Clinical and genetic associations for carboplatin‐related ototoxicity in children treated for retinoblastoma: A retrospective noncomparative single‐institute experience
Bibliographic record
Abstract
BACKGROUND: Children with retinoblastoma treated with carboplatin chemotherapy risk moderate to severe, irreversible hearing loss. Based on published evidence, we hypothesized that ototoxicity risk is associated with clinical parameters and variants in candidate genes in drug metabolism pathways (methyltransferases [thiopurine S-methyltransferase, TPMT] and [catechol-O-methyltransferase, COMT], and drug transporter ABCC3). PROCEDURE: We retrospectively reviewed clinical records of patients with retinoblastoma treated with carboplatin chemotherapy regarding age (at diagnosis and chemotherapy initiation), chemotherapy sessions (cycles number, drug doses, and cumulative carboplatin dose), and hearing loss (defined as ototoxicity ≥grade 2 by at least one classification system). Blood samples were genotyped for genetic variants in TPMT (rs12201199, rs1800460), COMT (rs4646316, rs9332377), and ABCC3 (rs1051640) by quantitative PCR and confirmed by allele-specific PCR. Univariate statistical tests, receiver-operating characteristic analysis, and Kaplan-Meier curves were used to examine the association between hearing loss, clinical factors, and variants in candidate genes. RESULTS: ). Ototoxicity occurred in 18 patients (25%), strongly associated with age at diagnosis (P = 0.01) and age at chemotherapy initiation (OR = 4.99, P = 0.008). The highest likelihood ratio of hearing loss was associated with chemotherapy initiation <4.25 months of age. Ototoxicity was not associated with any tested genetic variants. CONCLUSIONS: We observed a 25% prevalence of ototoxicity in patients with retinoblastoma treated with carboplatin, higher than previously published. Age at chemotherapy initiation was associated with carboplatin-induced ototoxicity, with children <4.25 months of age at highest risk.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".