Exploring opportunities to de-escalate treatment of ductal carcinoma in situ and early-stage breast cancer

Abstract

This thesis investigates treatment de-escalation for ductal carcinoma in situ (DCIS) and early-stage breast cancer, focusing on reducing overtreatment and enhancing patient quality of life. DCIS, often detected through screening, does not always progress to invasive cancer, leading to potential overtreatment risks. The thesis examines various risk factors—such as family history, BMI, menopausal status, and breast density—that may influence DCIS progression to invasive cancer.

A systematic review of these risk factors aims to identify predictors of recurrence, providing insight into tailoring patient management. Additionally, artificial intelligence is explored for its potential to assess DCIS risk levels accurately, supporting non-invasive treatment approaches. Active surveillance trials like COMET, LORIS, and LORD, which assess monitoring instead of immediate treatment for low-risk DCIS cases, are highlighted as important advancements. For early-stage invasive cancer, genomic assays such as MammaPrint® are examined to help identify candidates who could safely avoid radiotherapy or chemotherapy. This thesis underscores the need for precision medicine, advocating for personalized treatment that spares patients from unnecessary interventions while maintaining effective cancer control.