Evidence map›Paper›PMID 21421860›Full record

ArticleJournal of the National Cancer Institute2011

Microarray-based class discovery for molecular classification of breast cancer: analysis of interobserver agreement.

Alan Mackay, Britta Weigelt, Anita Grigoriadis, Bas Kreike, Rachael Natrajan, Roger A'Hern, David S P Tan, Mitch Dowsett, Alan Ashworth, Jorge S Reis-Filho

Open access · hybridAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed
8.3field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

56 citing papers in PubMed, 135 citations in OpenAlex.

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  20. Meta-analytic framework for sparseJournal of the American Statistical Association · 2016
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 1 institution in 1 country.

Alan MackayThe Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, 237 Fulham Rd, London SW3 6JB, UK.
Britta Weigelt
Anita Grigoriadis
Bas Kreike
Rachael Natrajan
Roger A'Hern
David S P Tan
Mitch Dowsett
Alan Ashworth
Jorge S Reis-Filho
Institute of Cancer Research · GB

Funding

Breast Cancer Now BREAST CANCER NOW RESEARCH CENTRECancer Research UK
6 · The paper itself

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.

Indexed as

Gene Expression ProfilingGene Expression Regulation, NeoplasticMicroarray AnalysisAdultAgedBiomarkers, TumorBreast NeoplasmsCluster AnalysisErb-b2 Receptor Tyrosine KinasesFemaleHumansMiddle AgedObserver VariationReproducibility of ResultsRetrospective StudiesBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine Kinases

Identifiers

PMID21421860
PMCPMC3079850
OpenAlexW2150524410

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.