title: Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer.
abstract: BACKGROUND
  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.
  
  
  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.
  
  
  RESULTS
  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.
  
  
  CONCLUSIONS
  This study provides proof-of-principle evidence for the use of NPI+ in supporting improved individualised clinical decision making.
authors.affiliation: 1] Breast Cancer Pathology Research Group, Division of Cancer and Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK [2] Cellular Pathology, The Breast Institute, Nottingham University Hospitals NHS Trust, Nottingham, UK.
authors.forename: E A
authors.initials: EA
authors.lastname: Rakha
authors.affiliation: 1] School of Computer Science, University of Nottingham, Nottingham, UK [2] Advanced Data Analysis Centre, University of Nottingham, Nottingham, UK.
authors.forename: D
authors.initials: D
authors.lastname: Soria
authors.affiliation: Breast Cancer Pathology Research Group, Division of Cancer and Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK.
authors.forename: A R
authors.initials: AR
authors.lastname: Green
authors.affiliation: College of Arts and Science, School of Science and Technology, Nottingham Trent University, Nottingham, UK.
authors.forename: C
authors.initials: C
authors.lastname: Lemetre
authors.affiliation: Cellular Pathology, The Breast Institute, Nottingham University Hospitals NHS Trust, Nottingham, UK.
authors.forename: D G
authors.initials: DG
authors.lastname: Powe
authors.affiliation: School of Computer Science, University of Nottingham, Nottingham, UK.
authors.forename: C C
authors.initials: CC
authors.lastname: Nolan
authors.affiliation: 1] School of Computer Science, University of Nottingham, Nottingham, UK [2] Advanced Data Analysis Centre, University of Nottingham, Nottingham, UK.
authors.forename: J M
authors.initials: JM
authors.lastname: Garibaldi
authors.affiliation: College of Arts and Science, School of Science and Technology, Nottingham Trent University, Nottingham, UK.
authors.forename: G
authors.initials: G
authors.lastname: Ball
authors.affiliation: 1] Breast Cancer Pathology Research Group, Division of Cancer and Stem Cells, School of Medicine, University of Nottingham, Nottingham, UK [2] Cellular Pathology, The Breast Institute, Nottingham University Hospitals NHS Trust, Nottingham, UK.
authors.forename: I O
authors.initials: IO
authors.lastname: Ellis
mesh_terms: D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000235:genetics / Q000378:metabolism*; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000473:pathology / Q000628:therapy; D003657:Decision Making; D005260:Female; D020869:Gene Expression Profiling; D006801:Humans; D008875:Middle Aged; D011379:Prognosis; D012720:Severity of Illness Index; D016019:Survival Analysis; D059467:Transcriptome; D047368:Tumor Burden
chemical_list: D014408:Biomarkers, Tumor