What Is a Clinically Meaningful Survival Benefit in Refractory Metastatic Colorectal Cancer?
Bibliographic record
Abstract
Assessment of the clinical benefit of cancer treatments can be highly subjective, influenced by both perspective and context. Such assessments are required in regulatory and policy decision-making, but consistency between jurisdictions is often lacking. Clear and consistent standards for determining when a treatment offers a meaningful benefit, relative to the current standard of care, can help to address issues of equity and transparency in health technology assessment. For metastatic colorectal cancer (mcrc), no standardized Canadian definition of clinically meaningful benefit has yet been proposed. Colorectal Cancer Canada therefore convened a group of medical oncologists expert in colorectal cancer to review the literature about clinical significance. The resulting consensus is intended to apply to any therapeutic agent being considered in the setting of chemotherapy-refractory mcrc. It was agreed that overall survival is the appropriate measure of clinical efficacy in chemorefractory mcrc. As quantitative targets for efficacy, an improvement of 2 months or more in median overall survival or a hazard ratio for survival of 0.75 or lower (or both) are proposed as the threshold for clinically meaningful benefit. That threshold could be influenced by a treatment's effect on quality of life. Treatment toxicity is also relevant to the assessment of clinical benefit in this setting, specifically when significant differences in treatment tolerability are evident.
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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 | 0.040 | 0.088 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| 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".