Treatment with pembrolizumab in programmed death ligand 1–positive recurrent glioblastoma: Results from the multicohort phase 1 KEYNOTE‐028 trial
Bibliographic record
Abstract
BACKGROUND: Current treatments for recurrent glioblastoma offer limited benefit. The authors report the antitumor activity and safety of the anti-programmed death 1 (anti-PD-1) immunotherapy, pembrolizumab, in programmed death ligand 1 (PD-L1)-positive, recurrent glioblastoma. METHODS: Adult patients with PD-L1-positive tumors were enrolled in the recurrent glioblastoma cohort of the multicohort, phase 1b KEYNOTE-028 study (ClinicalTrials.gov identifier, NCT02054806) and received pembrolizumab 10 mg/kg every 2 weeks for up to 2 years. The primary endpoint was investigator-assessed overall response rate according to the Response Evaluation Criteria in Solid Tumors, version 1.1. Archival tumor samples were assessed for PD-L1 expression levels (prospectively) and T-cell-inflamed gene expression profile score (retrospectively). RESULTS: After a median follow-up of 14 months (range, 2-55 months) among the 26 enrolled patients, the overall response rate was 8% (95% CI, 1%-26%). Two partial responses, lasting 8.3 and 22.8 months, occurred. Progression-free survival (median, 2.8 months; 95% CI, 1.9-8.1 months) rate at 6 months was 37.7%, and the overall survival (median, 13.1 months; 95% CI, 8.0-26.6 months) rate at 12 months was 58%. Correlation of therapeutic benefit to level of PD-L1 expression, gene expression profile score, or baseline steroid use could not be established. Treatment-related adverse events occurred in 19 patients (73%), and 5 patients experienced grade 3 or 4 events (there were no grade 5 events). Immune-mediated adverse events and infusion reactions occurred in 7 patients (27%). CONCLUSIONS: Pembrolizumab monotherapy demonstrated durable antitumor activity in a subset of patients with manageable toxicity in this small, signal-finding, recurrent glioblastoma cohort. Future studies evaluating rationally designed pembrolizumab combination regimens may improve outcomes in patients with recurrent glioblastoma.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".