Role of Cisplatin Dose Intensity and TPMT Variation in the Development of Hearing Loss in Children
Bibliographic record
Abstract
BACKGROUND: Cisplatin, widely used in the treatment of solid tumors, causes permanent hearing loss in more than 60% of treated children. Previous studies have implicated several clinical factors in the development of ototoxicity, including cumulative cisplatin dose. However, the role of cisplatin dose intensity in the development of hearing loss in children remains unclear. Pharmacogenetic studies have also identified genetic variants in TPMT that increase the risk of cisplatin-induced hearing loss. This study aims to determine whether cisplatin dose intensity contributes to the risk of hearing loss in children and whether genetic variations in TPMT further modifies the risk of cisplatin-induced hearing loss. METHODS: The authors genotyped 371 cisplatin-treated children for the presence of any 3 TPMT -risk variants. Patients were categorized into high-, moderate-, and low-intensity cisplatin dosing groups according to the cisplatin dose administered per unit time. Kaplan-Meier curves were plotted to compare the cumulative incidence of hearing loss between the genotype and dose intensity groups. RESULTS: Patients receiving cisplatin at high dose intensity experienced significantly higher incidences of ototoxicity than those receiving cisplatin at low dose intensity ( P = 9 × 10 -7 ). Further stratification by TPMT genotype revealed that carriers of ≥1 TPMT variants receiving high-intensity cisplatin developed ototoxicity sooner and more often than their wild-type counterparts (93.8% vs. 56.6% at 12 months; P = 5 × 10 -5 ) and noncarriers receiving low-intensity cisplatin (21.2% at 12 months). CONCLUSIONS: Cisplatin dose intensity is strongly associated with ototoxicity development in children, and this risk is further increased by the presence of TPMT -risk alleles.
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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".