Overall survival with cisplatin–gemcitabine and bevacizumab or placebo as first-line therapy for nonsquamous non-small-cell lung cancer: results from a randomised phase III trial (AVAiL)
Bibliographic record
Abstract
BACKGROUND: Bevacizumab, the anti-vascular endothelial growth factor agent, provides clinical benefit when combined with platinum-based chemotherapy in first-line advanced non-small-cell lung cancer. We report the final overall survival (OS) analysis from the phase III AVAiL trial. PATIENTS AND METHODS: Patients (n = 1043) received cisplatin 80 mg/m(2) and gemcitabine 1250 mg/m(2) for up to six cycles plus bevacizumab 7.5 mg/kg (n = 345), bevacizumab 15 mg/kg (n = 351) or placebo (n = 347) every 3 weeks until progression. Primary end point was progression-free survival (PFS); OS was a secondary end point. RESULTS: Significant PFS prolongation with bevacizumab compared with placebo was maintained with longer follow-up {hazard ratio (HR) [95% confidence interval (CI)] 0.75 (0.64-0.87), P = 0.0003 and 0.85 (0.73-1.00), P = 0.0456} for the 7.5 and 15 mg/kg groups, respectively. Median OS was >13 months in all treatment groups; nevertheless, OS was not significantly increased with bevacizumab [HR (95% CI) 0.93 (0.78-1.11), P = 0.420 and 1.03 (0.86-1.23), P = 0.761] for the 7.5 and 15 mg/kg groups, respectively, versus placebo. Most patients ( approximately 62%) received multiple lines of poststudy treatment. Updated safety results are consistent with those previously reported. CONCLUSIONS: Final analysis of AVAiL confirms the efficacy of bevacizumab when combined with cisplatin-gemcitabine. The PFS benefit did not translate into a significant OS benefit, possibly due to high use of efficacious second-line therapies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".