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Abstract HER2-15: HER2-15 Retrospective Study to Estimate the Prevalence and Describe the Clinicopathological Characteristics, Treatment Patterns, and Outcomes of HER2-Low Breast Cancer

2023· article· en· W4322772140 on OpenAlexaff
Giuseppe Viale, Mark Basik, Naoki Niikura, Eriko Tokunaga, Sara Y. Brucker, Frédérique Penault‐Llorca, Naoki Hayashi, Joohyuk Sohn, Rita Sousa, Adam Brufsky, Ciara O’Brien, Fernando Schmitt, Gavin C. Higgins, Della Varghese, Gareth D. James, Akira Moh, Andrew Livingston, Victoria de Giorgio‐Miller

Bibliographic record

VenueCancer Research · 2023
Typearticle
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsJewish General Hospital
Fundersnot available
KeywordsMedicineImmunohistochemistryConcordanceInternal medicineBreast cancerTrastuzumabOncologyMetastatic breast cancerCancer

Abstract

fetched live from OpenAlex

Abstract Background: About 60% of breast cancers (BCs) traditionally categorized as HER2 negative (HER2-neg; immunohistochemistry [IHC] 0, IHC 1+ or IHC 2+/in situ hybridization [ISH]–) express low levels of HER2 (HER2-low; IHC 1+ or IHC 2+/ISH–; Schettini, NPJ Breast Cancer 2021). In the phase 3 DESTINY-Breast04 trial (NCT03734029), trastuzumab deruxtecan (T-DXd) showed significantly longer progression-free survival and overall survival (OS) vs physician’s choice of chemotherapy in patients (pts) with HER2-low metastatic BC (mBC) who previously received chemotherapy (Modi, NEJM 2022). As HER2-low becomes a clinically relevant HER2 status among pts with BC, greater understanding of pts with HER2-low disease is needed, including identification of these pts using conventional IHC assays. Our objectives were to assess the prevalence of HER2-low among HER2-neg mBC based on rescored HER2 IHC slides, to describe characteristics of pts with HER2-low mBC, and to characterize concordance between historical HER2 scores and rescores. Methods: This global, multicenter, retrospective study (NCT04807595) included pts with confirmed HER2-neg (HER2 IHC 0, 1+, or 2+/ISH−) unresectable/mBC diagnosed from 2014 through 2017. HER2 IHC-stained slides were rescored after training on low-end expression scoring using Ventana 4B5 and other assays by local laboratories at 13 sites in 10 countries blinded to historical HER2 scores. BCs were categorized as HER2-low (IHC 1+ or IHC 2+/ISH−) or HER2 IHC 0 (IHC 0 or >0< 1+). Prevalence of HER2-low and concordance between historical HER2 scores and rescores were assessed. Demographics, clinicopathological characteristics, treatment patterns, and outcomes were examined via data from medical charts/health records. Results: HER2 rescores were obtained for 781 pts with HER2-neg mBC. HER2-low prevalence was 67.1% overall; 71.1% in hormone receptor (HR)–positive (HR+) and 52.5% in HR–negative (HR−) subgroups. There were no notable differences in characteristics (Table) or treatment patterns between pts with HER2-low and HER2 IHC 0. The most frequent therapies used in the first treatment in the metastatic setting were endocrine therapy (64.1%) for pts with HR+ mBC and chemotherapy (94.4%) for pts with HR− mBC. Among pts with HR+ mBC, 10.2% received cyclin-dependent kinase 4/6 inhibitors as part of their first treatment. There were no statistically significant differences in clinical outcomes between the HER2-low and HER2 IHC 0 groups within each HR subgroup. For pts with HR+ mBC, median time to first subsequent treatment was 10 and 8 months for the HER2-low and HER2 IHC 0 groups, respectively. Overall, concordance was 81.2% (kappa=0.582). Concordance between historical HER2 scores and rescores was 87.3% for HER2-low and 70.1% for HER2 IHC 0 samples. Conclusions: The prevalence of HER2-low (67.1%) among pts previously categorized as HER2-neg mBC in this study was similar to that of an earlier study (≈60%). No obvious differences in patient characteristics or clinical presentation were seen between pts with HER2-low and HER2 IHC 0 mBC. Overall percentage agreement between rescored and historical HER2 scores was 81.2%; agreement was numerically greater for HER2-low than HER2 IHC 0. As HER2-targeted therapies such as T-DXd for the treatment of pts with HER2-low BC are emerging, a greater understanding of pts with HER2-low expression who may benefit from these therapies is important. Citation Format: Giuseppe Viale, Mark Basik, Naoki Niikura, Eriko Tokunaga, Sara Brucker, Frédérique Penault-Llorca, Naoki Hayashi, Joo Hyuk Sohn, Rita Teixeira de Sousa, Adam M. Brufsky, Ciara S. O’Brien, Fernando Schmitt, Gavin Higgins, Della Varghese, Gareth D. James, Akira Moh, Andrew Livingston, Victoria de Giorgio-Miller. HER2-15 Retrospective Study to Estimate the Prevalence and Describe the Clinicopathological Characteristics, Treatment Patterns, and Outcomes of HER2-Low Breast Cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr HER2-15.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.094
GPT teacher head0.473
Teacher spread0.379 · 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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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