Managing Treatment–Related Adverse Events Associated with Alk Inhibitors
Bibliographic record
Abstract
Anaplastic lymphoma kinase (ALK) rearrangements have been identified as key oncogenic drivers in a small subset of non-small-cell lung cancers (nsclcs). Small-molecule Alk kinase inhibitors such as crizotinib have transformed the natural history of nsclc for this subgroup of patients. Because of the prevalence of nsclc, ALK-positive patients represent an important example of the paradigm for personalized medicine. Although Alk inhibitors such as crizotinib are well tolerated, there is a potential for adverse events to occur. Proactive monitoring, treatment, and education concerning those adverse events will help to optimize the therapeutic index of the drugs. The present review summarizes the management of treatment-related adverse events that can arise with Alk inhibitors such as crizotinib.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".