Bevacizumab Plus Chemotherapy as First-Line Treatment for Patients with Metastatic Colorectal Cancer: Results from a Spanish Observational Study
Bibliographic record
Abstract
Background: This observational study evaluated the efficacy and safety of treatment with bevacizumab plus chemotherapy until disease progression (PD) in Spanish patients with metastatic colorectal cancer (mCRC). Methods: This multicentre, retrospective, observational analysis included patients receiving bevacizumab plus fluoropyrimidine-based chemotherapy as first-line treatment for mCRC who then developed PD. All patients received treatment in hospital oncology departments and none received bevacizumab as part of a clinical trial. Patients discontinuing treatment with bevacizumab for reasons other than PD were excluded. The primary endpoint was PFS; secondary endpoints were overall response rate (ORR) and safety. Results: Overall, 165 patients were evaluable for analysis: median age 63.0 years; male/female 62%/38%; ECOG performance status 0/1/2 55%/43%/2%. Median duration of bevacizumab treatment was 8.7 months. ORR was 48.5% (6 complete and 74 partial responses) and disease control rate was 74%. Median progression-free survival (PFS) was 8.4 months (95% CI 7.2-9.6). Patients receiving oxaliplatin- or irinotecan-based regimens had median PFS of 9.2 and 7.7 months, respectively; those receiving treatment not containing either oxaliplatin or irinotecan had a median PFS of 6.1 months. KRAS status did not have a statistically significant effect on PFS (9.5 vs. 7.8 months for KRAS wild-type vs. mutant tumours, respectively; p=0.647) or ORR (44.8% vs. 52.6%, respectively; p=0.391). The most common grade 3/4 adverse events were: diarrhoea (7%), paraesthesia (7%), neutropenia (3%), cutaneous toxicity (2%), and thrombocytopenia (2%). Conclusions: Treatment with bevacizumab plus standard chemotherapy is an effective and well-tolerated option for patients with mCRC who continue treatment until PD.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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, 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".