Assessment of safety of bevacizumab (bev) use for metastatic colorectal cancer (mCRC) in elderly patients treated at the Centre Hospitalier de l’Université de Montréal (CHUM): A retrospective study.
Bibliographic record
Abstract
677 Background: A 2004 randomized study showed a meaningful improvement in survival with bev added to chemotherapy (CT) for patients with mCRC. This combination is now widely used and generally well tolerated although adverse events (AEs) are described associated with the use of bev, some of which may be increased in incidence in an elderly population. In this study, we assessed these AEs in a population of elderly patients treated with bev in a major center in Montréal. Methods: Patients with mCRC who received bev at our institution outside a clinical trial were retrieved from the pharmacy registry. Medical records were sought from patients who qualified for the inclusion criteria: ≥ 65 years, bev therapy at 5mg/kg every two weeks, combination with CT, period 2007-2011. A retrospective analysis of specific AEs was done and grade according to NCI-CTC (version 4.0) was assessed: febrile neutropenia, hypertension, proteinuria, diarrhea, venous thromboembolic event (VTE), arterial thromboembolic event (ATE), bleeding and gastrointestinal perforation. Results: 47 patients received a total of 486 cycles of bev. Out of these cycles, 210 were given with FOLFOX, 199 with FOLFIRI and 77 with other combinations. Median age of the patients was 69 years. 3 episodes of febrile neutropenia were noted. Grade 3 or 4 arterial hypertension occurred in 4 patients of which 2 had to definitively stop bev. Grade 3 proteinuria was reported with definitive cessation of bev in 2 patients. Grade 3 or 4 diarrhea was observed in 2 cases. We reported 1 cerebral ATE leading to discontinuation of bev and grade 2 VTE in two patients. One grade 5 gastrointestinal perforation was reported. No major bleeding was noted. Conclusions: The number of adverse events observed in this population of elderly patients is comparable to other studies. Thus, age should not be an exclusion criteria for treatment with bev and CT.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".