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Record W2982402876 · doi:10.21873/anticanres.11701

Concordance of HER2 Immunohistochemistry and Fluorescence In Situ Hybridization Using Tissue Microarray in Breast Cancer

2017· article· en· W2982402876 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAnticancer Research · 2017
Typearticle
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsHôpital du Saint-SacrementUniversité Laval
FundersFonds de Recherche du Québec - SantéFondation du cancer du sein du QuébecUniversité Laval
KeywordsConcordanceImmunohistochemistryTissue microarrayFluorescence in situ hybridizationBreast cancerPathologyIn situ hybridizationMedicineCancerBiologyOncologyInternal medicineGene expressionGene

Abstract

fetched live from OpenAlex

AIM: Immunohistochemistry (IHC) and fluorescence in situ hybridization (FISH) are common methods for assessment of human epidermal growth factor receptor 2 (HER2) in breast cancer. MATERIALS AND METHODS: In a cohort of 498 consecutive patients with breast cancer, we examined concordance between IHC and FISH for HER2 on tissue microarray (TMA) sections. In a subset of 116 specimens, we examined HER2 concordance from the block used for diagnostics and a randomly-chosen additional block (a proxy of the core biopsy). RESULTS: Overall concordance between both methods on TMA sections was 93.8% and between HER2, determined on diagnostic and additional blocks, was 93.6% for IHC and 98.0% for FISH. CONCLUSION: Since some cases were discordant, we suggest that both methods be used for HER2 assessment. The lower concordance rate between diagnostic and additional blocks using IHC compared to FISH suggests a greater variability of IHC staining across tumor regions than for FISH results.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.081
GPT teacher head0.487
Teacher spread0.405 · 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