Update on Retinoblastoma Predisposition and Surveillance Recommendations for Children
Bibliographic record
Abstract
Hereditary retinoblastoma is a classic cancer predisposition syndrome with risks beginning in early infancy. About 45% of children with retinoblastoma (RB) have hereditary disease. These children are at risk for both intraocular disease and additional neoplasms throughout their lifetime. Germline pathogenic/likely pathogenic variants in RB1 typically lead to bilateral intraocular disease, elevated risks of trilateral RB, and risks of non-ocular subsequent malignant neoplasms (SMN), especially sarcomas and melanomas. There is further increased risk of SMNs if radiation treatment is used. In this report, with a reconvening of the American Association for Cancer Research (AACR) Childhood Cancer Predisposition Workshop, we expand on strategies for identifying individuals with hereditary RB, with a focus on testing strategies for children with RB. We also provide updates from previous recommendations. Given the high penetrance of retinal tumors, we review the importance of close intraocular surveillance and consider recent data on surveillance for SMNs. Finally, we discuss the importance of counseling for survivors of intraocular disease to address risks of adult-onset tumors as well as to consider reproductive risks.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".