Costs of Illness of Spinal Muscular Atrophy: A Systematic Review

Objectives The objective of our study was to conduct a systematic literature review of estimates of costs of illness of spinal muscular atrophy (SMA). Methods We searched MEDLINE (through PubMed), CINAHL, Embase, Web of Science, National Health Service Economic Evaluation Database, and the National Health Service Health Technology Assessment Database for studies published from inception up until 31 August, 2020, reporting direct medical, direct non-medical, and/or indirect costs of any phenotype of SMA. Two reviewers independently screened records for eligibility, extracted the data, and assessed studies for risk of bias using the Newcastle-Ottawa Scale. Costs were adjusted and converted to 2018 US dollars. Results The search identified 14 studies from eight countries (Australia, France, Germany, Italy, Spain, Sweden, the UK, and the USA). The mean per-patient annual direct medical cost of illness was estimated at between $3320 (SMA type III, Italy) and $324,410 (SMA type I, USA), mean per-patient annual direct non-medical cost between $25,880 (SMA types I-III, Spain) and $136,800 (SMA type I, Sweden), and mean per-patient annual indirect cost between $9440 (SMA type I, Germany) and $74,910 (SMA type II, Australia). Most studies exhibited a risk of bias. Conclusions The current body of evidence of costs of illness of SMA is relatively scarce and characterized by considerable variability across geographical settings and disease phenotypes. Our review provides data pertaining to the economic impact of SMA, which is of particular relevance in light of emerging treatments and ongoing research in this field, and underscores the substantial unmet medical need in this patient population.

Automated summary

This study conducted a systematic literature review on estimates of costs of illness of spinal muscular atrophy (SMA) from multiple countries, revealing significant variations in costs across different countries and disease types, with most studies exhibiting bias risks.