Small molecules and targeted therapies in distant metastatic disease
Bibliographic record
Abstract
Chemotherapy, biological agents or combinations of both have had little impact on survival of patients with metastatic melanoma. Advances in understanding the genetic changes associated with the development of melanoma resulted in availability of promising new agents that inhibit specific proteins up-regulated in signal cell pathways or inhibit anti-apoptotic proteins. Sorafenib, a multikinase inhibitor of the RAF/RAS/MEK pathway, elesclomol (STA-4783) and oblimersen (G3139), an antisense oligonucleotide targeting anti-apoptotic BCl-2, are in phase III clinical studies in combination with chemotherapy. Agents targeting mutant B-Raf (RAF265 and PLX4032), MEK (PD0325901, AZD6244), heat-shock protein 90 (tanespimycin), mTOR (everolimus, deforolimus, temsirolimus) and VEGFR (axitinib) showed some promise in earlier stages of clinical development. Receptor tyrosine-kinase inhibitors (imatinib, dasatinib, sunitinib) may have a role in treatment of patients with melanoma harbouring c-Kit mutations. Although often studied as single agents with disappointing results, new targeted drugs should be more thoroughly evaluated in combination therapies. The future of rational use of new targeted agents also depends on successful application of analytical techniques enabling molecular profiling of patients and leading to selection of likely therapy responders.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".