Non-classical BRAF melanoma: A retrospective review of disease characteristics and prognostic implications.
Bibliographic record
Abstract
e21060 Background: Activating mutations in the BRAF gene occur in 40-60% of melanomas with the majority of mutations resulting in V600E/K. Previous cohort studies have identified rates of non-V600E/K BRAF mutations to occur in 5-12% of patients. Despite this, there remains limited evidence characterizing the disease characteristics and outcomes of patients who harbor the non-classical BRAF mutation. Methods: Retrospective review of all melanoma patients treated at a tertiary cancer center that had BRAF mutation testing through targeted sequencing. Three groups of patients were identified and compared with respect to patient and disease characteristics: a) BRAF negative; b) BRAF V600E/K positive; c) BRAF non-V600E/K positive. Results: BRAF testing was performed in 168 melanoma patients of which 101 (60%) were BRAF negative; 55 (33%) were BRAF V600E/K positive; 12 (7%) were BRAF non-V600E/K positive (2 G466E, 1 of each G469E, K601N, K601E, L597Q, L597S, V741I, N594G, D594N, V600R and 1 with both K601N & V600E). Of these, 147 patients had baseline demographic and treatment data available for analysis. BRAF mutations were more common among males (45.6% of men vs. 22.7% of women, p = 0.03). No significant differences between other baseline patient demographics noted. Pathological characteristics revealed a non-significant trend toward poorer prognostic factors with BRAF non-V600E/K patients having increased Breslow depth (7.0 mm vs. 5.0 mm BRAF negative, 4.3 mm BRAF V600E/K) and higher rates of ulceration (71% vs. 44% BRAF negative, 30% BRAF V600E/K). BRAF non-V600E/K patients displayed a non-significant trend toward poorer overall survival (71 months vs. 215 months BRAF negative, 125 months BRAF V600E/K). Conclusions: Non-V600E/K BRAF positive patients appear to display less favorable disease characteristics and outcomes as compared to BRAF negative and BRAF V600E/K positive patients. Non-V600E/K melanoma show limited response to BRAF targeted therapy; however, evidence suggests the presence of non-classical mutations may confer susceptibility to MEK inhibition. Further characterization of non-V600E/K BRAF melanoma may allow for more refined prognostication and treatment decisions.
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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 | 0.002 | 0.002 |
| 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 | 0.001 |
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".