Challenges of Immunotherapy in Stage IV Non–Small-Cell Lung Cancer
Bibliographic record
Abstract
Treatment for metastatic non-small-cell lung carcinoma has seen important advances in recent years with the introduction of targeted therapies and immunotherapy. Immune checkpoint inhibitors, which target the programmed death 1 receptor and programmed death ligand-1, alone or in combination with platinum-based chemotherapy, have become standard of care in the first-line setting for patients with advanced non-small-cell lung carcinoma without targetable driver mutations. However, several clinical questions have now since emerged. Physicians treating lung cancer lack guidance when treating patients who have a poor performance status, patients who are receiving corticosteroids, and those known for pre-existing autoimmune disorders. Furthermore, data are scarce on rechallenging a patient with immune checkpoint inhibitors after the occurrence of a significant immune-related adverse event. In this review, we aim to shed light on these topics.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".