Treatment and outcomes of patients with metastatic colorectal cancer (mCRC) with epidermal growth factor receptor (EGFR) therapy in the third-line setting.
Bibliographic record
Abstract
579 Background: Monoclonal antibodies targeting the EGFR improve outcomes of patients with mCRC in the first-, second-, and third-line settings. The optimal treatment setting for use of these agents is not yet defined. In British Columbia, cetuximab and panitumumab are limited to patients with KRAS wild type (wt) mCRC previously treated with 5-fluorouracil (5-FU), oxaliplatin (Ox), and irinotecan (Iri). The objective of this study was to describe the treatment and outcomes of patients with mCRC after the introduction of EGFR targeted therapy in the third-line setting. Methods: All patients with newly diagnosed mCRC and referred to 1 of 5 BC Cancer Agency clinics in 2009 were included. Prognostic and treatment information was prospectively collected while KRAS testing information was determined by chart review. Results: 443 patients with a median age of 66 were included of which 59% were men, 73% received any systemic therapy for metastatic disease of which 13% underwent hepatic resection of metastatic disease. Of 117 patients who received 5-FU, Ox and Iri, 10% were not tested for KRAS. Among those tested, 38% were KRAS mutant. In patients who were KRAS wt, 23% did not receive EGFR therapy. On chart review, poor performance status was the dominant reason for not receiving KRAS testing and anti-EGFR therapy in 67% and 50% of cases, respectively. Median survival of 321 patients who received any systemic therapy for metastatic disease was 22.3 months. Conclusions: In this study, when EGFR therapy is limited to patients with KRAS wt mCRC previously treated with 5-FU, Ox and Iri, only 15% received such therapy and poor performance status was the dominant reason for non-treatment. Earlier initiation of EGFR therapy may increase the proportion of patients treated with all active systemic agents. [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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".