Prognostic and Predictive Markers for Treatment Decisions in Early Breast Cancer

Abstract

Breast cancer clinically represents a heterogeneous disease. Over the last decades, the integration of prognostic and predictive markers in treatment decisions has led to a more individualized and optimized therapy. While prognosis describes the risk of disease recurrence and disease-related death after diagnosis without the influence of therapy, prediction illustrates the probability of efficacy or response of a specific therapeutic measure. The substantial decline in breast cancer mortality seen over the last 20 years is primarily due to the delivery of adjuvant systemic therapy. It is important that clinical decisions are made to minimize overtreatment, under-treatment, and incorrect treatment. Improved understanding of breast cancer biology together with the utilization of classical biomarkers and the identification of new markers or profiles is increasingly defining who should receive cancer therapy and what therapy offers the best efficacy. The molecular targets as the prerequisite for successful concepts of specific therapies like anti-estrogens, antibodies, or small molecules, have therefore high clinical value in regards to prognosis as well as prediction.