Atezolizumab in Combination With Carboplatin and Nab-Paclitaxel in Advanced Squamous NSCLC (IMpower131): Results From a Randomized Phase III Trial
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Cytotoxic agents have immunomodulatory effects, providing a rationale for combining atezolizumab (anti-programmed death-ligand 1 [anti-PD-L1]) with chemotherapy. The randomized phase III IMpower131 study (NCT02367794) evaluated atezolizumab with platinum-based chemotherapy in stage IV squamous NSCLC. METHODS: A total of 1021 patients were randomized 1:1:1 to receive atezolizumab+carboplatin+paclitaxel (A+CP) (n = 338), atezolizumab+carboplatin+nab-paclitaxel (A+CnP) (n = 343), or carboplatin+nab-paclitaxel (CnP) (n = 340) for four or six 21-day cycles; patients randomized to the A+CP or A+CnP arms received atezolizumab maintenance therapy until progressive disease or loss of clinical benefit. The coprimary end points were investigator-assessed progression-free survival (PFS) and overall survival (OS) in the intention-to-treat (ITT) population. The secondary end points included PFS and OS in PD-L1 subgroups and safety. The primary PFS (January 22, 2018) and final OS (October 3, 2018) for A+CnP versus CnP are reported. RESULTS: PFS improvement with A+CnP versus CnP was seen in the ITT population (median, 6.3 versus 5.6 mo; hazard ratio [HR] = 0.71, 95% confidence interval [CI]: 0.60-0.85; p = 0.0001). Median OS in the ITT population was 14.2 and 13.5 months in the A+CnP and CnP arms (HR = 0.88, 95% CI: 0.73-1.05; p = 0.16), not reaching statistical significance. OS improvement with A+CnP versus CnP was observed in the PD-L1-high subgroup (HR = 0.48, 95% CI: 0.29-0.81), despite not being formally tested. Treatment-related grade 3 and 4 adverse events and serious adverse events occurred in 68.0% and 47.9% (A+CnP) and 57.5% and 28.7% (CnP) of patients, respectively. CONCLUSIONS: Adding atezolizumab to platinum-based chemotherapy significantly improved PFS in patients with first-line squamous NSCLC; OS was similar between the arms.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 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 it