Brachytherapy in the retreatment of patients with new primary head and neck cancer.
Bibliographic record
Abstract
OBJECTIVE: Re-treatment for cure of the Head and Neck (H&N) region is therapeutically challenging. In this review we explore the long-term results of Ir(192) low-dose-rate (LDR) brachytherapy in the select subgroup of patients treated for a new H&N malignancy. METHODS & MATERIAL: Thirteen patients received brachytherapy between 1987-2004 for a new primary H&N cancer, six of whom had been retreated previously. Brachytherapy was given as a monotherapy in eight patients and delivered adjuvantly in five patients. Three of the thirteen patients had advanced disease at the time of diagnosis. MAIN OUTCOME MEASURES: In addition to the known prognostic factors of stage and site, intent of brachytherapy and prior re-treatment status were assessed for their influence on local control (LC) and overall survival (OS). RESULTS: Local control differed by disease stage of the new primary tumor. With a median follow-up of 50 months, mean progression-free survival was 50.2 months [95%CI = 30.1-70.4] and the 2-year rate of LC was 58%. Adjuvant brachytherapy following surgery resulted in poor LC and OS due to advanced disease at diagnosis. Prior retreatment did not appear to affect LC or OS. OS at 2 and 5 years was 69% and 38%, respectively. There were no cases of grade III toxicity. CONCLUSIONS: LDR Brachytherapy for a new primary H&N cancer is a well-tolerated retreatment alternative that results in good local control. Our results suggest that the best chance for long-term survival remains in the routine follow-up and early diagnosis of the new H&N malignancy.
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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 | 0.000 |
| Bibliometrics | 0.000 | 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".