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Record W2610732323 · doi:10.1002/cncy.21868

Consistency and reproducibility of next‐generation sequencing and other multigene mutational assays: A worldwide ring trial study on quantitative cytological molecular reference specimens

2017· article· en· W2610732323 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCancer Cytopathology · 2017
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsUniversity Health Network
FundersPublic Health Agency
KeywordsMedicineReproducibilityComputational biologyConsistency (knowledge bases)DNA sequencingMedical physicsMolecular diagnosticsBioinformaticsOncologyGeneticsBiologyDNAChromatographyArtificial intelligence

Abstract

fetched live from OpenAlex

BACKGROUND: Molecular testing of cytological lung cancer specimens includes, beyond epidermal growth factor receptor (EGFR), emerging predictive/prognostic genomic biomarkers such as Kirsten rat sarcoma viral oncogene homolog (KRAS), neuroblastoma RAS viral [v-ras] oncogene homolog (NRAS), B-Raf proto-oncogene, serine/threonine kinase (BRAF), and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit α (PIK3CA). Next-generation sequencing (NGS) and other multigene mutational assays are suitable for cytological specimens, including smears. However, the current literature reflects single-institution studies rather than multicenter experiences. METHODS: Quantitative cytological molecular reference slides were produced with cell lines designed to harbor concurrent mutations in the EGFR, KRAS, NRAS, BRAF, and PIK3CA genes at various allelic ratios, including low allele frequencies (AFs; 1%). This interlaboratory ring trial study included 14 institutions across the world that performed multigene mutational assays, from tissue extraction to data analysis, on these reference slides, with each laboratory using its own mutation analysis platform and methodology. RESULTS: All laboratories using NGS (n = 11) successfully detected the study's set of mutations with minimal variations in the means and standard errors of variant fractions at dilution points of 10% (P = .171) and 5% (P = .063) despite the use of different sequencing platforms (Illumina, Ion Torrent/Proton, and Roche). However, when mutations at a low AF of 1% were analyzed, the concordance of the NGS results was low, and this reflected the use of different thresholds for variant calling among the institutions. In contrast, laboratories using matrix-assisted laser desorption/ionization-time of flight (n = 2) showed lower concordance in terms of mutation detection and mutant AF quantification. CONCLUSIONS: Quantitative molecular reference slides are a useful tool for monitoring the performance of different multigene mutational assays, and this could lead to better standardization of molecular cytopathology procedures. Cancer Cytopathol 2017;125:615-26. © 2017 American Cancer Society.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.515
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.265
GPT teacher head0.440
Teacher spread0.175 · 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