Management of Diarrhea Induced by Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors
Bibliographic record
Abstract
Treatment for non-small-cell lung cancer (nsclc) is moving away from traditional chemotherapy toward personalized medicine. The reversible tyrosine kinase inhibitors (tkis) erlotinib and gefitinib were developed to target the epidermal growth factor receptor (egfr). Afatinib, an irreversible ErbB family blocker, was developed to block egfr (ErbB1), human epidermal growth factor receptor 2 (ErbB2), and ErbB4 signalling, and transphosphorylation of ErbB3. All of the foregoing agents are efficacious in treating nsclc, and their adverse event profile is different from that of chemotherapy. Two of the most common adverse events with egfr tkis are rash and diarrhea. Here, we focus on diarrhea. The key to successful management of diarrhea is to treat early and aggressively using patient education, diet, and antidiarrheal medications such as loperamide. We also present strategies for the effective assessment and management of egfr tki-induced diarrhea.
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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 | 0.000 | 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 | 0.001 |
| 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".