Defining the Prognostic Significance of BRAF V600E in Early-Stage Colon Cancer: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: BRAF mutations are found in 10% of colon cancers (CCs) and are associated with poor prognosis in metastatic disease. BRAF V600E predicts sensitivity to cetuximab + encorafenib in the metastatic setting. With new trials testing encorafenib-containing regimens for early-stage CC, we sought to characterize the clinical outcomes of early-stage BRAF V600E CC. METHODS: We performed a systematic review and meta-analysis. Key inclusion criteria were a diagnosis of stage 2/3 BRAF V600E CC. Co-primary endpoints were overall survival (OS) and recurrence/disease-free survival (DFS). Meta-analysis was performed with a random-effects model incorporating sample size, hazard ratio (HR), and 95% confidence intervals (CIs). RESULTS: A total of 206 studies underwent full-text review. Of these, six randomized controlled trials were included, comprising 6836 and 843 patients with wild-type (WT) and BRAF V600E, respectively. BRAF V600E was associated with inferior OS (HR 1.49, CI 1.21-1.75) and DFS (HR 1.17, CI 1.03-1.33). This finding remains in patients with microsatellite instability-low/stable or proficient mismatch repair (OS: HR 1.66, CI 1.36-2.02, DFS: HR 1.45, CI 1.22-1.72). CONCLUSIONS: BRAF V600E is associated with inferior prognoses compared to BRAF WT in early-stage CC. This finding will help optimize trial design for this 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 | 0.013 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.034 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".