Early Health Economic Modeling of Novel Therapeutics in Age-Related Hearing Loss

Author:

Landry Evie C.,Scholte Mirre,Su Matthew P.,Horstink Yvette,Mandavia Rishi,Rovers Maroeska M.,Schilder Anne G. M.

Abstract

BackgroundHealth systems face challenges to accelerate access to innovations that add value and avoid those unlikely to do so. This is very timely to the field of age-related sensorineural hearing loss (ARHL), where a significant unmet market need has been identified and sizeable investments made to promote the development of novel hearing therapeutics (NT). This study aims to apply health economic modeling to inform the development of cost-effective NT.MethodsWe developed a decision-analytic model to assess the potential costs and effects of using regenerative NT in patients ≥50 with ARHL. This was compared to the current standard of care including hearing aids and cochlear implants. Input data was collected from systematic literature searches and expert opinion. A UK NHS healthcare perspective was adopted. Three different but related analyses were performed using probabilistic modeling: (1) headroom analysis, (2) scenario analyses, and (3) threshold analyses.ResultsThe headroom analysis shows an incremental net monetary benefit (iNMB) of £20,017[£11,299–£28,737] compared to the standard of care due to quality-adjusted life-years (QALY) gains and cost savings. Higher therapeutic efficacy and access for patients with all degrees of hearing loss yields higher iNMBs. Threshold analyses shows that the ceiling price of the therapeutic increases with more severe degrees of hearing loss.ConclusionNT for ARHL are potentially cost-effective under current willingness-to-pay (WTP) thresholds with considerable room for improvement in the current standard of care pathway. Our model can be used to help decision makers decide which therapeutics represent value for money and are worth commissioning, thereby paving the way for urgently needed NT.

Funder

UCLH Biomedical Research Centre

Publisher

Frontiers Media SA

Subject

General Neuroscience

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