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ALK-immunohistochemistry (IHC) standardization with D5F3 antibody in non-small cell lung carcinoma (NSCLC): An international consensus study.

2013· article· en· W2603873395 on OpenAlexaff
Fred R. Hirsch, Yasushi Yatabe, Manfred Dietel, Lynette M. Sholl, Ming‐Sound Tsao, Ed Schuuring, Raymond R. Tubbs

Bibliographic record

VenueJournal of Clinical Oncology · 2013
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsCrizotinibMedicineImmunohistochemistryInternal medicineFish <Actinopterygii>Lung cancerOncologyPathologyBiology

Abstract

fetched live from OpenAlex

e22042 Background: The outcome of patients with advanced NSCLC with ALK fusions detected by ALK FISH has improved significantly when treated with crizotinib. ALK IHC*, which is a relatively inexpensive assay, correlates well with ALK FISH. An international ALK IHC project was initiated to formulate scoring standardization and assess reproducibility of an ALK IHC assay. Methods: Using ALK FISH status (Abbott, Des Plaines, IL) as the enrollment criteria, formalin-fixed paraffin-embedded tumors from 103 NSCLC patients from 6 different institutes were stained and analyzed for ALK protein expression using a recently developed fully automated ALK IHC assay (Ventana, Tucson, AZ). Seven international observers blindly assessed the specimens as “positive” or “negative” after two training sessions and the use of an assessment manual. Results: The agreement between ALK IHC and ALK FISH for evaluable cases where 4/7 or 6/7 readers agreed on ALK status was 92/98 cases (93.9%, 95%CI 87.3-97.2) and 90/96 cases (93.8%, 95%CI 87.0-97.1) overall; positive IHC agreement was 39/43 cases (90.7%, 95%CI 78.4-96.3) for both methods; negative IHC agreement was 53/55 cases (96.4%, 95%CI 87.7-99.0) and 51/53 cases (96.2%, 95%CI 87.2-99.0), respectively. Average inter-observer agreement was 1987/2032 reads (97.8%, 95%CI 95.9-99.1) overall; average positive agreement was 1,710/1,755 reads (97.4%, 95%CI 95.0-99.1); average negative agreement was 2,264/2,309 reads (98.1%, 95%CI 96.4-99.3). Of the 6 discrepant cases, 4 were unanimously scored as ALK IHC negative with ALK FISH being positive. Two were confirmed by chromogenic ISH to be ALK rearranged, one was unevaluable, and one was genomically heterogeneous. The remaining 2 discrepant cases were discordant among scorers relating to ALK IHC cellular compartment staining in one case and a minute sample size showing ALK IHC staining in the other. Conclusions: ALK IHC standardized assessment achieved high inter-observer reproducibility among an international panel of participants and high correlation with ALK FISH. A screening strategy using ALK IHC should be considered.*ALK IHC has not been approved for use in the US as a diagnostic for crizotinib.

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 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)0.129
metaresearch head score (Gemma)0.047
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: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.129
Threshold uncertainty score0.683

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1290.047
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.003
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0040.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.036
GPT teacher head0.464
Teacher spread0.427 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

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
Published2013
Admission routes1
Has abstractyes

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