Five-year long-term overall survival for patients with advanced NSCLC treated with pembrolizumab: Results from KEYNOTE-001.
Bibliographic record
Abstract
LBA9015 Background: Pembrolizumab (pembro) monotherapy has demonstrated durable antitumor activity in advanced PD-L1–expressing NSCLC. We present 5-y OS for patients (pts) enrolled in the phase 1b KEYNOTE-001 study (NCT01295827), the first trial evaluating pembro in advanced NSCLC. These data provide the longest efficacy/safety follow-up for NSCLC pts treated with pembro. Methods: Pts had confirmed locally advanced/metastatic NSCLC and provided a contemporaneous tumor sample for PD-L1 evaluation by IHC using the 22C3 antibody. Pts received pembro 2 mg/kg Q3W or 10 mg/kg Q2W or Q3W. The primary efficacy endpoint was ORR. OS was a secondary endpoint. Results: 550 pts were enrolled (treatment-naive, n=101; previously treated, n=449). As of November 5, 2018 (data cutoff), median (range) follow-up was 60.6 (51.8–77.9) mo; 82% (n=450/550) had died. Estimated 5-y OS rates were 23.2% for treatment-naive pts and 15.5% for previously treated pts (Table). ORR (by investigator per irRC) was 42% (95% CI, 32–52) for treatment-naive pts and 23% (95% CI, 19–27) for previously treated pts. Median (range) DOR was 16.8 (2.1+ to 55.7+) mo and 38.9 (1.0+ to 71.8+) mo, respectively. Immune-mediated AEs had occurred in 17% of pts at 5 y, similar to the incidence reported at 3-y follow-up. Additional results, including outcomes in key subgroups and detailed safety follow-up data, will be presented. Conclusions: In KEYNOTE-001, 5-y OS rate was 23.2% in treatment-naive pts and 15.5% in previously treated pts with advanced NSCLC treated with pembro, compared to a historical rate of ~5% (per SEER 2008–2014), prior to the introduction of anti–PD-1 therapy. 5-y OS rate was at least 25% in pts with PD-L1 TPS ≥50% in both pt populations in KEYNOTE-001. Clinical trial information: NCT01295827. [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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".