|Title||Nottingham Prognostic Index Plus (NPI+): A Modern Clinical Decision Making Tool in Breast Cancer|
|Authors||Rakha, E., Soria, D., Green, A.R., Lemetre, C., Powe, D.G., Nolan, C.C., Garibaldi, J.M., Ball, G.R. and Ellis, I.O.|
Current management of breast cancer (BC) relies on risk stratification based on well-defined clinicopathologic factors. Global gene expression profiling studies have demonstrated that BC comprises distinct molecular classes with clinical relevance. 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.
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. Subsequently, each class was further stratified using a set of well-defined prognostic clinicopathologic variables. These variables were combined in formulae to prognostically stratify different molecular classes, collectively known as the Nottingham Prognostic Index Plus (NPI+). The NPI+ was then used to predict outcome in the different molecular classes.
Seven core molecular classes were identified using a selective panel of 10 biomarkers. Incorporation of clinicopathologic variables in a second-stage analysis resulted in identification of distinct prognostic groups within each molecular class (NPI+). Outcome analysis showed that using the bespoke NPI formulae for each biological BC class provides improved patient outcome stratification superior to the traditional NPI.
This study provides proof-of-principle evidence for the use of NPI+ in supporting improved individualised clinical decision making.
|Journal||British Journal of Cancer|
|Journal citation||110 (7), pp. 1688-1697|
|Publisher||Cancer Research UK (Publisher)|
|Digital Object Identifier (DOI)||doi:10.1038/bjc.2014.120|
|Published online||11 Mar 2014|