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Record W4403299677 · doi:10.1001/jamaoncol.2024.4354

Ninth Version of the AJCC and UICC Nasopharyngeal Cancer TNM Staging Classification

2024· article· en· W4403299677 on OpenAlexaff
Hai‐Qiang Mai, Wai Tong Ng, Chaosu Hu, Jingao Li, Xiaozhong Chen, James Chung Hang Chow, E. Wong, Victor Lee, Ling-Yu Ma, Qiaojuan Guo, Qin Liu, Lizhi Liu, Tingting Xu, Xiaochang Gong, Meng‐Yun Qiang, Kwok‐Hung Au, Tsz-Chim Liu, Chi‐Leung Chiang, Youping Xiao, Shao-Jun Lin, Yunbin Chen, Shanshan Guo, Charlene H. L. Wong, Lin-Quan Tang, Zhiyuan Xu, Yizhen Jia, Wen-Sa Peng, Liping Hu, Tianzhu Lu, Jiang Feng, Caineng Cao, Wei Xu, Jun Ma, Pierre Blanchard, Michelle Williams, Christine M. Glastonbury, Ann D. King, Snehal G. Patel, Raja R. Seethala, A. Dimitrios Colevas, Daiming Fan, Melvin L.K. Chua, Shao Hui Huang, Brian O’Sullivan, William M. Lydiatt, Anne W.M. Lee

Bibliographic record

VenueJAMA Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsPrincess Margaret Cancer Centre
FundersNational Cancer Institute
KeywordsMedicineNasopharyngeal carcinomaCancerStage (stratigraphy)AJCC staging systemCancer stagingInternal medicineOncologyRadiation therapyStaging system

Abstract

fetched live from OpenAlex

Importance: Accurate staging is a fundamental step in treating patients with nasopharyngeal carcinoma (NPC) worldwide; this is crucial not only for prognostication, but also for guiding treatment decisions. The American Joint Committee on Cancer (AJCC)/Union for International Cancer Control (UICC) tumor-node-metastasis (TNM) system is the global language for clinicians, researchers, and cancer registries. Continual improvement that aligns with contemporary pattern of care is essential. Objective: To improve the prognostic accuracy and clinical applicability of the eighth edition (TNM-8) for NPC. Design, Setting, and Participants: This multicenter study analyzed patients with NPC with detailed tumor features during January 2014 and December 2015 and was reviewed by experienced radiologists. The data analysis was completed in December 2023. The findings were further confirmed with internal and external validation. Statistical analyses and clinical considerations were reviewed by the AJCC/UICC multidisciplinary head and neck panels and attained consensus. The recommendations were evaluated by the AJCC Evidence-Based Medicine Committee before final endorsement as the ninth version (TNM-9). Main Outcomes and Measures: The primary end point was overall survival. Adjusted hazard ratios of different subgroups were then assessed for confirmation of optimal stage grouping. Results: Of the 4914 patients analyzed, 1264 (25.7%) were female and 3650 (74.3%) were male; the median (SD) age was 48.1 (12.0) years. Advanced radiological extranodal extension (with involvement of adjacent muscles, skin, and/or neurovascular bundles) was identified as an independent adverse factor for all end points: this was added as a criterion for N3. Patients with nonmetastatic disease were regrouped into stages I to III instead of TNM-8 stages I to IVA. Significant hazard discrimination was achieved by grouping T1-2N0-1 as stage I, T3/N2 as stage II, and T4/N3 as stage III. Although the T1-2N0-1 subgroups had comparable 5-year overall survival, subdivisions into IA (T1-T2N0) and IB (T1-T2N1) were recommended due to the distinction in adjusted hazard ratios following adjustment for chemotherapy use. Metastatic disease was exclusively classified as stage IV, and prognostication was further refined by subdivision into IVA (M1a, ≤3 lesions) and IVB (M1b, >3 lesions). TNM-9 demonstrated superiority compared with TNM-8 in major statistical aspects. Conclusion and Relevance: The results of this diagnostic study suggest that the ninth version of TNM staging for NPC, based on robust analyses and a comprehensive review by the AJCC/UICC staging committees, provides an improved staging system for global application and a framework for future incorporation of nonanatomical factors. This will be launched for global application in January 2025.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.676
Threshold uncertainty score0.150

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.035
GPT teacher head0.361
Teacher spread0.326 · 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

Citations102
Published2024
Admission routes1
Has abstractyes

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