Incorporation of clinicopathologic variables in a second-stage analysis resulted in identification of distinct prognostic groups within each molecular class (NPI+). Seven core molecular classes were identified using a selective panel of 10 biomarkers. The NPI+ was then used to predict outcome in the different molecular classes. These variables were combined in formulae to prognostically stratify different molecular classes, collectively known as the Nottingham Prognostic Index Plus (NPI+). Subsequently, each class was further stratified using a set of well-defined prognostic clinicopathologic variables. In the current study, a comprehensive panel of biomarkers with relevance to BC was applied to a large and well-characterised series of BC, using immunohistochemistry and different multivariate clustering techniques, to identify the key molecular classes. In this study, we hypothesised that molecular features of BC are a key driver of tumour behaviour and when coupled with a novel and bespoke application of established clinicopathologic prognostic variables can predict both clinical outcome and relevant therapeutic options more accurately than existing methods. Global gene expression profiling studies have demonstrated that BC comprises distinct molecular classes with clinical relevance. Current management of breast cancer (BC) relies on risk stratification based on well-defined clinicopathologic factors.
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