Re-Irradiation for Recurrent Head and Neck Cancer: Freedom from Cancer Recurrence Rate
Bibliographic record
Abstract
Salvage re-irradiation (rRT) for patients with locoregionally recurrent head and neck cancer (rHNC) remains challenging. A retrospective analysis was performed on 49 patients who received rRT between 2011 and 2018. The co-primary endpoint of the study was 2-year freedom from cancer recurrence rate (FCRR) and overall survival (OS), and secondary endpoints were 2-year disease-free survival (DFS), local failure (LF), regional failure (RF), distant metastases (DM), and RTOG grade 3 ≥ late toxicities. Adjuvant and definitive rRT were delivered to 22 and 27 patients, respectively. A total of 91% of patients were managed with conventional re-RT and 71% of patients received concurrent chemotherapy. The median follow-up after rRT was 30 months. The 2-year FCRR, OS, DFS, LF, RF, and DM were 64%, 51%, 28%, 32%, 9%, and 39% respectively. MVA showed that poor performance status (PS: 1-2 vs. 0) and age > 52 years were predictive of worse OS. In comparison, poor PS (1-2 vs. 0) and total dose of rRT < 60 Gy were predictive of worse DFS. Late RTOG toxicity of grade 3 ≥ was reported in nine (18.3%) patients. FCRR at 2 years after salvage rRT for rHNC was higher than other traditional endpoints and could be an important endpoint to be included in future rRT studies. rRT for rHNC at our cohort was relatively successful, with a manageable level of late severe toxicity. Replacing this approach in other developing countries is a viable option.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".