Clinical Characteristics and Surgical Outcomes of Patients Receiving Perioperative Pembrolizumab in KEYNOTE-671
Bibliographic record
Abstract
BACKGROUND: The phase 3 KEYNOTE-671 study (NCT03425643) demonstrated significantly improved event-free survival (EFS) and overall survival with neoadjuvant pembrolizumab plus chemotherapy followed by surgery and adjuvant pembrolizumab vs neoadjuvant chemotherapy and surgery for early-stage non-small cell lung cancer (NSCLC). We describe participant characteristics, surgical outcomes, and EFS in surgically relevant subgroups. METHODS: Participants with untreated, resectable, stage II-IIIB (N2) NSCLC were randomized 1:1 to neoadjuvant pembrolizumab 200 mg or placebo plus cisplatin-based chemotherapy every 3 weeks for 4 cycles, then surgery and adjuvant pembrolizumab or placebo for 13 cycles. Surgery was performed ≤20 weeks after first neoadjuvant dose (if 4 cycles of neoadjuvant therapy) or 4-8 weeks after last neoadjuvant dose (1-3 cycles); surgery beyond this was considered surgical delay. Adjuvant therapy began 4-12 weeks after surgery. EFS was assessed in the surgical population. RESULTS: Of 397 participants randomized to pembrolizumab and 400 to placebo, 325 (82.1%) and 317 (79.4%), respectively, underwent surgery. At data cutoff (July 10, 2023), 4.9% (pembrolizumab) and 7.6% (placebo) of participants experienced surgical delay; 38.9% and 28.4%, respectively, experienced nodal downstaging; 78.8% and 75.1% underwent lobectomy; and 92.0% and 84.2% had R0 resections. Pembrolizumab improved EFS irrespective of disease stage, nodal status, and type of surgery vs chemotherapy. Eight participants (pembrolizumab, n = 6; placebo, n = 2) died ≤30 days after surgery from surgery-related adverse events. CONCLUSIONS: Neoadjuvant pembrolizumab did not adversely affect surgical outcomes, was associated with numerically higher R0 resections, and improved EFS vs neoadjuvant chemotherapy in surgically relevant subgroups in early-stage NSCLC.
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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".