Brain Metastases in Non-Small-Cell Lung Cancer: Are Tyrosine Kinase Inhibitors and Checkpoint Inhibitors Now Viable Options?
Bibliographic record
Abstract
Significant progress has been made in the treatment of stage IV non-small-cell lung cancer (NSCLC); however, the prognosis of patients with brain metastases remains poor. Resection and radiation therapy remain standard options. This issue is an important one because 10% of patients with NSCLC have brain metastases at diagnosis, and 25%–40% develop brain metastases during their disease. Standard chemotherapy does not cross the blood–brain barrier. However, there is new hope that tyrosine kinase inhibitors (TKIS) used in patients with identified targetable mutations such as mutations of EGFR and rearrangements of ALK could have activity in the central nervous system (CNS). Furthermore, immunotherapy is increasingly becoming a standard option for patients with NSCLC, and interest about the intracranial activity of those agents is growing. This review presents current data about the CNS activity of the available major TKIS and immunotherapy agents.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".