Primary Mucosal Melanoma of the Nasal Cavity and Paranasal Sinuses: 12 Years of Experience
Bibliographic record
Abstract
INTRODUCTION: Melanomas that arise in the nasal cavity or paranasal sinuses are rare and have a poor prognosis. In this study, we reviewed 15 patients in a tertiary referral centre and analyzed their treatment results and patterns of treatment failure. MATERIALS AND METHODS: Fifteen patients diagnosed from January 1994 to February 2005 at the Chang Gung Memorial Hospital were retrospectively reviewed. RESULTS: Eight men (53.3%) and seven (46.7%) women ranged in age from 51 to 85 years (mean 69.0 years) at the time of diagnosis. All patients presented with symptoms related to the nose. The majority of patients presented with epistaxis (93.3%). Ten patients received surgery and postoperative radiotherapy, three patients received surgery and postoperative chemo- and radiotherapy, and one patient received radiotherapy alone. The overall actuarial survival revealed that 49.5% were alive at 2 years and 33.0% were alive at 5 years. The average time from surgery to local recurrence was 5 months, the average time from surgery to the occurrence of regional recurrence was 7.45 months, and the time from surgery to the diagnosis of distant metastasis was 10.3 months. The sites of distant metastasis according to frequency are the lung, liver, bone, and brain. The average survival after the diagnosis of distant metastasis was 8 months. CONCLUSION: The prognosis of mucosal melanoma of the nasal cavity is poor in our experience. Most of the local recurrence, regional recurrence, and distant metastasis occurs in the first year after surgery. For those patients in the first year after surgery, frequent and regular follow-up is mandatory.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".