Programmed Cell Death-Ligand 1 Expression and Clinical Outcomes Among Patients with Resected, Early-Stage Non-Small Cell Lung Cancer: A Real-World Study
Bibliographic record
Abstract
Treatment options for non-small cell lung cancer (NSCLC) are evolving, given recent and expected approvals of immune checkpoint inhibitors (ICIs) targeting programmed cell death-(ligand) 1 (PD-1/PD-L1). We retrospectively evaluated outcomes among patients with resected stage IB-IIIA NSCLC tumors expressing PD-L1 using PALEOS (Pan-cAnadian Lung cancEr Observational Study) data (2016-2019). Key outcomes included PD-L1 expression rate and treatment patterns, recurrence, and median overall (mOS) and disease-free survival (mDFS) among PD-L1+ patients. Among 539 PD-L1-tested patients, 317 (58.8%) were PD-L1+ (≥1%). At diagnosis, 35.3%, 39.8%, and 24.9% of PD-L1+ patients had stage IB, II, or IIIA disease. Forty-one percent had received adjuvant therapy. At 22.6 months (median follow-up), first disease recurrence had occurred in 31.9% of patients, primarily at metastatic sites. After first metastatic recurrence, ICI regimens were the most common first systemic therapy (29.8%). mOS was not reached; mDFS was 40.0 months. At four years, DFS probability was 44%. Four-year OS and DFS rates were generally similar when stratified by PD-L1 expression (1-49% vs. ≥50%). These findings underscore the generally poor outcomes experienced by patients with early-stage, resected, PD-L1+ NSCLC after treatment with available adjuvant therapies, and provide context to recent and emerging trials of new treatment options.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".