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Record W4414163609 · doi:10.1016/j.ebiom.2025.105919

New standards in HER2-low testing: the CASI-01 comparative methods study

2025· article· en· W4414163609 on OpenAlexaff
David J. Dabbs, Emina Torlakovic, Søren Nielsen, Suzanne Parry, Jing Yu, Catherine T. Stoos, Beth Z. Clark, Henrik Høeg, Jeppe Thagaard, Seshi R. Sompuram, Stephen P. Naber, Yukako Yagi, James Sayre, Kodela Vani, Mélissande Cossutta, F. Soussaline, Alexandre Papine, Nils t'Hart, Matthias Szabolcs, Bharat Jasani, Mary Kinloch, Luis Chiriboga, Keith Miller, Steve Bogen

Bibliographic record

VenueEBioMedicine · 2025
Typearticle
Languageen
FieldMedicine
TopicHER2/EGFR in Cancer Research
Canadian institutionsRoyal University HospitalSaskatchewan Health Authority
FundersNational Cancer InstituteNational Institutes of Health
KeywordsWork (physics)MEDLINECancerPublic healthHealth policy

Abstract

fetched live from OpenAlex

BACKGROUND: The introduction of Trastuzumab deruxtecan (T-Dxd) has exposed clinically significant limitations in accurately detecting HER2-low expression testing when using immunohistochemistry (IHC) assays originally developed to detect HER2 over-expression. While HER2 testing is widely used to determine T-Dxd eligibility, no HER2-low assay was ever validated against HER2 protein expression. METHODS: To address this pressing need, the Consortium for Analytic Standardization in Immunohistochemistry (CASI) conducted the CASI-01 study, involving 54 IHC laboratories across Europe and the U.S. The study aimed to identify optimal assay conditions for accurate HER2 testing, differentiating between HER2 overexpression (3+) for Trastuzumab eligibility and HER2-low expression (1+ or ultra-low) for T-Dxd eligibility. The conventional FDA-cleared HER2 assay ("predicate") was compared with higher-sensitivity assays using pathologist versus image analysis readouts. HER2 overexpression was validated against HER2 gene amplification via in situ hybridisation (ISH), while HER2-low accuracy was evaluated using newly introduced HER2 reference standards and a novel IHC parameter-dynamic range. FINDINGS: CASI-01 revealed variability in predicate HER2 assays, with detection thresholds ranging from 30,000 to 60,000 among laboratories. Despite this variability, these assays demonstrated high accuracy for identifying HER2 overexpression (3+), with 85.7% (18/21) sensitivity (95% confidence limits 63.66-96.95%) and 100% (49/49) specificity (95% confidence limits 92.75-100%), though sensitivity may have been limited by the use of older tissue specimens, with loss or reduced expression levels of the HER2 protein. However, these same assays exhibited poor dynamic range for detecting HER2-low scores. Enhanced analytic sensitivity of IHC assays combined with image analysis overcame this limitation with HER2-low scores, achieving a six-fold improvement (p = 0.0017). INTERPRETATION: IHC assays with detection thresholds in the range of 30,000-60,000 HER2 molecules per cell yield accurate results for determination of Trastuzumab eligibility (HER2 3+) but fail to demonstrate the dynamic range for accurate HER2-low scores. Enhanced analytic sensitivity of HER2 assays combined with image analysis addresses this critical gap in HER2-low testing. More generally, CASI-01 introduces pivotal advancements in precision medicine: (a) the importance of reporting IHC analytic sensitivity and ability to demonstrate an assay dynamic range, and (b) image analysis can surpass pathologist readout accuracy in specific clinical contexts. FUNDING: This work was supported by the National Cancer Institute of the National Institutes of Health under Award Number R44CA268484.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.003
Science and technology studies0.0000.000
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 head0.186
GPT teacher head0.575
Teacher spread0.389 · 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 designNot applicable
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

Citations9
Published2025
Admission routes1
Has abstractyes

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