Safety and Clinical Activity of Atezolizumab Plus Ipilimumab in Locally Advanced or Metastatic Non–Small Cell Lung Cancer: Results From a Phase 1b Trial
Bibliographic record
Abstract
BACKGROUND: This phase 1b study investigated safety and activity of combined checkpoint inhibition (CPI) with programmed death-ligand 1 (PD-L1) antibody atezolizumab plus cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) inhibitor ipilimumab in NSCLC. PATIENTS AND METHODS: Eligible patients had previously treated locally advanced or metastatic non-small cell lung cancer (NSCLC) or melanoma. A standard 3+3 dose escalation investigated atezolizumab (600-1200 mg IV every 3 weeks) plus ipilimumab starting at 1 mg/kg, administered as a single dose or 4 doses, administered every 3 weeks. The expansion stage included a cohort previously treated with atezolizumab. Patients were monitored for safety and tolerability; response was evaluated every 6 weeks. RESULTS: Twenty-seven patients were enrolled, 4 with melanoma and 23 with NSCLC; here, we focus on data for the NSCLC population. Three of 23 patients (13.0%) received prior CPI. No dose-limiting toxicities were reported during dose escalation; dose expansion occurred with atezolizumab 1200 mg plus 1 cycle of ipilimumab 1 mg/kg. Most common treatment-emergent adverse events were dyspnea (39%) and cough (35%); treatment-related Grade ≥3 adverse events occurred in 11 patients (48%), most frequently pneumonitis (17%) and amylase or lipase elevation (9% each). Six of 23 NSCLC patients (26%) achieved confirmed responses, 5 of whom (25%) were CPI naive. Median duration of response was 23.0 (95% CI, 3.2-36.9) months overall and 36.9 (95% CI, 2.9-36.9) months in CPI-naive patients. CONCLUSION: Preliminary efficacy of atezolizumab plus ipilimumab was observed in metastatic NSCLC. The combination had manageable toxicity, with a safety profile consistent with those of the individual agents.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".