The relationship between the development of rash and clinical and quality of life outcomes by Kras mutation status in patients with colorectal cancer treated with cetuximab in NCIC CTG CO.17.
Bibliographic record
Abstract
481 Background: The NCIC Clinical Trials Group CO.17 trial, conducted with the Australasian Gastrointestinal Trials Group, showed cetuximab monotherapy (CET vs. best supportive care [BSC]) improved overall (OS) and progression-free survival (PFS) and maintained quality of life (QoL) in patients previously treated for advanced colorectal cancer. Correlative analyses showed strong relationships between CET benefits and both rash development and Kras mutation status. Association between rash and CET benefits is now presented by Kras mutation status. Methods: Rash was graded weekly by NCI CTC 2.0 criteria. Landmark-type analyses (LTA) were performed by excluding patients who died within 28 days and then grouping by rash severity (gr 2+ vs. gr 0/1) based both on worst grade ever developed (LTA1) and worst grade on or before day 28 (LTA2). Multivariate Cox models were conducted separately for wild-type (WT) and mutated (MUT) Kras tumors. Results: More rash of severity gr 2+ was observed in WT than MUT patients treated with CET (57.3% vs. 44.4%; p = 0.08). The median OS, PFS, and HRs from LTA2 are presented for WT and MUT groups (see Table). Conclusions: Rash severity was positively correlated with PFS and OS in Kras WT patients who received CET, although only for gr 2+ rash did OS significantly exceed that of BSC patients. In Kras MUT patients, neither gr 0/1 nor gr 2+ rash was associated with either improved PFS or OS vs. BSC patients. Quality of life outcomes will also be reported by Kras mutation status. [Table: see text] [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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".