Bibliographic record
Abstract
OBJECTIVE: To review the effectiveness and toxicity of periocular topotecan hydrochloride in fibrin sealant (Tisseel) for the control of intraocular retinoblastoma. METHODS: Retrospective medical record review of visually threatening or recurrent intraocular retinoblastoma treated with periocular topotecan. RESULTS: Eight children (10 eyes) received 1 to 4 injections of periocular topotecan in fibrin sealant, without or with concomitant laser and/or single freeze-thaw prechemotherapy cryotherapy. Median dose was 0.18 mg/kg (3.72 mg/m(2)). The 6 children who responded to treatment had small discrete tumors (8 International Intraocular Retinoblastoma Classification group A or B eyes). Of these, prior primary treatment for 3 children (3 eyes) was laser; for 1 child (2 eyes), systemic chemotherapy with focal laser; and for 2 children (3 eyes), periocular topotecan. In 4 children (4 eyes), tumor regression was sufficient for effective focal therapy, but in 2 children (4 eyes), long-term control required systemic chemotherapy. The 2 children who did not respond each had an International Intraocular Retinoblastoma Classification group D eye treated primarily with systemic chemotherapy, focal laser, and cryotherapy and recurrent disease that was not controlled by periocular topotecan; both eyes were eventually enucleated. No ocular and minimal hematological toxic effects were observed. At 11 months' median follow-up after topotecan treatment (18 months since diagnosis), all 8 group A and B eyes were retained with ongoing focal therapy required in only 1 group B eye; the 2 group D eyes were enucleated. CONCLUSION: Periocular topotecan in fibrin sealant can achieve volume reduction of small and recurrent retinoblastoma sufficient to allow successful focal therapy.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".