Nivolumab (N) plus ipilimumab (I) as first-line (1L) treatment for advanced (adv) NSCLC: 2-yr OS and long-term outcomes from CheckMate 012.
Bibliographic record
Abstract
9093 Background: The fully human anti–PD-1 antibody N offers long-term OS benefit in patients (pts) with previously treated adv NSCLC. Adding I (anti–CTLA-4 antibody) to N has been shown to improve clinical activity vs either agent alone in multiple tumor types. We present long-term data for 1L N+I treatment of pts with adv NSCLC from CheckMate 012. Methods: In two cohorts in this phase 1 study, pts with recurrent stage IIIb/IV, chemotherapy-naive NSCLC and ECOG PS 0–1 received N 3 mg/kg Q2W combined with I 1 mg/kg Q12W (n=38) or Q6W (n=39) until disease progression, unacceptable toxicity, or consent withdrawal. The primary endpoint was safety and tolerability. Secondary endpoints included investigator-assessed ORR (RECIST v1.1) and PFS. Exploratory endpoints included OS and efficacy by tumor PD-L1 expression. Results: In the N+I Q12W and N+I Q6W cohorts, respectively, 42% and 31% of pts experienced grade 3–4 treatment-related (TR) AEs; 18% in each cohort discontinued due to any-grade TRAEs. The most frequently reported any-grade TRAEs were pruritus (26%) and diarrhea (21%) with N+I Q12W, and fatigue (26%) and diarrhea (23%) with N+I Q6W. There were no TR deaths. N+I showed promising efficacy (table). While efficacy was enhanced with increasing PD-L1 expression, activity was noted in pts with <1% PD-L1 (table). Of 6 complete responses (CRs), 3 were in pts with <1% PD-L1. Conclusions: 1L therapy with N+I demonstrates a manageable safety profile and promising, durable efficacy (including pathological CRs) in adv NSCLC; efficacy was enhanced in pts with ≥1% PD-L1 tumor expression. Longer follow-up data, including 2-yr OS and characteristics of long-term survivors, will be presented. Clinical trial information: NCT01454102. [Table: see text]
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".