Clinical Outcomes With Dabrafenib Plus Trametinib in a Clinical Trial Versus Real-World Standard of Care in Patients With BRAF-Mutated Advanced NSCLC
Bibliographic record
Abstract
Introduction BRAF mutations are rare in patients with NSCLC, and treatment options are limited. Dabrafenib plus trametinib (dab-tram) was approved for BRAF V600 -mutated advanced NSCLC (aNSCLC), based on results from a phase 2 study (NCT01336634). This retrospective analysis compared the effectiveness of dab-tram, based on previously reported clinical trial data, versus real-world standard of care in patients with BRAF -mutated aNSCLC. Methods Real-world cohorts were derived from a deidentified real-world database (2011–2020) and included patients with BRAF -mutated aNSCLC receiving first-line platinum-based chemotherapy (PBC), first-line immune checkpoint inhibitors (ICIs) plus PBC, or second-line ICIs. Weighting by odds was used to estimate the average treatment effect of the treated. Results For first-line dab-tram versus PBC, the hazard ratio (HR; 95% confidence interval) for death in unweighted and weighted analyses was 0.65 (0.39–1.1) and 0.51 (0.29–0.92; p = 0.03), respectively; unweighted and weighted median overall survival was 17.3 (12.3–40.2) versus 14.5 (9.2–19.6) months and 17.3 (14.6-not reached) versus 9.7 (6.4–19.6) months, respectively. Hazard ratio of death in unweighted and weighted analyses was 0.56 (0.29–1.1) and 0.57 (0.28–1.17), respectively, with first-line dab-tram versus PBC plus ICI, and 0.65 (0.39–1.07) and not reported (Cox proportional-hazards assumption violated), respectively, with second-line dab-tram versus ICI. Conclusions In this indirect comparison in patients with BRAF -mutated aNSCLC, the risk of death was lower and median overall survival was longer with first-line dab-tram versus PBC. In analyses of dab-tram versus first-line PBC plus ICI or second-line ICI, sample sizes were small and findings were inconclusive with overlapping confidence intervals. Despite some limitations, the study provides useful data for this rare patient population.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".