Avaliação da sobrevida livre de doença de pacientes com recidiva loco-regional de carcinoma epidermóide de cavidade bucal e orofaringe submetidos a tratamento de resgate
Bibliographic record
Abstract
OBJECTIVE: Salvage surgery is the first therapeutic option for recurrent tumors of the mouth and oropharynx, mainly in early stage tumors. This study intends to evaluate the disease free survival interval after salvage treatment for recurrent tumors of the mouth and oropharynx. METHODS: Retrospective analysis of 276 patients with squamous cell carcinoma of the mouth and oropharynx treated with surgery. One hundred and twenty seven patients developed loco-regional recurrence. Ninety-seven were staged as early tumors and 178 as advanced ones. The tumor site was the lip in 25 cases, oral cavity in 173 and oropharynx in 78. Postoperative radiotherapy was indicated in 121 cases with a mean dose of 60.8Gy. RESULTS: Eighty-nine patients underwent salvage treatment (surgery in 76 patients). Loco-regional recurrences were treated with salvage surgery in 65% of cases. Disease free survival after salvage surgery was 13% in cases with recurrences diagnosed up to 6 months and 48% in those who recurred after 12 months of follow-up (p=0.0009). Modality of salvage treatment and the disease free interval were independent variables of survival in the multivariate analysis. CONCLUSION: In cases clinically staged as I and II, the disease free survival in five years after salvage treatment was 70%.
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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 | 0.000 |
| 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) | 0.002 | 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".