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Record W4386571007 · doi:10.1016/j.jtho.2023.09.001

The International Association for the Study of Lung Cancer Thymic Epithelial Tumor Staging Project: A Re-Assessment of the International Thymic Malignancy Interest Group/International Association for the Study of Lung Cancer Lymph Node Map for Thymic Epithelial Tumors for the Forthcoming Ninth Edition of the TNM Classification of Malignant Tumors

2023· article· en· W4386571007 on OpenAlexafffund
Edith M. Marom, Wentao Fang, Enrico Ruffini, Frank Detterbeck, Usman Ahmad, Sarit Appel, Andrea Billè, Souheil Boubia, Cecilia Brambilla, Vanessa Cilento, Ayten Cangır, Conrad Falkson, Pier Luigi Filosso, Giuseppe Giaccone, Nicolas Girard, Emily Goren, Francesco Guerrera, James Huang, Maurizio Infante, Dong-Kwan Kim, Marco Lucchi, Mirella Marino, Andrew G. Nicholson, Meinoshin Okumura, Ramón Rami–Porta, Andreas Rimner, Charles B. Simone, Hisao Asamura

Bibliographic record

VenueJournal of Thoracic Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicMyasthenia Gravis and Thymoma
Canadian institutionsQueen's University
FundersNational Cancer InstituteYonsei University College of MedicineCollege of Medicine, Seoul National UniversityInstitut universitaire de cardiologie et de pneumologie de Québec, Université LavalCentre Hospitalier Universitaire de RennesMinistry of Health of the Russian FederationShanghai Pulmonary HospitalSzegedi TudományegyetemInstitut de Cancérologie de LorraineTokyo Women's Medical UniversityShanghai Chest HospitalInstitut Gustave-RoussyPeking UniversityUniversiteit GentKU LeuvenAstellas PharmaSamsungYonsei UniversityEisaiHealth Science Center, University of TennesseeUniversitair Ziekenhuis GentSoochow UniversityUniversiteit AntwerpenSeoul National University HospitalFudan UniversityUniversität WienUniversidade de São PauloHyogo College of MedicineSungkyunkwan UniversityBristol-Myers SquibbSemmelweis EgyetemUniversità di PisaKanazawa UniversityTechnische Universität MünchenAnkara UniversitesiChugai PharmaceuticalHospices Civils de LyonComprehensive Cancer Center, City of HopeAix-Marseille UniversitéUniversity of TorontoImperial College LondonAstraZenecaUniversity of AberdeenInternational Association for the Study of Lung CancerMount Sinai Health SystemUniversity of ChicagoYale UniversityNSW Health PathologyUniversity of North Carolina at Chapel HillHarvard UniversitySeoul National UniversityAlexion PharmaceuticalsChina Medical UniversityUniversity of LeicesterOhio State UniversityKindai UniversityMemorial Sloan-Kettering Cancer CenterVarian Medical SystemsUniversità degli Studi di PadovaCentro de Investigación Biomédica en Red de CáncerMassachusetts General HospitalPfizerUniversidad de NavarraYork UniversityUniversitätsspital ZürichMedizinische Universität WienPostgraduate Institute of Medical Education and Research, ChandigarhBrigham and Women's Hospital
KeywordsMedicineLymph nodeMalignancyStage (stratigraphy)CancerLung cancerTNM staging systemThymic carcinomaOncologyInternal medicinePathologyNeoplasm staging

Abstract

fetched live from OpenAlex

INTRODUCTION: A lymph node map is the pillar on which accurate assignment and documentation of nodal classification stands. The International Thymic Malignancy Interest Group created the first map for thymic epithelial malignancies in conjunction with the eighth edition of the TNM classification, representing the first official TNM classification of thymic epithelial malignancies. The map was based on clinical experience and published studies, but it was largely empirical because of limited available data. Dissemination of the map and implementation of a standard thymic stage classification across the world in 2017 have provided more consistent and granular data. METHODS: More than twice as many cases of node involvement are available for analysis in the current database compared with that of the eighth edition database, allowing validation of many aspects of the eighth edition map. This article details the process and considerations for refinement of the thymic map for the ninth TNM used by the Thymic Domain of the Staging and Prognostic Factors Committee of the International Association for the Study of Lung Cancer. The committee evaluated a large international collaborative data set, published anatomical and clinical studies pertaining to lymph node spread from thymic epithelial tumors, in conjunction with the analysis underlying refinements of the TNM components for the ninth edition TNM classification. RESULTS: The node map boundaries of the N1 and N2 categories remain unchanged. Visual clarifications have been added to the nomenclature of nodal stations within these regions. CONCLUSIONS: On the basis of the recommendation to keep the N component unchanged for the ninth edition TNM classification, the lymph node map remains unchanged as well; however, clarifications have been added to facilitate clinical use.

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)0.021
metaresearch head score (Gemma)0.034
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: Empirical · Consensus signal: none
Teacher disagreement score0.034
Threshold uncertainty score0.113

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.034
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.010
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0030.004
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0050.003

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 head0.041
GPT teacher head0.420
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 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".

Quick stats

Citations17
Published2023
Admission routes2
Has abstractyes

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