Extending Age Ranges in Breast Cancer Screening in Four European Countries: Model Estimations of Harm-to-Benefit Ratios

SIMPLE SUMMARY: Breast cancer screening causes harms and benefits. The balance between the two varies by age. By applying microsimulation modelling, we compared several age ranges of screening in four European countries (the Netherlands, Finland, Italy and Slovenia) and evaluated the respective harm-to-benefit ratios. In all countries, adding screening between the ages 45 and 49 or 70 and 74 resulted in more life-years gained and more breast cancer deaths averted, but at the expense of increases in harms. Adapting the age range of breast cancer screening is an option to improve harm-to-benefit ratios in all four countries. The prioritization of considered harms and benefits affects the interpretation of results. ABSTRACT: The main benefit of breast cancer (BC) screening is a reduction in mortality from BC. However, screening also causes harms such as overdiagnosis and false-positive results. The balance between benefits and harms varies by age. This study aims to assess how harm-to-benefit ratios of BC screening vary by age in the Netherlands, Finland, Italy and Slovenia. Using microsimulation models, we simulated biennial screening with 100% attendance at varying ages for cohorts of women followed over a lifetime. The number of overdiagnoses, false-positive diagnoses, BC deaths averted and life-years gained (LYG) were calculated per 1000 women. We compared four strategies (50–69, 45–69, 45–74 and 50–74) by calculating four harm-to-benefit ratios, respectively. Compared to the reference strategy 50–69, screening women at 45–74 or 50–74 years would be less beneficial in any of the four countries than screening women at 45–69, which would result in relatively fewer overdiagnoses per death averted or LYG. At the same time, false-positive results per death averted would increase substantially. Adapting the age range of BC screening is an option to improve harm-to-benefit ratios in all four countries. Prioritization of considered harms and benefits affects the interpretation of results.