ArticleJournal of the National Cancer Institute2011
Microarray-based class discovery for molecular classification of breast cancer: analysis of interobserver agreement.
Article in Journal of the National Cancer Institute, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.
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Who cites it
56 citing papers in PubMed, 135 citations in OpenAlex.
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- Comparing Breast Cancer Multiparameter Tests in the OPTIMA Prelim Trial: No Test Is More Equal Than the Others.Journal of the National Cancer Institute · 2016Trial
- Impact of Proton Irradiation Depending on Breast Cancer Subtype in Patient-Derived Cell Lines.International journal of molecular sciences · 2024Article
- Radiologic imaging biomarkers in triple-negative breast cancer: a literature review about the role of artificial intelligence and the way forward.BJR artificial intelligence · 2024Review
- Modulation of JAK-STAT Signaling by LNK: A Forgotten Oncogenic Pathway in Hormone Receptor-Positive Breast Cancer.International journal of molecular sciences · 2023Review
- RNA sequencing-based single sample predictors of molecular subtype and risk of recurrence for clinical assessment of early-stage breast cancer.NPJ breast cancer · 2022Article
- Neo-Adjuvant Chemotherapy in Luminal, Node Positive Breast Cancer: Characteristics, Treatment and Oncological Outcomes: A Single Center's Experience.European journal of breast health · 2021Article
- Comparative survival analysis of multiparametric tests-when molecular tests disagree-A TEAM Pathology study.NPJ breast cancer · 2021Article
- Deep-learning approach to identifying cancer subtypes using high-dimensional genomic data.Bioinformatics (Oxford, England) · 2020Article
- Molecular Profiles of Matched Primary and Metastatic Tumor Samples Support a Linear Evolutionary Model of Breast Cancer.Cancer research · 2020Article
- Computational approaches to support comparative analysis of multiparametric tests: Modelling versus Training.PloS one · 2020Article
- Systems biology: perspectives on multiscale modeling in research on endocrine-related cancers.Endocrine-related cancer · 2019Review
- Clinical utility of multigene profiling assays in early-stage breast cancer.Current oncology (Toronto, Ont.) · 2017Article
- Statistical significance for hierarchical clustering.Biometrics · 2017Article
- Computational approach for deriving cancer progression roadmaps from static sample data.Nucleic acids research · 2017Article
- Breast cancer classification and prognostication through diverse systems along with recent emerging findings in this respect; the dawn of new perspectives in the clinical applications.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2016Review
- Breast cancer subtype predictors revisited: from consensus to concordance?BMC medical genomics · 2016Article
- Meta-analytic framework for sparseJournal of the American Statistical Association · 2016Article
Corrections and comments
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
backgroundBreast cancers can be classified by hierarchical clustering using an "intrinsic" gene list into one of at least five molecular subtypes: basal-like, HER2, luminal A, luminal B, and normal breast-like. Five different intrinsic gene lists composed of varying numbers of genes have been used for molecular subtype identification and classification of breast cancers. The aim of this study was to determine the objectivity and interobserver reproducibility of the assignment of molecular subtype classes by hierarchical cluster analysis.
methodsThree publicly available breast cancer datasets (n = 779) were subjected to two-way average-linkage hierarchical cluster analysis using five distinct intrinsic gene lists. We used free-marginal Kappa statistics to analyze interobserver agreement among five breast cancer researchers for the whole classification and for each molecular subtype separately according to each intrinsic gene list for each breast cancer dataset.
resultsNone of the classification systems tested produced almost perfect agreement (Kappa ≥ 0.81) among observers. However, substantial interobserver agreement (70.8% to 76.1% of the samples and free-marginal Kappa scores from 0.635 to 0.701) was consistently observed in all datasets for four molecular subtypes (luminal, basal-like, HER2, and normal breast-like). When luminal cancers were subdivided (luminal A, B, and C), none of the classification systems produced substantial agreement (Kappa ≥ 0.61) in all the datasets analyzed. Analysis of each subtype separately revealed that only two (basal-like and HER2) could be reproducibly identified by independent observers (Kappa ≥ 0.81).
conclusionsAssignment of molecular subtype classes of breast cancer based on the analysis of dendrograms obtained with hierarchical cluster analysis is subjective and shows modest interobserver reproducibility. For the development of a molecular taxonomy, objective definitions for each molecular subtype and standardized methods for their identification are required.
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