1. Predicting Hearing Loss in Testicular Cancer Patients after Cisplatin-Based Chemotherapy
- Author
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Garcia, Sara L., Lauritsen, Jakob, Christiansen, Bernadette K., Hansen, Ida F., Bandak, Mikkel, Dalgaard, Marlene D., Daugaard, Gedske, Gupta, Ramneek, Garcia, Sara L., Lauritsen, Jakob, Christiansen, Bernadette K., Hansen, Ida F., Bandak, Mikkel, Dalgaard, Marlene D., Daugaard, Gedske, and Gupta, Ramneek
- Abstract
Testicular cancer is predominantly curable, but the long-term side effects of chemotherapy have a severe impact on life quality. In this research study, we focus on hearing loss as a part of overall chemotherapy-induced ototoxicity. This is a unique approach where we combine clinical data from the acclaimed nationwide Danish Testicular Cancer (DaTeCa)-Late database. Clinical and genetic data on 433 patients were collected from hospital files in October 2014. Hearing loss was classified according to the FACT/GOG-Ntx-11 version 4 self-reported Ntx6. Machine learning models combining a genome-wide association study within a nested cross-validated logistic regression were applied to identify patients at high risk of hearing loss. The model comprising clinical and genetic data identified 67% of the patients with hearing loss; however, this was with a false discovery rate of 49%. For the non-affected patients, the model identified 66% of the patients with a false omission rate of 19%. An area under the receiver operating characteristic (ROC-AUC) curve of 0.73 (95% CI, 0.71–0.74) was obtained, and the model suggests genes SOD2 and MGST3 as important in improving prediction over the clinical-only model with a ROC-AUC of 0.66 (95% CI, 0.65–0.66). Such prediction models may be used to allow earlier detection and prevention of hearing loss. We suggest a possible biological mechanism for cisplatin-induced hearing loss development. On confirmation in larger studies, such models can help balance treatment in clinical practice.
- Published
- 2023