Ototoxicity in Children With High-Risk Neuroblastoma: Prevalence, Risk Factors, and Concordance of Grading Scales—A Report From the Children's Oncology Group
Bibliographic record
Abstract
PURPOSE: Platinum-based therapy is the mainstay for management of high-risk neuroblastoma. Prevalence of platinum-related ototoxicity has ranged from 13% to 95% in previous reports; variability is attributable to small samples and disparate grading scales. There is no consensus regarding optimal ototoxicity grading. Furthermore, prevalence and predictors of hearing loss in a large uniformly treated high-risk neuroblastoma population are unknown. We address these gaps in our study. PATIENTS AND METHODS: Audiologic testing was completed after administration of cisplatin alone (< 400 mg/m(2); exposure one) or after cisplatin (400 mg/m(2)) plus carboplatin (1,700 mg/m(2); exposure two). Hearing loss was graded using four scales (American Speech-Language-Hearing Association; Brock; Chang; and Common Terminology Criteria for Adverse Events, version 3 [CTCAEv3]). RESULTS: Of 489 eligible patients, 333 had evaluable audiologic data. Median age at diagnosis was 3.3 years. Prevalence of severe hearing loss differed by scale. For those in the exposure-one group, prevalence ranged from 8% per Brock to 47% per CTCAEv3 (Brock v CTCAEv3 and Chang, P < .01; CTCAEv3 v Chang, P = .16); for those in the exposure-two group, prevalence ranged from 30% per Brock to 71% per CTCAEv3 (all pair-wise comparisons, P < .01). In patients requiring hearing aids, hearing loss was graded as severe in 49% (Brock), 91% (Chang), and 100% (CTCAEv3). Risk factors for severe hearing loss included exposure to cisplatin and carboplatin compared with cisplatin alone and hospitalization for infection. CONCLUSION: Severe hearing loss is prevalent among children with high-risk neuroblastoma. Exposure to cisplatin combined with myeloablative carboplatin significantly increases risk. The Brock scale underestimates severe hearing loss and should be used with caution in this setting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| 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) | 0.000 | 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".