Cetuximab plus irinotecan versus panitumumab in patients with refractory metastatic colorectal cancer in Ontario, Canada
Bibliographic record
Abstract
The addition of irinotecan to an epidermal growth factor receptor (EGFR) antibody has previously been shown to improve tumor response rate and time to progression but not overall survival (OS) for refractory metastatic colorectal cancer (mCRC). We assessed the "real-world" effectiveness and toxicity of the combination versus monotherapy. In Ontario, Canada, universal public funding is available for either cetuximab plus irinotecan (Cmab + I) combination therapy or panitumumab (Pmab) monotherapy, only in patients with refractory nonmutated RAS mCRC. All patients diagnosed before December 2012 and treated with an EGFR antibody for mCRC were identified from the Ontario drug database and linked to the Ontario Cancer Registry and other administrative databases to ascertain baseline characteristics, health services utilization, and outcomes. Multivariable Cox and logistic models were constructed to compare the time to treatment discontinuation (TTD), OS, emergency department (ED) or hospital visits between Cmab + I and Pmab. Observable confounders were adjusted for using propensity score methods. One thousand and eighty-one patients were identified (Cmab + I: 278, Pmab: 803). Patients receiving Cmab + I were younger (mean age 61 vs 64 years) and had a longer duration of prior irinotecan treatment. The use of Cmab + I as compared to Pmab alone was associated with a prolonged TTD [median: 3.8 months vs 2.8 months] and an improved OS [median: 8.8 months vs. 5.9 months] with an adjusted HR of 0.62 [95% CI 0.53-0.73, p < 0.001]. Both treatment regimens afforded similar 14-day mortality and incidence of ED or hospital visits. The findings for patients over and below the age of 65 were similar.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".