New concepts in the diagnosis and management of choroidal metastases
Bibliographic record
Abstract
The most frequent site of ocular metastasis is the choroid. The occurrence of choroidal metastases has increased steadily due to the longer survival of metastatic patients and the improvement of diagnostic tools. Fundoscopy, ultrasonography, and fluorescein angiography are now complemented by indocyanine green angiography and optical coherence tomography. Choroidal tumor biopsy may also confirm the metastatic nature of the tumor and help to determine the site of the primary malignancy. There is currently no consensus on the treatment strategy. Most patients have a limited life expectancy and for these complex treatments are generally not recommended. However, recent advances in systemic therapy have significantly improved survival of certain patients who may benefit from an aggressive ocular approach that could preserve vision. Although external beam radiation therapy is the most widely used treatment, more advanced forms of radiotherapy that are associated with fewer side effects can be proposed in select cases. In patients with a shorter life expectancy, systemic therapies such as those targeting oncogenic drivers, or immunotherapy can induce a regression of the choroidal metastases, and may be sufficient to temporarily decrease visual symptoms. However, they often acquire resistance to systemic treatment and ocular relapse usually requires radiotherapy for durable control. Less invasive office-based treatments, such as photodynamic therapy and intravitreal injection of anti-VEGF, may also help to preserve vision while reducing time spent in medical settings for patients in palliative care. The aim of this review is to summarize the current knowledge on choroidal metastases, with emphasis on the most recent findings in epidemiology, pathogenesis, diagnosis and treatment.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".