Safety and Patient-Reported Outcomes of Atezolizumab Plus Chemotherapy With or Without Bevacizumab Versus Bevacizumab Plus Chemotherapy in Non–Small-Cell Lung Cancer
Bibliographic record
Abstract
PURPOSE: Atezolizumab, bevacizumab, carboplatin, and paclitaxel (ABCP) demonstrated survival benefit versus bevacizumab, carboplatin, and paclitaxel (BCP) in chemotherapy-naïve nonsquamous non-small-cell lung cancer (NSCLC). We present safety and patient-reported outcomes (PROs) to provide additional information on the relative impact of adding atezolizumab to chemotherapy with and without bevacizumab in nonsquamous NSCLC. METHODS: Patients were randomly assigned to receive atezolizumab, carboplatin, and paclitaxel (ACP), ABCP, or BCP. Coprimary end points were overall survival and investigator-assessed progression-free survival. The incidence, nature, and severity of adverse events (AEs) were assessed. PROs, a secondary end point, were evaluated using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ)-Core 30 and EORTC QLQ-Lung Cancer 13. RESULTS: 11.1%). During induction, the incidence of serious AEs (SAEs) was 28.3%, 28.5%, and 26.4% in the ACP, ABCP, and BCP arms, respectively. During maintenance, SAE incidences were 20.0%, 26.3%, and 13.0%, respectively. Completion rates of the PRO questionnaires were > 88% at baseline and remained ≥ 70% throughout most study visits. Across arms, patients on average reported no clinically meaningful worsening of global health status or physical functioning scores through cycle 13. Patients across arms rated common symptoms with chemotherapy and immunotherapy similarly. CONCLUSION: ABCP seems tolerable and manageable versus ACP and BCP in first-line nonsquamous NSCLC. Treatment tolerability differed between induction and maintenance phases across treatment arms. PROs reflect a minimal treatment burden (eg, health-related quality of life, symptoms) with each regimen.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".