Personalized screening based on risk and density: prevalence data from the RIBBS study

To present the prevalence screening results of the RIsk-Based Breast Screening (RIBBS) study (ClinicalTrials.gov NCT05675085), a quasi-experimental population-based study evaluating a personalized screening model for women aged 45-49. This model uses digital breast tomosynthesis (DBT) and stratifies participants by risk and breast density, incorporating tailored screening intervals with or without supplemental imaging (ultrasound, US, and breast MRI), with the goal of reducing advanced breast cancer (BC) incidence compared to annual digital mammography (DM).

An interventional cohort of 10,269 women aged 45 was enrolled (January 2020-December 2021. Participants underwent DBT and completed a BC risk questionnaire. Volumetric breast density and lifetime risk were used to assign five subgroups to tailored screening regimens: low-risk low-density (LR-LD), low-risk high-density (LR-HD), intermediate-risk low-density (IR-LD), intermediate-risk high-density (IR-HD), and high-risk (HR). Screening performance was compared with an observational control cohort of 43,838 women undergoing annual DM.

Compared to LR-LD, intermediate-risk groups showed a 4.9- (IR-LD) and 4.6-fold (IR-HD) higher prevalence of BC, driven by a 7.1- and 7.1-fold higher prevalence of pT1c tumors. The interventional cohort had lower recall rate (rate ratio, 0.5), higher surgery rate (1.9) and increased prevalence of DCIS (2.9), pT1c (2.3) and grade 3 tumors (2.4), compared to controls.

The prevalence screening demonstrated the feasibility of using DBT and -in high-density subgroups- supplemental US. The stratification criteria effectively identified subpopulations with different BC prevalence. Increasing the detection rate of pT1c tumors is not sufficient but necessary to achieve a reduction in advanced BC incidence.