51. Economics of hematopoietic stem cell transplant in immune-mediated neurologic autoimmune diseases.
- Author
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Hughes SL, Prettyjohns MJ, Snowden JA, and Sharrack B
- Subjects
- Humans, Cost-Benefit Analysis, Autoimmune Diseases of the Nervous System economics, Autoimmune Diseases of the Nervous System therapy, Autoimmune Diseases of the Nervous System immunology, Hematopoietic Stem Cell Transplantation economics, Hematopoietic Stem Cell Transplantation methods, Hematopoietic Stem Cell Transplantation adverse effects
- Abstract
Autologous hematopoietic stem cell transplantation (AHSCT) is a therapeutic procedure for autoimmune diseases which suppresses inflammation and resets the immune system, thereby halting disease activity and disability progression in treatment-resistant patients. This chapter reviews existing guidelines and health economic evaluations of AHSCT for multiple sclerosis (MS) and presents a cost-utility analysis from the UK NHS and personal social services perspective comparing AHSCT with disease-modifying therapies (DMTs) in patients with highly active relapsing-remitting MS (RRMS) based on the only published randomized controlled trial, "MIST," in this population. Over a 5-year time horizon, AHSCT was dominant (more effective and less costly) over the DMTs in MIST. At a threshold of £20,000 per QALY, there was a 100% probability that AHSCT was cost-effective. This result is explained by the high ongoing costs of DMTs compared with the up-front cost of AHSCT, combined with the high effectiveness of AHSCT. When compared with natalizumab, the result did not change; AHSCT remained dominant. These results support current guideline recommendations regarding AHSCT for highly active RRMS. The cost-effectiveness of AHSCT in progressive and aggressive MS and other immune-mediated neurologic diseases remains uncertain due to a lack of health economic analyses, reflecting the limited clinical evidence base., (Copyright © 2024 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.)
- Published
- 2024
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