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Ki-67 is a Luminal B marker that identifies a high-risk subgroup in hormone receptor positive and node negative breast cancer

2007· article· en· W2232080041 on OpenAlexaff
Maggie C.U. Cheang, D. Voduc, Suet Yi Leung, Dmitry Turbin, Philip S. Bernard, M. Ellis, ER Mardis, Charles M. Perou, Torsten O. Nielsen

Bibliographic record

VenueJournal of Clinical Oncology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsBreast cancerImmunohistochemistryKi-67MedicineTissue microarrayPathologyCancerPopulationHormone receptorProliferation MarkerInternal medicineLymph nodeOncology

Abstract

fetched live from OpenAlex

10521 Background: Gene expression profiling studies have revealed prognostically significant intrinsic breast cancer subtypes, designated Luminal A, Luminal B, Basal and Her2. Expression of ER and associated genes characterizes the luminal breast cancers. The Lum B subgroup is associated with poor outcome, but we lack immunohistochemical (IHC) markers to distinguish Lum A and Lum B subgroups. MKI67 is one gene known to be highly expressed in Lum B tumors, encoding the Ki-67 protein, a robust marker of cell proliferation. In this study, we perform IHC analysis of Ki-67 in a large breast cancer tissue microarray. Methods: Our patient cohort consists of 2222 consecutive cases of invasive breast cancer referred to the BC Cancer Agency from 1986 to 1992. Archival paraffin tissue blocks were used to construct a tissue microarray that was then stained for Ki-67 using a commercially available mouse monoclonal antibody. Ki-67 staining was scored quantitatively by automated image analysis and a tumor was positive if the percent positive nuclei was >30%’ Results: Of the 2,222 patients, there are 1,437 Luminal tumors as defined by IHC (ER or PR positive). As Her2 positive status is an established marker of poor prognosis, we excluded these tumors from our analysis. Of the remaining tumors, 9% were Ki-67 positive when using a ki-67 cut off of 30% positive nuclei. In survival analysis of patients ER/PR positive and Her2 negative, we found that Ki-67 identifies a population with poor prognosis (10-yr BCSS 60% vs. 80%). In a multivariate Cox regression we found that Ki-67 is independently prognostic. We repeated Cox regression analysis including only node negative patients and again found that Ki-67 is an independent predictor of poor outcome. Conclusions: Ki-67 has prognostic significance on multivariate survival analysis. Hormone receptor positive and node negative status is typically associated with a favorable outcome for breast cancer. However, Ki-67 is able to identify a small, but clinically significant subgroup with a particularly poor outcome. Defining the Luminal B subtype as (ER or PR) positive and (HER2 or Ki-67) positive, results in a subgroup that contains 18% of hormone receptor positive breast cancers with 10-yr BCSS of 61%. No significant financial relationships to disclose.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationalmedium
models agreeAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.377
Teacher spread0.349 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2007
Admission routes1
Has abstractyes

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