Canadian experience managing dose intensity of regorafenib in relation to safety and clinical outcome in metastatic colorectal cancer patients.
Bibliographic record
Abstract
e15154 Background: Phase III trials CORRECT and CONCUR have shown that Regorafenib confers survival advantage in metastatic colorectal (mCRC) patients. Unfortunately, toxicity often limits its full use. Therefore, upfront priori dose reduction (PDR) is often performed. Its clinical implications and outcomes were reviewed. Methods: A chart review was conducted on 50 mCRC patients who failed standard chemotherapy and received Regorafenib as a 3rd or 4th line of treatment at the Jewish General Hospital, McGill University between 2013-2015. The primary endpoints examined treatment patterns and adverse events (AEs) as per CTCAE v 4.0. A secondary endpoint examined progression free survival (PFS) as estimated by the Kaplan Meier method. Results: Among the 50 patients were 44 males with a median age of 61 (42-82), 24 KRAS mutated (47%) and 19 (KRAS) wild type (38%). All patients had either ECOG 0 or 1 (32% ECOG 0,68% ECOG 1). Upfront PDR of 25% (120 mg) was performed in 26/50 patients (52%). The median duration of treatment was 2.7 months (2-11 months). In most cases, PDR lowered Aes: fatigue (58% vs 73%); diarrhea (5% vs 27%) and hepatotoxicity (11% vs 82%) (p < 0.05). However, the occurrence of skin reactions (47% vs 46%) did not fluctuate much. Throughout the course of treatment, 24/50 patients (48%) receiving a full dose (160 mg) required dose modification, including 8/24 (33%) while 45% required dose interruption or delays secondary to AEs respectively. The median PFS was 3.7 months (95% CI: 3.4 – 7.5 months) with no statistically significant difference in PFS between patients receiving a full dose, compared to those who received PDR upfront.Conclusions: Our findings suggest that patients treated with upfront PDR (120 mg) of Regorafenib had a better tolerance for treatment than those treated with the recommended dose of 160 mg. No further statistically significant differences were observed between the two cohorts in clinical outcomes.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".