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Record W2120326191 · doi:10.1097/jto.0000000000000115

An International Interpretation Study Using the ALK IHC Antibody D5F3 and a Sensitive Detection Kit Demonstrates High Concordance between ALK IHC and ALK FISH and between Evaluators

2014· article· en· W2120326191 on OpenAlexaff
Murry W. Wynes, Lynette M. Sholl, Manfred Dietel, Ed Schuuring, Ming‐Sound Tsao, Yasushi Yatabe, Raymond R. Tubbs, Fred R. Hirsch

Bibliographic record

VenueJournal of Thoracic Oncology · 2014
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer CentreUniversity Health Network
FundersNational Cancer Institute
KeywordsAnaplastic lymphoma kinaseImmunohistochemistryMedicineConcordanceFluorescence in situ hybridizationCrizotinibLung cancerFish <Actinopterygii>PathologyCompanion diagnosticCancerOncologyInternal medicineBiologyGene

Abstract

fetched live from OpenAlex

INTRODUCTION: The goal of personalized medicine is to treat patients with a therapy predicted to be efficacious based on the molecular characteristics of the tumor, thereby sparing the patient futile or toxic therapy. Anaplastic lymphoma kinase (ALK) inhibitors are effective against ALK-positive non-small-cell lung cancer (NSCLC) tumors, but to date the only approved companion diagnostic is a break-apart fluorescence in situ hybridization (FISH) assay. Immunohistochemistry (IHC) is a clinically applicable cost-effective test that is sensitive and specific for ALK protein expression. The purpose of this study was to assemble an international team of expert pathologists to evaluate a new automated standardized ALK IHC assay. METHODS: Archival NSCLC tumor specimens (n =103) previously tested for ALK rearrangement by FISH were provided by the international collaborators. These specimens were stained by IHC with the anti-ALK (D5F3) primary antibody combined with OptiView DAB IHC detection and OptiView amplification (Ventana Medical Systems, Inc., Tucson, AZ). Specimens were scored binarily as positive if strong granular cytoplasmic brown staining was present in tumor cells. IHC results were compared with the FISH results and interevaluator comparisons made. RESULTS: Overall for the 100 evaluable cases the ALK IHC assay was highly sensitive (90%), specific (95%), and accurate relative (93%) to the ALK FISH results. Similar results were observed using a majority score. IHC negativity was scored by seven of seven and six of seven evaluators on three and two FISH-positive cases, respectively. IHC positivity was scored on two FISH-negative cases by seven of seven readers. There was agreement among seven of seven and six of seven readers on 88% and 96% of the cases before review, respectively, and after review there was agreement among seven of seven and six of seven on 95% and 97% of the cases, respectively. CONCLUSIONS: On the basis of expert evaluation the ALK IHC test is sensitive, specific, and accurate, and a majority score of multiple readers does not improve these results over an individual reader's score. Excellent inter-reader agreement was observed. These data support the algorithmic use of ALK IHC in the evaluation of NSCLC.

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)0.017
metaresearch head score (Gemma)0.020
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.002
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.023
GPT teacher head0.466
Teacher spread0.444 · 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
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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Citations161
Published2014
Admission routes1
Has abstractno

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