Uveal metastasis: clinical characteristics, treatment, and prognostic factors in a cohort of 161 patients in China
Bibliographic record
Abstract
OBJECTIVE: To investigate the clinical and prognostic features of uveal metastasis in a Chinese population and compare these features across different primary cancers. DESIGN: Retrospective cross-sectional study. PARTICIPANTS: 161 patients with uveal metastasis at Beijing Tongren Hospital. METHODS: Clinical characteristics of the primary tumour and uveal metastasis, treatments and outcomes were reviewed. Tumor regression was assessed using B-scan ultrasonography to measure changes in tumor height. RESULTS: Among 161 patients, 185 eyes had uveal metastasis. Lung cancer was the most common primary tumour (49.4%), followed by breast cancer (22.4%), kidney cancer (4.3%). Uveal metastasis was the initial cancer manifestation in 39 patients (24.2%). Unilateral involvement was predominant (86.3%), with the choroid being the most common site (91%). Compared with lung cancer and other cancers, breast carcinoma patients developed uveal metastasis at a younger age (p < 0.001), had a longer interval to uveal metastasis diagnosis (0.67, 4.19, and 6.27 years, p < 0.0001), were prone to be bilateral (11.1%, 9.1%, and 27.8%; p < 0.05) and exhibited lower tumour height (4.47 ± 2.49 mm and 4.88 ± 3.01 mm, 3.09 ± 2.46 mm; p < 0.01). Local treatments (133 eyes) included plaque radiotherapy (PRT, brachytherapy), transpupillary thermotherapy (TTT), anti-VEGF and enucleation. The tumour regression correlated with increased tumor height (r = 0.5699; p < 0.05) in eyes treated with PRT (n = 15). Despite effective local tumour control, the 1-year, 3-year, and 5-year survival rates were 72.61%, 31.82%, and 19.84%, respectively (n = 103). Among the 54 deceased patients, 27 (50%) died within one year following the diagnosis of uveal metastasis. The mean survival was 18.84 months. Extraocular metastasis correlated with shorter survival (p < 0.05). CONCLUSION: This study provides a comprehensive analysis of uveal metastasis in Chinese patients, highlighting the distinct characteristics from various primaries. Although survival rates remain uncertain, local therapies were effective at achieving ocular tumor control, which aligns with the expectations for patients battling metastatic cancers.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".