Aflibercept Plus FOLFIRI for Second-line Treatment of Metastatic Colorectal Cancer: Observations from the Global Aflibercept Safety and Health-Related Quality-of-Life Program (ASQoP)
Bibliographic record
Abstract
BACKGROUND: The objectives of this study were to evaluate the safety profile of aflibercept and health-related quality of life (HRQL) in patients with metastatic colorectal cancer (mCRC) provided with aflibercept access before marketing authorization. PATIENTS AND METHODS: Patients received aflibercept followed by FOLFIRI (fluorouracil, leucovorin, irinotecan) on day 1 of a 2-week cycle until disease progression, unacceptable toxicity, death, or patient/investigator decision to discontinue. Treatment-emergent adverse events (TEAEs) were evaluated, and HRQL was assessed at baseline, cycle 3, and every other cycle using the European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30, EORTC QLQ-CR29, and EuroQol 5-Dimensions 3-Levels questionnaires (NCT01571284). RESULTS: Overall, 779 adult patients with mCRC, who received ≥ 1 prior oxaliplatin-based regimen and had disease progression during or following their last administration of oxaliplatin-based chemotherapy, were enrolled. At data cutoff, all patients had discontinued treatment, mainly owing to disease progression (51.7%). The most common TEAEs of any grade were diarrhea (61.6%), hypertension (48.4%), and nausea (43.3%). The most common grade 3/4 TEAEs were hypertension (24.1%), neutropenia (23.1%), and diarrhea (15.3%). Clinically meaningful changes in HRQL were reported for all measures. Most patients either had an improvement in their HRQL scores or remained stable during the treatment period based on patient-reported outcomes. CONCLUSION: The data from this study support the tolerability of the combination of aflibercept and FOLFIRI in a setting that more closely approximates real life in patients with mCRC who failed to respond to oxaliplatin-based chemotherapy, and also suggest an improvement in HRQL.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".