Dual-agent immunotherapy for prevention of melanoma brain metastases: A real-world analysis of 8686 patients.
Bibliographic record
Abstract
2022 Background: Melanoma brain metastases (MBM) are a common endpoint among patients with advanced melanoma and prognosis is poor. Strategies for MBM prevention can prolong life and reduce morbidity. Dual agent immunotherapy (dIT) has been paradigm-changing in management malignant melanoma management. Recent clinical trials have supported the role of dIT for upfront management of small, asymptomatic MBM. Yet, its potential role in extending brain metastasis-free survival (BMFS) and decreasing MBM incidence overall has not been explored. The objective was to compare MBM incidence, median overall survival (OS), and BMFS in melanoma patients treated with dIT versus single immunotherapy (sIT). Methods: A real-world deidentified database collating clinical information from 92 organizations (TriNetX, Inc.) was queried. Melanoma patients without brain metastases prior to immunotherapy were stratified by treatment (anti-CTLA4 [sIT] and combination anti-CTLA4/ anti-PD1 [dIT]) and propensity-score matched. MBM incidence was measured within 5 years post-IT initiation. A complementary single-institution retrospective cohort study analyzed melanoma patients treated from 2012-2019. Median OS and BMFS were compared via log-rank tests and multivariate Cox proportional-hazards models. A competing risk analysis was performed to measure the cumulative incidences of MBM and death without MBM. Results: TriNetX identified 8,686 melanoma patients who received immunotherapy (4,585 dIT; 4,101 sIT). MBM incidence was 13.4%, and 19.3%, for the dIT and sIT cohorts, respectively (p < 0.0001). DIT was associated with a lower likelihood of developing MBM compared to sIT (RR [95%CI], 0.69 [0.62-0.77]). After propensity-score matching on demographics and comorbidities, MBM incidence was similarly 13.3% and 18.5% for the dIT and sIT cohorts, respectively. On single-institution analysis, 130 melanoma patients were included (87 dIT; 43 sIT with anti-CTLA4). In patients with stage IV disease, median OS was 1.70 and 3.66 years for the sIT and dIT cohorts, respectively (p=0.6). Median BMFS was 1.56 and 2.36 years in the sIT and dIT cohorts respectively (p=0.76). On multivariable Cox proportional hazard regression analysis, NRAS mutation was significantly correlated with a worse prognosis for BMFS. Conclusions: These data highlight the impact of combination anti-CTL4/ anti-PD1 immunotherapy in decreasing MBM incidence. The potential primary prophylactic role of dIT in MBM warrants prospective exploration, including mechanistic understanding.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".