A Retrospective Observational Study to Estimate the Attrition of Patients across Lines of Systemic Treatment for Metastatic Colorectal Cancer in Canada
Bibliographic record
Abstract
Background: Selection and sequencing of treatment regimens for individual patients with metastatic colorectal cancer (mcrc) is driven by maintaining reasonable quality of life and extending survival, as well as by access to and cost of therapies. The objectives of the present study were to describe, for patients with mcrc, attrition across lines of systemic therapy, patterns of therapy and their timing, and KRAS status. Methods: A retrospective chart review at 6 Canadian academic centres included sequential patients who were diagnosed with mcrc from 1 January 2009 onward and who initiated first-line systemic treatment for mcrc between 1 January and 31 December 2009. Death was included as a competing risk in the analysis. Results: The analysis included 200 patients who started first-line therapy. The proportions of patients who started second-, third-, and fourth-line systemic therapy were 70%, 30%, and 15% respectively. Chemotherapy plus bevacizumab was the most common first-line combination (66%). The most common first-line regimen was folfiri plus bevacizumab. KRAS testing was performed in 103 patients (52%), and 38 of 68 patients (56%, 19% overall) with confirmed KRAS wild-type tumours received an epidermal growth factor receptor inhibitor (egfri), which was more common in later lines. Most KRAS testing occurred after initiation of second-line therapy. Conclusions: In the modern treatment era, a high proportion of patients receive at least two lines of therapy for mcrc, but only 19% receive egfri therapy. Earlier KRAS testing and therapy with an egfri might allow a greater proportion of patients to access all 5 active treatment 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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".