NCOG-02. MANAGEMENT OF PATIENTS WITH MELANOMA BRAIN METASTASES AND PRIOR SYSTEMIC TREATMENT EXPOSURE: A SINGLE-CENTER EXPERIENCE
Bibliographic record
Abstract
Abstract Although systemic therapy (ST) for melanoma patients with untreated brain metastases (BrM) has activity, ST options for patients with melanoma BrM that develop on or after ST are limited. In this single-center retrospective study, we describe the characteristics and survival outcomes of patients aged > 18 years with metastatic melanoma and who developed BrM > 90 days after their first dose of checkpoint inhibitor (CPI) or targeted therapy (TT). Relevant clinical data and data on ST prior to and after BrM diagnosis were collected. MRIs were reviewed to assess intracranial progression-free survival (IC-PFS) as per RANO-BM criteria. The primary outcome was overall survival (OS). Cox regression model was applied to identify factors associated with OS. Between 2010 and 2019, we identified 103 patients with median age 56 (29-92) years, 69 (67%) of whom were male; 57 (55%) had BRAF V600-mutant tumors. Ninety-four (91%) had no known BrM at the time of first-line therapy. Median number of BrM was 3 (1-58), median number of prior ST was 1 (1-5), 75 (73%) had prior CPI exposure and 70 (68%) were on concurrent CPI or TT at the time of BrM diagnosis. Local treatments included SRS in 43 (42%) and WBRT in 46 (44%) patients. From BrM diagnosis, median IC-PFS and OS were 3.5 (95% CI 2.6-4.3) and 6.9 (95% CI 5.2-8.6) months, respectively. Adverse prognostic factors were: BRAF wild-type (HR 2.04, 95% CI 1.15-3.64), ECOG 2-4 (HR 3.55, 95% CI 1.93-6.53), and increasing number of prior ST (HR 1.62, 95% CI 1.23-2.13). CPI therapy that was continued, started, or restarted after BrM was associated with improved median OS compared to non-ICI therapy (9.9 vs. 3.5 months, HR 0.45, 95% CI 0.27-0.74). In conclusion, our data support development of CPI-based trials for patients who experience progression with BrM on or after modern ST.
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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".