The treatment of bilaterally advanced retinoblastoma: The Institut Curie experience
Bibliographic record
Abstract
Abstract Purpose Since 2005 we have used more intensive chemotherapy, combined with intensive local treatment started at the third cycle in case of bilateral group D or group D+E bilateral retinoblastoma. We report the results Methods All children identified with bilaterally advanced retinoblastoma were treated with 6 courses of 3 drugs. Local treatments including laser, cryotherapy and sometimes iodine plaque brachytherapy were started at the third cycle, synergistic with the chemotherapy. All tumors except the macular tumors were treated with laser during 5 to 20 minutes. The inferior periphery was treated with cryotherapy . After the end of the chemotherapy, close follow up was performed and additional local treatments were often necessary. Data concerning the initial findings, treatments and results were entered in the data base. Results : the follow up ranges from 3 to 8 years with a mean follow up of five years. Between 2005 and 2010 23 group D eyes were treated in 16 children.17 eyes are preserved without external beam (73%) One eye is lost to follow up. Visual acuity is available in 11 children ranging from counting fingers to 20/20 with a mean visual acuity of 20/50. Conclusion Intravenous chemotherapy associated with intensive local treatments allows preservation of the eye with usefull vision in a great pourcentage of group D eyes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".