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Record W2511312089 · doi:10.1093/ajcp/aqw117

Comparison of HER2 Dual-Color and Fluorescence In Situ Hybridization in Breast Cancer

2016· article· en· W2511312089 on OpenAlexaff
Tiffany Shao, Martha Wood, Anthony Wing, Marta Hnatovska, María Fernanda Mendes, J. Brendan M. Mullen, Martin C. Chang

Bibliographic record

VenueAmerican Journal of Clinical Pathology · 2016
Typearticle
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsMount Sinai HospitalUniversity of Toronto
Fundersnot available
KeywordsFluorescence in situ hybridizationHuman Epidermal Growth Factor Receptor 2Fish <Actinopterygii>Breast cancerBiologyCohortIn situ hybridizationCopy-number variationPathologyCancerOncologyMedicineInternal medicineChromosomeGeneticsGeneFisheryGene expression

Abstract

fetched live from OpenAlex

OBJECTIVES: Human epidermal growth factor receptor 2 (HER2; ERBB2 gene) is of prognostic and predictive significance in breast carcinoma. Both fluorescence in situ hybridization (FISH) and dual-color in situ hybridization (DISH) methods are available. DISH and FISH are highly concordant in validation studies, but differences may be more prevalent in the equivocal range. Our goal was to compare FISH and DISH on a cohort enriched for equivocal cases, with respect to HER2 determination. METHODS: The cohort was enriched for equivocal (2+) cases. DISH and FISH were evaluated using standard protocols and the results compared with respect to HER2 status, HER2 copy number, and HER2/chromosome 17 (Chr17) ratio. RESULTS: In total, 109 cases were identified. The agreement rate of DISH with FISH was 74%. The mean ± SD HER2/Chr17 ratio by DISH was 1.63 ± 0.08 vs 1.59 ± 0.26 by FISH (P = .45). The mean ± SD HER2 copy number by DISH was 4.56 ± 0.45 vs 4.75 ± 1.08 by FISH (P = .004). Individual signals were more easily resolved using FISH in cases with higher copy numbers. CONCLUSIONS: In our cohort enriched for equivocal cases, the numerical values of HER2 copy number were significantly lower using DISH, resulting in discordances. Although DISH is a valid method, variations with FISH may be expected in high-equivocal cases and in quality assurance activities.

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

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.248
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.084
GPT teacher head0.507
Teacher spread0.423 · 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

Machine predicted; a candidate call from one teacher head, not a consensus.

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

Citations7
Published2016
Admission routes1
Has abstractyes

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