Overdiagnosis of invasive breast cancer in population-based breast cancer screening: A short- and long-term perspective

European Journal of Cancer(2022)

Cited 9|Views13
No score
Abstract
Background Overdiagnosis of invasive breast cancer (BC) is a contentious issue. Objective The aim of this paper is to estimate the overdiagnosis rate of invasive BC in an organised BC screening program and to evaluate the impact of age and follow-up time. Methods The micro-simulation model SiMRiSc was calibrated and validated for BC screening in Flanders, where women are screened biennially from age 50 to 69. Overdiagnosis rate was defined as the number of invasive BC that would not have been diagnosed in the absence of screening per 100,000 screened women during the screening period plus follow-up time (which was set at 5 years and varied from 2 to 15 years). Overdiagnosis rate was calculated overall and stratified by age. Results The overall overdiagnosis rate for women screened biennially from 50 to 69 was 20.1 (95%CI: 16.9–23.2) per 100,000 women screened at 5-year follow-up from stopping screening. Overdiagnosis at 5-year follow-up time was 12.9 (95%CI: 4.6–21.1) and 74.2 (95%CI: 50.9–97.5) per 100,000 women screened for women who started screening at age 50 and 68, respectively. At 2- and 15-year follow-up time, overdiagnosis rate was 98.5 (95%CI: 75.8–121.3) and 13.4 (95%CI: 4.9–21.9), respectively, for women starting at age 50, and 297.0 (95%CI: 264.5–329.4) and 34.2 (95%CI: 17.5–50.8), respectively, for those starting at age 68. Conclusions Sufficient follow-up time (≥10 years) after screening stops is key to obtaining unbiased estimates of overdiagnosis. Overdiagnosis of invasive BC is a larger problem in older compared to younger women.
More
Translated text
Key words
Breast neoplasms,Mammography,Mass screening,Overdiagnosis,Modelling studies,Invasive breast cancer
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined