Real-world evaluation of treatment patterns and clinical outcomes in patients with BRAF-V600E metastatic colorectal cancer (mCRC) in Canada
Bibliographic record
Abstract
BACKGROUND: BRAF V600E mutations are identified in 10 % of metastatic colorectal cancer (mCRC) cases. In this project, we evaluated the clinicopathologic features and natural history of patients with BRAF mutant (BRAF-mt) mCRC prior to era of BRAF targeted therapy. METHODS: This is a retrospective project evaluating patients with diagnosed with mCRC with an identified BRAF V600E mutation between January 1, 2015 and December 31, 2021 seen at the Ottawa Hospital Cancer Centre prior to the approval of cetuximab and encorafenib in Canada. Demographic, clinical, and cancer characteristics were collected from the medical records. Outcomes of interest included overall survival (OS) and time to next therapy (TNT). RESULTS: 71 patients were included. The median age was 69 years, 37 (52 %) patients were females, and 19 (27 %) were mismatch repair deficient (dMMR). Median OS was 12.9 months with 21 (30 %) patients living greater than 2-years. Signet ring histology (HR=7.27, p < 0.001), peritoneal metastasis (HR=2.29, 0.003), distant lymphatic metastasis (HR=2.70, p < 0.001), brain metastasis (HR=2.86, p < 0.048) and metastatectomy (HR=0.17, p < 0.001) were associated with OS. Forty-six (65 %) patients received first-line systemic therapy, 14 (20 %) second-line and 2 (3 %) third-line. Median duration of therapy was 8.5 months for first-line, 5.5 months for second-line and 1.5 months for third-line. CONCLUSION: Real world data demonstrates that patients with BRAF-V600E mCRC have poor clinical outcomes with traditional systemic therapies. Only a minority of patients received second- or third-line systemic treatments, highlighting the importance of ongoing research evaluating incorporation of targeted therapy in first-line treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".