Impact of systemic therapy sequencing on overall survival for patients with advanced BRAF-mutated melanoma.
Bibliographic record
Abstract
9552 Background: Both immune checkpoint inhibitors (ICI) and BRAF targeted therapy (TT) are effective treatments for patients with advanced BRAF-mutated melanoma. However, the choice of first-line (1L) therapy is at the discretion of treating oncologists without clear guidance from current available data or established guidelines. Utilizing prospectively collected data from the Canadian Melanoma Research Network (CMRN) database, we provide real-world evidence to highlight the impact of sequencing these therapies. Methods: Prospective data from 9 cancer centres in Canada was retrieved from the CMRN database for patients with unresectable/metastatic melanoma, with BRAF targetable subtypes, who received at least one-cycle of 1L palliative-intent ICI or TT, and at least 1-year of follow-up. We categorized patients into 2 groups: 1L BRAF±MEK inhibitors with/without subsequent PD-1±CTLA-4 inhibitors (1L-TT), or vice versa (1L-ICI). The primary study outcome was overall survival (OS). Survival outcomes were analyzed through Kaplan-Meier methods, and multivariable Cox analysis was utilized to account for potential confounders. Results: Our study (N=235) included 152 and 83 patients in 1L-TT and 1L-ICI groups, respectively. Combined BRAF-MEK inhibitors accounted for 59% of the 1L-TT group, whereas single-agent IO accounted for 66% of the 1L-ICI group. There were 93 patients who received second-line (2L) therapy, with a non-significant trend of 1L-TT group receiving more 2L therapy compared to 1L-ICI group (65% vs. 43%, P=0.404). Neither treatment group showed significant differences in median time on 1L therapy (P=0.645) or 2L therapy (P=0.686). The 1L-ICI group was associated with a favourable median overall survival (OS) compared to 1L-TT group (19.3 vs. 10.0 months, P=0.031). Specifically, the ICI only group had the highest median OS, followed by TT-ICI sequence, ICI-TT sequence, and TT only groups respectively (not reached vs. 38.3 vs. 16.9 vs. 6.1 months, P<0.001). However, this OS benefit (HR 0.89, 95% 0.51-1.53, P=0.644) was non-significant upon controlling for confounders such as baseline metastatic sites >2 (HR 2.07, 95%CI 1.24-3.46, P=0.006) and ECOG ≥2 (HR 3.47, 95%CI 2.02-5.97, P<0.001) in multivariable Cox analysis. Conclusions: There was no significant difference in OS between 1L-TT and 1L-IO groups. Rather, OS is driven mostly by the patient’s clinical status and tumour-associated features. Our study provides real-world evidence in an understudied area. Further studies are needed to validate our findings to inform guideline development.[Table: see text]
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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) | 0.000 | 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".