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Association of tumor volume and outcomes in T3 larynx cancer with organ preservation approach.

2021· article· en· W3167185898 on OpenAlexaff
Nauman Malik, Nicolin Hainc, Gia Gill, Steven C. Nakoneshny, Paul Kerr, Wayne Matthews, Adam Globerman, Joseph C. Dort, Pejman Maralani, Eugene Yu, John T. Lysack, Ali Hosni, Irene Karam, Antoine Eskander

Bibliographic record

VenueJournal of Clinical Oncology · 2021
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsHealth Sciences CentreUniversity of CalgarySunnybrook Health Science CentrePrincess Margaret Cancer CentreUniversity of ManitobaUniversity of Toronto
Fundersnot available
KeywordsMedicineLarynxLaryngectomyRadiation therapyCancerGlottisProportional hazards modelRetrospective cohort studyCohortClinical endpointPrimary tumorOncologySurgeryInternal medicineClinical trialMetastasis

Abstract

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e18044 Background: Organ preservation approaches to treatment of locally advanced larynx cancers are widely used and consist of radiotherapy (RT) with or without concurrent systemic therapy (CRT). Analyses of the National Cancer Database point to decreasing survival as CRT became widely adopted in place of total laryngectomy (TL). Tumor volume in T3 laryngeal tumors has been postulated as one variable to explain this finding, with higher volume associated with lower local control based on small sample size studies largely in pre-intensity modulated radiotherapy (IMRT) era, and low volume T3 tumors being associated with improved local control with CRT. We sought to validate these findings in a contemporary cohort of T3 larynx patients treated with IMRT. Methods: This was a national, multicentre retrospective cohort study of patients diagnosed with American Joint Committee on Cancer (AJCC) T3 N0-3 M0 glottic and supraglottic cancers who underwent curative intent IMRT with or without systemic treatment from 2002-2018. Tumor volumes were calculated using a validated standardized approach by a Neuroradiologist. Primary predictor was tumor volume, primary outcome was local control (LC), and secondary outcomes included overall survival (OS), as well as late grade 3+ toxicities. Kaplan Meier estimates and log-rank tests were used for survival analyses, with Cox proportional hazards used for univariable analyses. Results: 246 patients met inclusion criteria, 147 glottic and 99 supraglottic cancers. At baseline, glottic patients were more likely to be male (p < 0.01), have a fixed vocal cord (p < 0.01), not have pre-epiglottic space invasion ( < 0.01), be cN0 (p < 0.01), and have lower grade tumors (p < 0.01). Mean tumor volumes for glottic and supraglottic tumors were 5.0 (4.2-5.8) cc and 13.0 (10.3–15.6) cc respectively. Univariable analysis showed systemic therapy was associated with improved local failure (HR 0.49, 95%CI 0.24 – 0.99, p = 0.05). Within the glottic cohort, tumor volume was not associated with local failure (HR 1.09, 95%CI 0.71 – 1.67, p = 0.38), however having a local failure event was associated with increased feeding tube dependence (HR 2.52, 95%CI 1.05 – 6.02, p = 0.04). Median local failure free survival in the overall cohort was 28.5 months, with median OS 23.2 months. There was a trend towards improved local control in the supraglottic cohort compared to glottic patients (log-rank p = 0.08), but the supraglottic cohort had significantly worse overall survival (log-rank p = 0.02). Conclusions: In this retrospective cohort study, there were baseline and outcome differences between patients with T3 glottic and supraglottic larynx cancer, with worse overall survival in supraglottic patients. Tumor volume was not associated with local control in the glottic cohort. These findings are pending further validation in a larger cohort and will be analyzed separately for supraglottic tumors.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.100
GPT teacher head0.452
Teacher spread0.351 · 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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Citations0
Published2021
Admission routes1
Has abstractyes

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