Total Mucosal Irradiation with Intensity-modulated Radiotherapy in Patients with Head and Neck Carcinoma of Unknown Primary: A Pooled Analysis of Two Prospective Studies
Bibliographic record
Abstract
AIMS: To determine the clinical outcomes of an intensity-modulated radiotherapy technique for total mucosal irradiation (TM-IMRT) in patients with head and neck carcinoma of unknown primary (HNCUP). MATERIALS AND METHODS: A single-centre prospective phase II trial design was used in two sequential studies to evaluate TM-IMRT for HNCUP. Patients were investigated for primary tumour site using examination under anaesthetic and biopsies, computed tomography ± magnetic resonance imaging (MRI) or 18-fluorodeoxyglucose positron emission tomography-computed tomography (PET-CT). Patients received IMRT to the potential primary tumour sites and elective cervical nodes. Concomitant chemotherapy was used in patients who received primary radiotherapy or those with nodal extracapsular extension. RESULTS: Thirty-six patients with HNCUP were recruited; 72% male. Twenty-five patients (69.4%) had p16-positive disease. Two year mucosal and local nodal control rates were 97.1% (95% confidence interval 91.4-100) and 89.8% (78.4-100), respectively. One mucosal primary was detected 7.3 months after TM-IMRT and three patients died from recurrent/metastatic squamous cell carcinoma of the head and neck. Twelve patients (33%) developed grade 3 (Late Effects in Normal Tissue-Subjective, Objective, Management and Analytical; LENT-SOMA) dysphagia with a 1 year enteric tube feeding rate of 2.7%. The high-grade subjective xerostomia rate (LENT-SOMA) at 24 months after IMRT was 15%. CONCLUSIONS: At a median follow-up of 36.1 months, the use of TM-IMRT was associated with good local control. Toxicity was comparable with previously reported TM-IMRT regimens encompassing similar mucosal volumes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".