ArticleThe journal of pathology. Clinical research2016
Nottingham Prognostic Index Plus: Validation of a clinical decision making tool in breast cancer in an independent series.
Article in The journal of pathology. Clinical research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed, 3 syntheses or guidelines pooled it, 45 citations in OpenAlex.
- Overinterpretation of findings in machine learning prediction model studies in oncology: a systematic review.Journal of clinical epidemiology · 2023Pooled it
- Reporting of prognostic clinical prediction models based on machine learning methods in oncology needs to be improved.Journal of clinical epidemiology · 2021Pooled it
- Prognostic models for breast cancer: a systematic review.BMC cancer · 2019Pooled it
- Health services research in patients with breast cancer (CAMISS-prospective): study protocol for an observational prospective study.BMC cancer · 2018Trial
- Added value of the tumor-stroma ratio to the PREDICT model for breast cancer.Breast (Edinburgh, Scotland) · 2026Article
- Identification of Patients with Early HR+ HER2- Breast Cancer at High Risk of Recurrence.Geburtshilfe und Frauenheilkunde · 2024Article
- Article
- DDX43 mRNA expression and protein levels in relation to clinicopathological profile of breast cancer.PloS one · 2023Article
- Predicting breast cancer-specific survival in metaplastic breast cancer patients using machine learning algorithms.Journal of pathology informatics · 2023Article
- Genomic assays for lobular breast carcinoma.Journal of clinical and translational research · 2022Review
- Advancement of prognostic models in breast cancer: a narrative review.Gland surgery · 2021Review
- Altona Prognostic Index: A New Prognostic Index for ER-Positive and Her2-Negative Breast Cancer of No Special Type.Cancers · 2021Article
- One-year conditional survival of dogs and cats with invasive mammary carcinomas: A concept inspired from human breast cancer.Veterinary and comparative oncology · 2021Article
- Breast cancer molecular subtypes and receptor status among women at Potchefstroom Hospital: a cross-sectional study.The Pan African medical journal · 2021Article
- A prognostic model based on cell-cycle control predicts outcome of breast cancer patients.BMC cancer · 2020Article
- External validation of a prognostic model based on total tumor load of sentinel lymph node for early breast cancer patients.Breast cancer research and treatment · 2020Article
- Cole Relaxation Frequency as a Prognostic Parameter for Breast Cancer.Journal of patient-centered research and reviews · 2020Article
- Microcalcifications Drive Breast Cancer Occurrence and Development by Macrophage-Mediated Epithelial to Mesenchymal Transition.International journal of molecular sciences · 2019Article
- Nottingham Prognostic Index is an Applicable Prognostic Tool in Non-Metastatic Triple-Negative Breast CancerAsian Pacific journal of cancer prevention : APJCP · 2019Article
- Basal-like Breast Cancers: From Pathology to Biology and Back Again.Stem cell reports · 2018Review
Corrections and comments
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Authors and funding
16 authors at 7 institutions in 2 countries.
Funding
Abstract
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 series of BC. Eight hundred and eighty five primary early stage BC cases from Edinburgh were semi-quantitatively assessed for 10 biomarkers [Estrogen Receptor (ER), Progesterone Receptor (PgR), cytokeratin (CK) 5/6, CK7/8, epidermal growth factor receptor (EGFR), HER2, HER3, HER4, p53, and Mucin 1] using immunohistochemistry and classified into biological classes by fuzzy logic-derived algorithms previously developed in the Nottingham series. Subsequently, NPI+ Prognostic Groups (PGs) were assigned for each class using bespoke NPI-like formulae, previously developed in each NPI+ biological class of the Nottingham series, utilising clinicopathological parameters: number of positive nodes, pathological tumour size, stage, tubule formation, nuclear pleomorphism and mitotic counts. Biological classes and PGs were compared between the Edinburgh and Nottingham series using Cramer's V and their role in patient outcome prediction using Kaplan-Meier curves and tested using Log Rank. The NPI+ biomarker panel classified the Edinburgh series into seven biological classes similar to the Nottingham series (p > 0.01). The biological classes were significantly associated with patient outcome (p < 0.001). PGs were comparable in predicting patient outcome between series in Luminal A, Basal p53 altered, HER2+/ER+ tumours (p > 0.01). The good PGs were similarly validated in Luminal B, Basal p53 normal, HER2+/ER- tumours and the poor PG in the Luminal N class (p > 0.01). Due to small patient numbers assigned to the remaining PGs, Luminal N, Luminal B, Basal p53 normal and HER2+/ER- classes could not be validated. This study demonstrates the reproducibility of NPI+ and confirmed its prognostic value in an independent cohort of primary BC. Further validation in large randomised controlled trial material is warranted.
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Registered trials
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