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Record W4229335523 · doi:10.1097/aud.0000000000001172

Ototoxicity After Cisplatin-Based Chemotherapy: Factors Associated With Discrepancies Between Patient-Reported Outcomes and Audiometric Assessments

2022· article· en· W4229335523 on OpenAlexaff
Shirin Ardeshir‐Rouhani‐Fard, Sophie D. Fosså, Robert Huddart, Patrick O. Monahan, Chunkit Fung, Yiqing Song, M. Eileen Dolan, Darren R. Feldman, Robert J. Hamilton, David J. Vaughn, Neil E. Martin, Christian Kollmannsberger, Paul C. Dinh, Lawrence H. Einhorn, Robert D. Frisina, Lois B. Travis

Bibliographic record

VenueEar and Hearing · 2022
Typearticle
Languageen
FieldNeuroscience
TopicHearing, Cochlea, Tinnitus, Genetics
Canadian institutionsUniversity of British ColumbiaPrincess Margaret Cancer Centre
FundersNational Institute of General Medical SciencesNational Cancer Institute
KeywordsMedicineConfidence intervalOtotoxicityTinnitusOdds ratioHearing lossAudiologyAbsolute threshold of hearingInternal medicineCisplatinChemotherapy

Abstract

fetched live from OpenAlex

Objectives: To provide new information on factors associated with discrepancies between patient-reported and audiometrically defined hearing loss (HL) in adult-onset cancer survivors after cisplatin-based chemotherapy (CBCT) and to comprehensively investigate risk factors associated with audiometrically defined HL. Design: A total of 1410 testicular cancer survivors (TCS) ≥6 months post-CBCT underwent comprehensive audiometric assessments (0.25 to 12 kHz) and completed questionnaires. HL severity was defined using American Speech-Language-Hearing Association criteria. Multivariable multinomial regression identified factors associated with discrepancies between patient-reported and audiometrically defined HL and multivariable ordinal regression evaluated factors associated with the latter. Results: Overall, 34.8% of TCS self-reported HL. Among TCS without tinnitus, those with audiometrically defined HL at only extended high frequencies (EHFs) (10 to 12 kHz) (17.8%) or at both EHFs and standard frequencies (0.25 to 8 kHz) (23.4%) were significantly more likely to self-report HL than those with no audiometrically defined HL (8.1%) [odds ratio (OR) = 2.48; 95% confidence interval (CI), 1.31 to 4.68; and OR = 3.49; 95% CI, 1.89 to 6.44, respectively]. Older age (OR = 1.09; 95% CI, 1.07 to 1.11, p < 0.0001), absence of prior noise exposure (OR = 1.40; 95% CI, 1.06 to 1.84, p = 0.02), mixed/conductive HL (OR = 2.01; 95% CI, 1.34 to 3.02, p = 0.0007), no hearing aid use (OR = 5.64; 95% CI, 1.84 to 17.32, p = 0.003), and lower education (OR = 2.12; 95% CI, 1.23 to 3.67, p = 0.007 for high school or less education versus postgraduate education) were associated with greater underestimation of audiometrically defined HL severity, while tinnitus was associated with greater overestimation (OR = 4.65; 95% CI, 2.64 to 8.20 for a little tinnitus, OR = 5.87; 95% CI, 2.65 to 13.04 for quite a bit tinnitus, and OR = 10.57; 95% CI, 4.91 to 22.79 for very much tinnitus p < 0.0001). Older age (OR = 1.13; 95% CI, 1.12 to 1.15, p < 0.0001), cumulative cisplatin dose (>300 mg/m 2 , OR = 1.47; 95% CI, 1.21 to 1.80, p = 0.0001), and hypertension (OR = 1.80; 95% CI, 1.28 to 2.52, p = 0.0007) were associated with greater American Speech-Language-Hearing Association-defined HL severity, whereas postgraduate education (OR = 0.58; 95% CI, 0.40 to 0.85, p = 0.005) was associated with less severe HL. Conclusions: Discrepancies between patient-reported and audiometrically defined HL after CBCT are due to several factors. For survivors who self-report HL but have normal audiometric findings at standard frequencies, referral to an audiologist for additional testing and inclusion of EHFs in audiometric assessments should be considered.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.070
GPT teacher head0.307
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations23
Published2022
Admission routes1
Has abstractyes

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