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. What's new The detection of breast cancer before symptoms arise greatly increases the chance of prolonging survival or even curing malignancy. However, the assumption that asymptomatic disease progresses to symptomatic disease is a major factor in breast cancer overdiagnosis. While estimates of overdiagnosis vary substantially, the present analysis of observational data and data from modelling studies shows that overdiagnosis accounts for less than 10 percent of invasive breast cancer cases among women ages 50 to 69. The findings reaffirm the idea that observational studies require careful design to avoid methodological pitfalls and highlight the value of insight gained from well‐calibrated modelling studies.