 1,750,002 digital screening mammograms (2145 screen-detected DCIS) performed in the Quebec breast cancer screening program between 2007 and 2015 inclusively. The associations between radiologists' and facilities' characteristics and (1) the DCIS detection rate, (2) the invasive detection rate, and (3) the odds of DCIS on invasive detection were assess. For statistically significant associations in the latter analysis, analyses stratified by DCIS grade were performed. Multivariable logistic regression with generalized estimating equations estimates to account for correlation among mammograms was used.

RESULTS

Compared to radiologists with recall rate between 5.0 and 9.9%, radiologists with recall rate between 15.0-19.9% and ≥ 20% reached a higher DCIS detection rate, with adjusted detection ratios of, respectively, 1.33 (95% confidence interval = 1.15-1.53) and 1.43 (95% confidence interval = 1.13-1.81). Increase in radiologist' recall rate was statistically significantly associated with an increase in detection of low/intermediate-grade DCIS (P < 0.001), while not in high-grade DCIS (P = 0.15).

CONCLUSIONS

A major determinant of DCIS detection is the radiologists' recall rate. Abnormalities referred by radiologists with higher recall rates should be identified in order to understand how to decrease recall rate while keeping an optimal DCIS and invasive detection rate.

An analysis of screen-detected invasive cancers by grade in the English breast cancer screening programme: are we failing to detect sufficient small grade 3 cancers?

OBJECTIVE

Randomised controlled trials have shown a reduction in breast cancer mortality from mammography screening and it is the detection of high-grade invasive cancers that is responsible for much of this effect. We determined the detection rates of invasive cancers by grade, size and type of screen and estimated relative sensitivities with emphasis on grade 3 detection.

METHODS

This observational study analysed data from over 11 million screening episodes (67,681 invasive cancers) from the English NHS breast screening programme over seven screening years 2009/2010 to 2015/2016 for women aged 45-70.

RESULTS

At prevalent (first) screens (which are unaffected by screening interval), the detection rate of small (< 15 mm) invasive cancers was 0.95 per 1000 for grade 1, but for grade 3 only 0.30 per 1000. The ratio of small (< 15 mm) to large (≥ 15 mm) cancers was 1.8:1 for grade 1 but reversed to 0.5:1 for grade 3. We estimated that the relative sensitivity for grade 3 invasive cancers was 52% of that for grade 1 and the relative sensitivity for small (< 15 mm) grade 3 only 26% of that for small (< 15 mm) grade 1 invasive cancers.

CONCLUSIONS

Sensitivity for small grade 3 invasive cancers is poor compared with that for grade 1 and 2 invasive cancers and larger grade 3 malignancies. This observation is likely a limitation of the current technology related to the absence of identifiable mammographic features for small high-grade cancers. Future work should focus on technologies and strategies to improve detection of these clinically most significant cancers.

KEY POINTS

• The detection of small high-grade invasive cancers is vital to reduce breast cancer mortality. • We estimate the sensitivity for small grade 3 invasive cancers may be only 26% of that of small grade 1 invasive cancers. This is likely to be associated with the non-specific mammographic features for these cancers. • New technologies and appropriate strategies using current technology are required to maximise the detection of small grade 3 invasive cancers.