The role of immunotherapy in resectable non-small-cell lung cancer
Bibliographic record
Abstract
Non-small-cell lung cancer (NSCLC) accounts for 80%-85% of all lung cancer cases, being the leading cause of cancer-related mortality worldwide. Historically, outcomes for patients with resectable disease have trailed those with other solid organ malignancies. Advances in treatment strategies, particularly in immunotherapy (IO), have revolutionised the landscape of lung cancer care. In resectable NSCLC (rNSCLC), including stage III disease, the integration of immunotherapy is increasingly being explored for its potential to reduce recurrences and improve survival outcomes. Several landmark clinical trials have resulted in regulatory approvals, and the rapid adoption of immunotherapy in the neoadjuvant, perioperative and adjuvant settings. This review will comprehensively examine the evolving role of immunotherapy in rNSCLC, with a focus on trial evidence, mechanisms of action, biomarkers and challenges in clinical implementation. We also discuss its implications for multimodal therapy across neoadjuvant, perioperative and adjuvant settings while highlighting potential future directions and identifying unanswered questions.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 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".