Patterns of Practice with Third-Line Anti-EGFR Antibody for Metastatic Colorectal Cancer
Bibliographic record
Abstract
Background: Therapy with anti-epidermal growth factor receptor (EGFR) monoclonal antibody improves outcomes for patients with metastatic colorectal cancer (MCRC) in the first-, second-, and third-line trial settings. In British Columbia, the use of EGFR inhibitors (EGFRIS) is confined to third-line therapy, which might lower the proportion of patients who receive this therapy. The objective of the present study was to describe EGFRI treatment patterns when those agents are limited to the third-line setting. The results will inform decisions about optimal use of EGFRI agents, including earlier in the course of therapy for metastatic disease. Methods: All patients with newly diagnosed mcrc who were referred to BC Cancer Agency clinics in 2009 were included in the study. Prognostic and treatment information was prospectively collected; KRAS test results were determined by chart review. Results: The study included 443 patients with a median age of 66 years. For the 321 patients who received systemic therapy, median survival was 22.3 months. Of the 117 patients who were treated with 5-fluorouracil, oxaliplatin, and irinotecan, and who were potentially eligible for egfri therapy, 90% (105 patients) were tested for KRAS status. Of the 60 patients with KRAS wild-type tumours, 82% (49 patients) received egfri therapy. Conclusions: When EGFRI therapy is limited to the third-line setting, only a small proportion of patients receive such therapy, with death and poor performance status preventing its use in the rest. Availability of EGFRI in earlier lines of therapy could increase the proportion of patients treated with all active systemic agents.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".