Metastatic tracheal melanoma misdiagnosed as chronic obstructive pulmonary disease: A case report
Bibliographic record
Abstract
Introduction/objectives: Metastatic tracheal melanoma is rare, with fewer than 20 reported cases. This case describes a 62-year-old female with a history of cutaneous melanoma excised 10 years prior, initially misdiagnosed with severe COPD. We highlight the diagnostic challenges when rare metastases mimic common conditions. Description: Diagnosed with COPD based on dyspnoea and spirometry, the patient later developed worsening symptoms, including haemoptysis, requiring hospitalisation. A chest radiograph was unremarkable, but CT pulmonary angiogram revealed a 1.6 × 1.3 cm tracheal mass. Bronchoscopy confirmed 80-90 % luminal stenosis due to a friable mass, which biopsy identified as tracheal melanoma (BRAF V600E positive). She underwent tumor debulking via rigid bronchoscopy, followed by radiation therapy and vemurafenib. Discussion: This case represents the longest interval between cutaneous melanoma and tracheal metastasis. Spirometry showed a COPD-like scooping pattern rather than the expected large airway obstruction, delaying diagnosis. New-onset severe airflow obstruction in patients with minimal smoking history should prompt alternative considerations. Advanced imaging and bronchoscopy are essential for early detection. Treatment includes surgical debulking, radiation, and targeted therapy, with follow-up showing symptom resolution and normalised spirometry. Conclusion: Metastatic tracheal melanoma can mimic COPD, leading to misdiagnosis. The prolonged latency highlights the need for vigilance in melanoma follow-up. Rare airway lesions should be considered in atypical COPD presentations, reinforcing the importance of advanced diagnostic tools for timely identification and treatment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".