All Outputs (6)

Nottingham prognostic index plus (NPI+) predicts risk of distant metastases in primary breast cancer (2016)
Journal Article
Green, A. R., Soria, D., Powe, D. G., Nolan, C. C., Aleskandarany, M. A., Szász, M., …Ellis, I. O. (2016). Nottingham prognostic index plus (NPI+) predicts risk of distant metastases in primary breast cancer. Breast Cancer Research and Treatment, 157(1), 65-75. https://doi.org/10.1007/s10549-016-3804-1

The Nottingham prognostic index plus (NPI+) is based on the assessment of biological class combined with established clinicopathologic prognostic variables providing improved patient outcome stratification for breast cancer superior to the traditiona... Read More about Nottingham prognostic index plus (NPI+) predicts risk of distant metastases in primary breast cancer.

Nottingham Prognostic Index Plus: validation of a clinical decision making tool in breast cancer in an independent series (2015)
Journal Article
Green, A. R., Soria, D., Stephen, J., Powe, D. G., Nolan, C. C., Kunkler, I., …Ellis, I. O. (2016). Nottingham Prognostic Index Plus: validation of a clinical decision making tool in breast cancer in an independent series. Journal of Pathology: Clinical Research, 2, https://doi.org/10.1002/cjp2.32

The Nottingham Prognostic Index Plus (NPI+)is a clinical decision making tool in breast cancer (BC) that aims to provide improved patient outcome stratification superior to the traditional NPI. This study aimed to validate the NPI+ in an independent... Read More about Nottingham Prognostic Index Plus: validation of a clinical decision making tool in breast cancer in an independent series.

Markers of progression in early-stage invasive breast cancer: a predictive immunohistochemical panel algorithm for distant recurrence risk stratification (2015)
Journal Article
Aleskandarany, M. A., Soria, D., Green, A. R., Nolan, C., Diez-Rodriguez, M., Ellis, I. O., & Rakha, E. A. (2015). Markers of progression in early-stage invasive breast cancer: a predictive immunohistochemical panel algorithm for distant recurrence risk stratification. Breast Cancer Research and Treatment, 151(2), 325-333. https://doi.org/10.1007/s10549-015-3406-3

Accurate distant metastasis (DM) prediction is critical for risk stratification and effective treatment decisions in breast cancer (BC). Many prognostic markers/models based on tissue marker studies are continually emerging using conventional statist... Read More about Markers of progression in early-stage invasive breast cancer: a predictive immunohistochemical panel algorithm for distant recurrence risk stratification.

Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer (2014)
Journal Article
Rakha, E., Soria, D., Green, A. R., Lemetre, C., Powe, D. G., Nolan, C. C., …Ellis, I. O. (2014). Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer. British Journal of Cancer, 110(7), https://doi.org/10.1038/bjc.2014.120

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. I... Read More about Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer.

A quantifier-based fuzzy classification system for breast cancer patients (2013)
Journal Article
Soria, D., Garibaldi, J. M., Green, A. R., Powe, D. G., Nolan, C. C., Lemetre, C., …Ellis, I. O. (2013). A quantifier-based fuzzy classification system for breast cancer patients. Artificial Intelligence in Medicine, 58(3), https://doi.org/10.1016/j.artmed.2013.04.006

Objectives:Recent studies of breast cancer data have identified seven distinct clinical phenotypes (groups) using immunohistochemical analysis and a range of different clustering techniques. Consensus between unsupervised classification algorithms ha... Read More about A quantifier-based fuzzy classification system for breast cancer patients.

A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients (2010)
Journal Article
Soria, D., Garibaldi, J. M., Ambrogi, F., Green, A. R., Powe, D., Rakha, E., …Ellis, I. O. (2010). A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients. Computers in Biology and Medicine, 40(3), https://doi.org/10.1016/j.compbiomed.2010.01.003

Single clustering methods have often been used to elucidate clusters in high dimensional medical data, even though reliance on a single algorithm is known to be problematic. In this paper, we present a methodology to determine a set of ‘core classes’... Read More about A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients.