Treatment optimization for breast cancer patients according to age and tumor subtype

Abstract

In this thesis entitled 'Treatment optimization for breast cancer patients according to age and tumor subtype', we show that optimizing breast cancer treatment is possible in various ways and different settings. The investigation of prognosis and prognostic biomarkers enables us to identify which women need adjuvant systemic treatment. In part I of this thesis we describe the design of a study on young adjuvant treatment naïve breast cancer patients (chapter 1) which allows us to study the unbiased prognosis of these women (chapter 2). In addition, we explore and validate promising prognostic biomarkers (chapter 2 and chapter 3), all with the goal of treatment optimization. When adjuvant systemic treatment is deemed necessary there are often several treatment options. Based on tumor characteristics, predictive biomarkers or a combination thereof, the best treatment for an individual patient is selected. In Part II of this thesis, we describe three studies (chapter 4 – chapter 6) which investigated the effectiveness of already existing treatments in patients who were usually excluded from the large randomized controlled trials. Lastly, improvements can also be made in the metastatic setting, for instance by combining already existing treatment modalities. In part III we describe the study design of the REVIVAL study (chapter 7), a phase-Ib study on the safety of the olaparib-carboplatin treatment combination following a change in olaparib formulation (chapter 8).