137 Audiologic monitoring of cisplatin ototoxicity in cancer treatment of adults: a balance between overdiagnosis and patient safety?
Bibliographic record
Abstract
Objectives Cisplatin, despite its effectiveness against various malignancies, can lead to serious side effects such as ototoxicity. However, ototoxicity monitoring has been shown inconsistent during drug treatment for adults. Over the last few years, a protocol on systematic audiologic monitoring for ototoxicity in adults receiving chemotherapeutic treatments has been developed by the audiology department of our hospital. Due to limited resources to manage a high volume of patients, the audiology department was unable to fully implement the protocol. The main objective of this project was to evaluate the most suitable approach to manage audiologic monitoring in adults receiving cisplatin. Method Literature searches were conducted in several databases and grey literature to retrieve data on audiologic monitoring and cisplatin ototoxicity in adults including systematic reviews, guidelines and primary studies. Two review authors (MB and SL) independently performed document selection, methodological quality assessment and data extraction. A web-based survey was carried out in 2017 to document the clinical practice of audiologists in Québec for cisplatin ototoxicity management. A local survey in our institution was also performed to describe roles and involvement of pharmacists, hematologist-oncologists and specialized oncology nurses relative to cisplatin ototoxicity monitoring. Data extraction from Electronic Patient Record (EPR) were performed to review local practice regarding cisplatin ototoxicity monitoring in 125 adults treated from 2015 to 2017. Evidence-based review and local perspective were shared with an interdisciplinary group including oncologists, audiologists, pharmacists, oncology nurses and hospital managers. Results Six publications specific to cisplatin ototoxicity monitoring in adults were retrieved. Clinical practice guidelines suggested that an audiologic monitoring program should be available for all patients including repeated audiologic tests. Results from literature and Quebec web-based survey showed that audiologic monitoring programs are often unknown and not always enforced in clinical practice. In our hospital, data from the EPR suggested that audiologic consultation before starting, during or after stopping chemotherapeutic treatments was performed in 35 patients (28%), mainly for head and neck cancer, and high cisplatine dose. Results from the local survey highlighted concerns about the chemotherapy treatment decision making process when ototoxicity is diagnosed and the importance of communication between audiologists, oncologists, pharmacists, nurses and patients. Threshold level to interpret audiologic tests was also among the concerns because of the risk of overestimating patients having nonsignificant hearing loss, and the consequences of less effective anticancer treatment options. Conclusions Results suggest that audiologic monitoring in adults under cisplatin cannot rely only on audiometric testing by audiologists. An adapted approach based on an interdisciplinary collaboration, patient’s individual preferences as well as therapeutic alternatives should be the preferred way to promote share-decision making on cisplatin ototoxicity risks, preventive measures and auditory rehabilitation available.
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 | 0.055 | 0.184 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".