Sorafenib in metastatic uveal melanoma: efficacy, toxicity and health-related quality of life in a multicentre phase II study
Bibliographic record
Abstract
BACKGROUND: The aim of the study was to analyse efficacy, safety, and health-related quality of life (HRQoL) for sorafenib treatment in patients with metastatic uveal melanoma. METHODS: A multicentre, single-arm phase II trial was conducted. The primary objective was to determine the non-progression rate (RECIST) at 24 weeks for patients receiving sorafenib at a dose of 800 mg per day. Secondary endpoints included progression-free survival (PFS), overall survival (OS), toxicity, and HRQoL. RESULTS: Thirty-two patients were included. Ten patients showed non-progression at 24 weeks (31.2%) without objective tumour responses. The estimated 24-week PFS was 31.2% (95% CI: 14.8%-47.6%) and the estimated 24-week OS was 62.5% (95% CI: 45.4%-79.6%). Ten patients (34.3%) had at least one grade 3 or 4 adverse reaction and 12 patients (41.4%) required dose modifications due to toxicity. At 24 weeks, no patient had an improvement in global HRQoL and 87.5% experienced a permanent increase in physical fatigue. CONCLUSIONS: Sorafenib demonstrated non-progression at 24 weeks in 31.2% of patients. However, 41.4% of patients required dose modifications due to toxicity and no improvement in HRQoL was demonstrated.
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".