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Systematic Literature Review to Assess Economic Evaluations in Spinal Muscular Atrophy (SMA)

Noman Paracha, Pollyanna Hudson, Stephen Mitchell and C. Simone Sutherland ()
Additional contact information
Noman Paracha: F. Hoffmann-La Roche Ltd
Pollyanna Hudson: Mtech Access Limited
Stephen Mitchell: Mtech Access Limited
C. Simone Sutherland: F. Hoffmann-La Roche Ltd

PharmacoEconomics, 2022, vol. 40, issue 1, No 6, 69-89

Abstract: Abstract Background Spinal muscular atrophy (SMA) is a rare, progressive neuromuscular disease that affects individuals with a broad age range. SMA is typically characterised by symmetrical muscle weakness but is also associated with cardiac defects, life-limiting impairments in respiratory function and bulbar function defects that affect swallowing and speech. Despite the advent of three innovative disease-modifying therapies (DMTs) for SMA, the cost of DMTs in addition to the costs of standard of care can be a barrier to treatment access for patients. Health Technology Assessment (HTA) decision makers evaluate the cost effectiveness of a new treatment before making a reimbursement decision. Objective The primary objective was to conduct a systematic literature review (SLR) to identify the modelling approaches used in economic evaluations that assess current approved treatments in SMA, with a secondary objective to widen the scope and identify economic evaluations assessing other (non-SMA) neuromuscular disorders. Methods An SLR was performed to identify available economic evaluations associated with any type of SMA (Type 1, 2, 3 and/or 4). Economic evaluations associated with other (non-SMA) neuromuscular disorders were identified but not further analysed. Electronic searches were conducted in Embase, MEDLINE, Evidence-Based Medicine Reviews and EconLit via the Ovid platform in August 2019, and were supplemented by searches of the grey literature (reference lists, conference proceedings, global HTA body websites and other relevant sources). Eligibility criteria were based on the population, interventions, comparators and outcomes (PICO) framework. Quality assessment of full publications was conducted with reference to a published checklist. Results Nine publications covering eight unique studies met all eligibility criteria for inclusion in the SLR, including four conference abstracts, two peer-reviewed original research articles and three HTA submissions (conducted in Canada, the US and the UK). Evaluations considered patients with early infantile-onset (most likely to develop Type 1 or Type 2 SMA), later-onset SMA and both infantile- and later-onset SMA. Data for the identified economic models were collected from literature reviews and relatively short-term clinical trials. Several intent-to-treat clinical trial populations were used in the studies, which resulted in variation in cycle length and different outcome measures to determine clinical efficacy. The results of the quality assessment on the five full-text, peer-reviewed publications found that they generally provided clear descriptions of objectives, modelling methods and results. However, key decisions, such as choice of economic evaluation, model type and choice of variables for sensitivity analysis, were often not adequately justified. Conclusions This SLR highlights the need for economic evaluations in SMA to better align in modelling approaches with respect to (i) consistency in model structure and use of motor function milestones as health states; (ii) consensus on measuring quality of life to estimate utilities; (iii) consistency in data collection by registries; and (iv) consensus on SMA-type classification and endpoints that determine intervention efficacy. Future economic evaluations should also incorporate the review group critiques of previous HTA submissions relating to data inputs and approaches to modelling and should include patient data reflective of the SMA population being modelled. Economic evaluations would also be improved with inclusion of long-term efficacy and safety data from clinical trials and valid patient and caregiver utility data.

Date: 2022
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DOI: 10.1007/s40273-021-01095-6

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