Treatment of recurrent clear cell sarcoma of the kidney with brain metastasis
Bibliographic record
Abstract
BACKGROUND: Clear cell sarcoma of the kidney (CCSK) is known for its propensity to metastasize to bone, but it also spreads to other sites including the brain. This study was undertaken to describe the treatment and outcomes of patients with recurrent CCSK involving the brain. METHODS: A retrospective records review was conducted on eight patients with CCSK who developed brain metastases after complete responses to initial therapy. RESULTS: The recurrences occurred at a median of 24.5 months after initial diagnosis (range, 12-53 months). At the time of recurrence, patients were treated with multimodal therapy including biopsy or resection, radiation therapy, and chemotherapy. All patients received a variable number of courses of ifosfamide, carboplatin, and etoposide (ICE), with or without other agents. Four patients received high-dose chemotherapy with autologous stem cell rescue. One patient died from complications of bacteremia 8 weeks after starting chemotherapy. The other seven patients achieved a complete response after either surgery or ICE chemotherapy. Of these, six patients were alive without disease with a median follow-up of 30 months from the time of recurrence (range, 24 to 71 months). All six survivors received radiation therapy and four had gross total resections. Three survivors received high-dose chemotherapy with stem cell rescue. CONCLUSION: Patients with recurrent CCSK involving the brain can have durable survival after recurrence. ICE chemotherapy, together with radiation therapy and surgery, provides a reasonable salvage regimen for recurrent CCSK. It is unclear whether high-dose chemotherapy confers a benefit compared to conventional-dose chemotherapy.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".