Change in mammographic density across birth cohorts of Dutch breast cancer screening participants

Cumulative risks of false positive recall and screen-detected breast cancer after multiple screening examinations

Women tend to make a decision about participation in breast cancer screening and adhere to this for future invitations. Therefore, our study aimed to provide high-quality information on cumulative risks of false-positive (FP) recall and screen-detected breast cancer over multiple screening examinations. Individual Dutch screening registry data (2005-2018) were gathered on subsequent screening examinations of 92 902 women age 49 to 51 years in 2005. Survival analyses were used to calculate cumulative risks of a FP and a true-positive (TP) result after seven examinations. Data from 66 472 women age 58 to 59 years were used to extrapolate to 11 examinations. Participation, detection and additional FP rates were calculated for women who previously received FP results compared to women with true negative (TN) results. After 7 examinations, the cumulative risk of a TP result was 3.7% and the cumulative risk of a FP result was 9.1%. After 11 examinations, this increased to 7.1% and 13.5%, respectively. Following a FP result, participation was lower (71%-81%) than following a TN result (>90%). In women with a FP result, more TP results (factor 1.59 [95% CI: 1.44-1.72]), more interval cancers (factor 1.66 [95% CI: 1.41-1.91]) and more FP results (factor 1.96 [95% CI: 1.87-2.05]) were found than in women with TN results. In conclusion, due to a low recall rate in the Netherlands, the cumulative risk of a FP recall is relatively low, while the cumulative risk of a TP result is comparable. Breast cancer diagnoses and FP results were more common in women with FP results than in women with TN results, while participation was lower.

Breast cancer screening and overdiagnosis

Overdiagnosis is a harmful consequence of screening which is particularly challenging to estimate. An unbiased setting to measure overdiagnosis in breast cancer screening requires comparative data from a screened and an unscreened cohort for at least 30 years. Such randomised data will not become available, leaving us with observational data over shorter time periods and outcomes of modelling. This collaborative effort of the International Cancer Screening Network quantified the variation in estimated breast cancer overdiagnosis in organised programmes with evaluation of both observed and simulated data, and presented examples of how modelling can provide additional insights. Reliable observational data, analysed with study design accounting for methodological pitfalls, and modelling studies with different approaches, indicate that overdiagnosis accounts for less than 10% of invasive breast cancer cases in a screening target population of women aged 50 to 69. Estimates above this level are likely to derive from inaccuracies in study design. The widely discrepant estimates of overdiagnosis reported from observational data could substantially be reduced by use of a cohort study design with at least 10 years of follow-up after screening stops. In contexts where concomitant opportunistic screening or gradual implementation of screening occurs, and data on valid comparison groups are not readily available, modelling of screening intervention becomes an advantageous option to obtain reliable estimates of breast cancer overdiagnosis.

Mammographic Density and Screening Sensitivity, Breast Cancer Incidence and Associated Risk Factors in Danish Breast Cancer Screening

Background: Attention in the 2000s on the importance of mammographic density led us to study screening sensitivity, breast cancer incidence, and associations with risk factors by mammographic density in Danish breast cancer screening programs. Here, we summarise our approaches and findings. Methods: Dichotomized density codes: fatty, equal to BI-RADS density code 1 and part of 2, and other mixed/dense data from the 1990s—were available from two counties, and BI-RADS density codes from one region were available from 2012/13. Density data were linked with data on vital status, incident breast cancer, and potential risk factors. We calculated screening sensitivity by combining data on screen-detected and interval cancers. We used cohorts to study high density as a predictor of breast cancer risk; cross-sectional data to study the association between life style factors and density, adjusting for age and body mass index (BMI); and time trends to study the prevalence of high density across birth cohorts. Results: Sensitivity decreased with increasing density from 78% in women with BI-RADS 1 to 47% in those with BI-RADS 4. For women with mixed/dense compared with those with fatty breasts, the rate ratio of incident breast cancer was 2.45 (95% CI 2.14–2.81). The percentage of women with mixed/dense breasts decreased with age, but at a higher rate the later the women were born. Among users of postmenopausal hormone therapy, the percentage of women with mixed/dense breasts was higher than in non-users, but the patterns across birth cohorts were similar. The occurrence of mixed/dense breast at screening age decreased by a z-score unit of BMI at age 13—odds ratio (OR) 0.56 (95% CI 0.53–0.58)—and so did breast cancer risk and hazard ratio (HR) 0.92 (95% CI 0.84–1.00), but it changed to HR 1.01 (95% CI 0.93–1.11) when controlled for density. Age and BMI adjusted associations between life style factors and density were largely close to unity; physical activity OR 1.06 (95% CI 0.93–1.21); alcohol consumption OR 1.01 (95% CI 0.81–1.27); air pollution OR 0.96 (95% 0.93–1.01) per 20 μg/m³; and traffic noise OR 0.94 (95% CI 0.86–1.03) per 10 dB. Weak negative associations were seen for diabetes OR 0.61 (95% CI 0.40–0.92) and cigarette smoking OR 0.86 (95% CI 0.75–0.99), and a positive association was found with hormone therapy OR 1.24 (95% 1.14–1.35). Conclusion: Our data indicate that breast tissue in middle-aged women is highly dependent on childhood body constitution while adult life-style plays a modest role, underlying the need for a long-term perspective in primary prevention of breast cancer.