Supportive Care Treatments for Toxicities of Anti-EGFR and Other Targeted Agents
Bibliographic record
Abstract
Targeting of the epidermal growth factor receptor (egfr) pathway has become routine practice in the treatment of lung carcinoma. As more health authorities approve targeted compounds in a variety of treatment lines, use of this approach is expected only to increase.Gefitinib, an oral tyrosine kinase inhibitor (tki), is approved by Health Canada in the first-line setting of advanced non-small-cell lung carcinoma (nsclc) for tumours that harbour the EGFR gene mutation. Erlotinib, another tki, is currently approved in advanced nsclc in the second- and third-line settings.The side-effect profile of this class of drugs is unique. Hematologic toxicity is seldom seen. The most frequent side effects are rash and diarrhea. Although no randomized trials have addressed treatment of the side effects of this class of drugs, some basic principles of management have been agreed on and can likely improve patient compliance and decrease inappropriate dose reduction. The prognostic and predictive implications of side effects are also evolving.Finally, the ALK fusion mutation is being recognized as a mutation driver. The use of crizotinib (again, a tki) in this setting awaits approval. The side-effect profile of crizotinib is interesting and is also reviewed here.
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 | 0.000 | 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".