ArticleBritish journal of cancer2014
Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer.
Article in British journal of cancer, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 2 of them syntheses that pooled it.
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Who cites it
40 citing papers in PubMed, 2 syntheses or guidelines pooled it, 103 citations in OpenAlex.
- Prognostic models for breast cancer: a systematic review.BMC cancer · 2019Pooled it
- Survival estimates stratified by the Nottingham Prognostic Index for early breast cancer: a systematic review and meta-analysis of observational studies.Systematic reviews · 2018Pooled it
- Added value of the tumor-stroma ratio to the PREDICT model for breast cancer.Breast (Edinburgh, Scotland) · 2026Article
- Review
- Article
- Utility of the CPS + EG score with real-life data in patients with breast cancer undergoing neoadjuvant chemotherapy.Oncology letters · 2025Article
- Female breast cancer classification using immunohistochemistry biomarkers staining in Botswana.BMC cancer · 2025Article
- Differential response of placental cells to high D-glucose and its impact on extracellular vesicle biogenesis and trafficking via small GTPase Ras-related protein RAB-7A.Journal of extracellular biology · 2024Article
- Thyroglobulin expression, Ki-67 index, and lymph node ratio in the prognostic assessment of papillary thyroid cancer.Scientific reports · 2023Article
- DDX43 mRNA expression and protein levels in relation to clinicopathological profile of breast cancer.PloS one · 2023Article
- Comparison of the Nottingham Prognostic Index and OncotypeDX© recurrence score in predicting outcome in estrogen receptor positive breast cancer.Breast (Edinburgh, Scotland) · 2022Article
- The role of CPT1A as a biomarker of breast cancer progression: a bioinformatic approach.Scientific reports · 2022Article
- Classification of Breast Cancer Nottingham Prognostic Index Using High-Dimensional Embedding and Residual Neural Network.Cancers · 2022Article
- Advancement of prognostic models in breast cancer: a narrative review.Gland surgery · 2021Review
- A prognostic model based on cell-cycle control predicts outcome of breast cancer patients.BMC cancer · 2020Article
- Correlation between HER2 Expression and Clinicopathological Features of Breast Cancer: A Cross- Sectional Study in Vietnam.Asian Pacific journal of cancer prevention : APJCP · 2020Article
- Gene Expression Profiling Tests for Early-Stage Invasive Breast Cancer: A Health Technology Assessment.Ontario health technology assessment series · 2020Article
- Quantitative parameters of MRI andAmerican journal of nuclear medicine and molecular imaging · 2020Article
- A 23 gene-based molecular prognostic score precisely predicts overall survival of breast cancer patients.EBioMedicine · 2019Article
- Genomics applied to the treatment of breast cancer.Oncotarget · 2019Review
Corrections and comments
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Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundCurrent 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.
methodsIn 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.
resultsSeven 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.
conclusionThis study provides proof-of-principle evidence for the use of NPI+ in supporting improved individualised clinical decision making.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.