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Record W4411413397 · doi:10.1001/jamaoto.2025.1721

Adjuvant Chemoradiotherapy for Oral Cavity SCC With Minor and Major Extranodal Extension

2025· article· en· W4411413397 on OpenAlexaffabout
Mirko Manojlovic‐Kolarski, Susie Su, Ilan Weinreb, Robert Calvisi, Bayardo Perez‐Ordoñez, Stephen J. Smith, Snehal G. Patel, Cristina Valero, Bin Xu, Ronald Ghossein, Nora Katabi, Jonathan R. Clark, Tsu‐Hui Low, Ruta Gupta, Joel Davies, Mary S. Richardson, David Goldstein, Shao Hui Huang, Brian O’Sullivan, Wei Xu, Aaron R. Hansen, John R. de Almeida

Bibliographic record

VenueJAMA Otolaryngology–Head & Neck Surgery · 2025
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsPublic Health OntarioUniversity of TorontoHealth Sciences NorthUniversity Health Network
FundersNational Cancer Institute
KeywordsMedicineChemoradiotherapyHazard ratioInternal medicineRadiation therapySubgroup analysisAdjuvantOncologySurgeryRetrospective cohort studyAdjuvant therapyCohort studyChemotherapyMeta-analysisConfidence interval

Abstract

fetched live from OpenAlex

Importance: Extranodal extension (ENE) in oral cavity squamous cell carcinoma (OSCC) is a poor prognostic feature and an indication for adjuvant chemoradiotherapy. ENE is stratified into minor (≤2 mm) or major (>2 mm) extent. The role of adjuvant chemoradiotherapy, particularly for the minor ENE subgroup, is unclear. Objective: To determine the impact of adjuvant chemoradiotherapy on oncological outcomes depending on the extent of ENE. Design, Setting, and Participants: This retrospective, multicenter cohort study was conducted across 4 high-volume head and neck surgery centers in Australia, the US, and Canada. The study included patients with surgically resected OSCC with pathologic positive nodal disease treated between 2005 and 2018. Statistical analysis took place between 2022 and 2025; final follow-up was in 2022. Exposures: Extent of ENE was restaged on archived tissue. Adjuvant radiotherapy or chemoradiotherapy was recommended per standard guidelines. Outcomes: Univariable and multivariable analysis were used to assess the effect of chemotherapy for the entire group and for propensity score-matched cohorts on locoregional control (LRC), disease-free survival (DFS), and overall survival (OS) stratified by minor vs major ENE. Results: A total of 755 patients (mean [SD] age, 61.7 [12.9] years; 36% female) were included in the study: 126 (17%) with minor ENE and 243 (32%) with major ENE. A total of 50 (39.7%) patients with minor ENE and 116 (47.8%) with major ENE received adjuvant chemotherapy. On multivariable analysis, chemotherapy was not associated with improved LRC (hazard ratio [HR], 1.07 [95% CI, 0.49-2.32]), DFS (HR, 0.96 [95% CI, 0.56-1.66]), or OS (HR, 0.97 [95% CI, 0.55-1.73]) in patients with minor ENE. However, in patients with major ENE, chemotherapy improved DFS (HR, 0.58 [95% CI, 0.41-0.81]) and OS (HR, 0.61 [95% CI, 0.38-0.98]). In propensity score-matched cohorts, chemotherapy did not improve LRC (71% vs 75%; difference, 4% [95% CI, -18% to 26%]), DFS (56% vs 56%; difference, 0% [95% CI, -25% to 25%]), or OS (57% vs 57%; difference, 0% [95% CI, -25% to 25%]) for patients with minor ENE, but improved DFS (33% vs 11%; difference, 22% [95% CI, 5%-38%]) and OS (41% vs 15%; difference, 26% [95% CI, 8%-44%]) but not LRC (61% vs 62%; difference, 1% [95% CI, -17% to 21%]) in patients with major ENE. Conclusions: This multicenter cohort study found that in patients with OSCC, adjuvant chemotherapy is beneficial in patients with major ENE, but may not be beneficial in patients with minor ENE.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.298
Teacher spread0.275 · 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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Citations4
Published2025
Admission routes2
Has abstractyes

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