Cochlear Implantation in Neurofibromatosis Type 2: Experience From the UK Neurofibromatosis Type 2 Service. Issue 5 (24th June 2022) - Smith, Matthew E.; Edmiston, Rachel; Trudel, Mathieu; Freeman, Simon; Stapleton, Emma; Axon, Patrick; Donnelly, Neil; Tysome, James R.; Bance, Manohar; Obholzer, Rupert; Jiang, Dan; Mackeith, Samuel; et al.
Abstract : Objective: To review the outcomes of cochlear implants (CI) in patients with neurofibromatosis type 2 (NF2) in a large cohort, and identify factors associated with poor hearing benefit. Study Design: Fifteen-year retrospective national observational case series. Setting: United Kingdom regional NF2 multidisciplinary teams. Patients: Consecutive patients with NF2 receiving a CI. Interventions: CI for hearing rehabilitation. Main outcome measures: 1) Audiometric performance at 9 to 12 months after implantation using City University of New York (CUNY) sentence recognition score, and Bamford- Kowal-Bench (BKB) word recognition score in quiet (BKBq), and in noise (BKBn). 2) CI use at most recent review. Results: Sixty four consecutive patients, median age 43 years, were included. Nine to 12 months mean audiometric scores were: CUNY 60.9%, BKBq 45.8%, BKBn 41.6%. There was no difference in audiometric outcomes between VS treatment modalities. At most recent review (median 3.6 years from implantation), 84.9% with device in situ/available data were full or part-time users. Between 9 and 12 months and most recent review there was an interval reduction in mean audiometric scores: CUNY −12.9%, BKBq −3.3%, BKBn −4.9%. Larger tumor size and shorter duration of profound hearing loss were the only variables associated with poorer audiometric scores. Tumor growth at the time of surgery was the only variable associated with CI non-use. Individual patient response was highly variable. Conclusions: CI can provide significant and sustained auditory benefits to patients with NF2 independent of tumor treatment modality, with the majority of those implanted becoming at least part-time users. Larger datasets are required to reliably assess the role of independent variables.