Clinical Outcomes of Curative Intent Radiotherapy by Helical Tomotherapy for Laryngeal Squamous Cell Carcinoma: A Retrospective Analysis in a Tertiary Referral Center
Bibliographic record
Abstract
Background: The management of laryngeal cancer involves balancing curative treatment with preserving essential functions. This study aimed to evaluate the clinical outcomes of helical tomotherapy, an advanced form of radiation therapy, as a primary treatment modality for laryngeal squamous cell carcinoma (LSCC). Methods: A retrospective analysis of data obtained from a tertiary referral center was performed to assess treatment response rates, survival outcomes, disease control, and treatment-related adverse events. Results: The study included 45 patients with LSCC treated with helical tomotherapy between May 2015 and September 2022. The 5-year overall survival (OS) rate and disease-free survival (DFS) rate were 89.2% and 71.1%, respectively. Local control and laryngeal preservation rates at 5 years were 79.7% and 84.7%, respectively. Subgroup analysis revealed higher DFS rates in early-stage patients (84.2%) compared to advanced-stage patients (58.9%). Conclusions: The results indicate that helical tomotherapy offers effective tumor control and potential for laryngeal preservation in LSCC. Further prospective studies and longer follow-up are needed to validate these findings and optimize treatment strategies for LSCC patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".