A Real-Life Experience Using Panitumumab in Chemo-Refractory Metastatic Colorectal Cancer Patients: A Retrospective Analysis at the Jewish General Hospital, 2009–2012
Bibliographic record
Abstract
BACKGROUND: Panitumumab is a fully human monoclonal antibody, directed against the epidermal growth factor receptor, that was shown to be effective in third-line metastatic colorectal cancer. We performed a retrospective analysis of patients with chemo-refractory non-KRAS-mutated metastatic colorectal cancer, who received panitumumab at the Jewish General Hospital in Montreal, Canada, between 2009 and 2012. METHODS: This chart review included 44 patients (median age: 60 years; performance status: 0-3), of whom 50% had already received three lines of treatment. The primary endpoint was progression-free survival (pfs). Secondary endpoints were overall survival and safety. Tumour progression was determined by radiologic assessments performed once every 3 months per clinical guidelines or by clinical deterioration as determined by the clinician-investigator. RESULTS: In our sample, median pfs was 21.86 ± 5.23 weeks (95% confidence interval: 12.9 to 36.9 weeks) and overall survival was 35.14 ± 7.75 weeks (95% confidence interval: 25.6 to 73.4 weeks) with a median of 5 cycles of panitumumab treatment. The most frequently reported toxicities with panitumumab were skin toxicity (16.2% grade 3) and hypomagnesemia (10.8% grade 3). No infusion reactions were reported. CONCLUSIONS: Despite a small sample size from a single institution, our survival and efficacy data are encouraging and comparable to results obtained from the registration panitumumab trial. Our findings suggest that panitumumab can be effective and tolerable in a real-world setting.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".