Tumor volumes in <scp>T3</scp> supraglottic cancers treated with radiotherapy in the modern era: A study of the Canadian Head & Neck Collaborative Research Initiative
Bibliographic record
Abstract
Abstract Purpose To evaluate the association of primary tumor volume (TV) with overall survival (OS) and disease‐free survival (DFS) in T3 N0‐3M0 supraglottic cancers treated with intensity‐modulated radiotherapy (IMRT). Methods This was a retrospective cohort study involving 239 patients diagnosed with T3 N0‐3M0 supraglottic cancers between 2002 and 2018 from seven regional cancer centers in Canada. Clinical data were obtained from the patient records. Supraglottic TV was measured by neuroradiologists on diagnostic imaging. Kaplan–Meier method was used for survival probabilities, and a restricted cubic spline Cox proportional hazards regression analysis was used to analyze TV associations with OS and DFS. Results Mean (SD) of participants was 65.2 (9.4) years; 176 (73.6%) participants were male. 90 (38%) were N0, and 151 (64%) received concurrent systemic therapy. Mean TV (SD) was 11.37 (12.11) cm3. With mean follow up (SD) of 3.28 (2.60) years, 2‐year OS was 72.7% (95% CI 66.9%–78.9%) and DFS was 53.6% (47.4%–60.6%). Increasing TV was associated (per cm3 increase) with worse OS (HR, 1.01, 95% CI 1.00–1.02, p < 0.01) and DFS (HR, 1.01, 95% CI 1.00–1.02, p = 0.02). Conclusions Increasing primary tumor volume is associated with worse OS and DFS in T3 supraglottic cancers treated with IMRT, with no clear threshold. The findings suggest that patients with larger tumors and poor baseline laryngeal function may benefit from upfront laryngectomy with adjuvant radiotherapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".