Optimizing Biologic Sequencing in Metastatic Colorectal Cancer: First Line and Beyond
Bibliographic record
Abstract
Significant advances in the treatment of metastatic colorectal cancer (mcrc) since the early 2000s have led to improved clinical outcomes, including overall survival (os). When fluorouracil was the sole treatment agent for mcrc, os in phase iii studies was approximately 12 months. Now, in 2019, the median os (mos) in the most recent mcrc clinical trials has been approaching 3 years. The biologic agents that target the vascular endothelial growth factor (vegf), epithelial growth factor receptor (egfr), human epidermal growth factor receptor 2 (her2), PD-1, ctla-4, ntrk, and braf pathways play important roles in the mcrc treatment algorithm, given their significant-sometimes dramatic-activity. Emerging data indicate that the choice of a specific biologic at a particular time (line of treatment) for specific patient populations (based on tumour characteristics) is critical. In the present review, we discuss the available evidence for optimal biologic sequencing in the management of mcrc.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".