A retrospective study of head and neck re-irradiation for patients with recurrent or second primary head and neck cancer: The McGill University experience
Bibliographic record
Abstract
BACKGROUND: We report our experience with patients who received re-irradiation to the head and neck area for locoregional recurrences (LRR) or second primaries (SP) in a previously irradiated field. METHODS: We reviewed 27 consecutive patients with a diagnosis of LRR or SP head and neck carcinoma treated with a second course of radiotherapy between April 2004 and July 2012. The main outcome measures were local control, overall survival, and complications. The results are expressed as actuarial values using the Kaplan-Meier estimates. RESULTS: The median follow-up time was 24.7 months (range: 11 days-79.3 months). There were 23 males and four females with a median age of 61 years (range: 40-87 years). The actuarial overall survival rates at 1, 2, and 5 years were 77, 59, and 57%, respectively. The actuarial local control rate was 80, 52, and 52% at 1, 2, and 5 years, respectively. Three patients developed systemic metastases. The rate of grade 3 toxicity was 26%, and that of grade 4 toxicity was 3%. There were two treatment-related deaths (grade 5 toxicity). CONCLUSIONS: Continuous course re-irradiation in patients with LRR or SP head and neck cancer is feasible with acceptable toxicity. With current encouraging rates of local control and overall survival, this option should be discussed with patients who have few alternative therapeutic options.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".