Safety of Multi-Targeted Kinase Inhibitors as Monotherapy Treatment of Cancer: A Systematic Review of the Literature
Bibliographic record
Abstract
PURPOSE: To identify potential safety profiles for small molecule multi-targeted kinase inhibitors for the treatment of advanced cancer. METHODS: A systematic review was performed on published papers and meeting abstracts reporting safety outcomes in cancer patients for selected multi-kinase inhibiting small molecules with mainly anti-angiogenic activity. Specifically, we focused on single agent safety or early phase clinical development studies. RESULTS: Of 1,923 studies identified in a MEDLINE search, 26 primary studies met eligibility criteria. Meeting materials included 7 papers, 6 posters, and 27 abstracts. When grade I-IV safety results of all 23 kinases were summed together, diarrhea, fatigue, nausea, rash, anorexia, vomiting, hand/foot syndrome, and hypertension were common, occurring in greater than 10% of patients. When only grade III and IV events are pooled together, fatigue and hypertension remain relatively common (> 5%). When total adverse events were stratified by kinase or by kinase family, differences in safety profiles emerged. CONCLUSIONS: The results of this systematic review suggest that adverse events are common and varied for patients treated with a multi-kinase inhibitor. However, unlike some systemic cytotoxic therapies, serious and severe adverse events for multikinase inhibitors are less frequent. Sub-analyses by target kinase or kinase family demonstrate that certain groups of multi-kinase inhibitors can be associated with different safety profiles with unique adverse events.
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 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 | 0.009 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".