Comparative effectiveness of early natalizumab treatment in JC virus-negative relapsing-remitting multiple sclerosis
- PMID: 23725360
Comparative effectiveness of early natalizumab treatment in JC virus-negative relapsing-remitting multiple sclerosis
Abstract
Objectives: To estimate the long-term comparative effectiveness of first-line treatment in patients negative for anti-JC virus (JCV) antibodies with glatiramer acetate (GA), fingolimod, or natalizumab for relapsing-remitting multiple sclerosis (RRMS).
Study design: We developed a simulation model to estimate the average 20-year clinical risks and benefits of GA, fingolimod, and natalizumab for RRMS patients initially negative for anti-JCV antibodies.
Methods: Model inputs included published natural history progressions of the Expanded Disability Status Scale (EDSS), treatment effects from randomized controlled trials on slowing disease progression and reducing relapse rates, risk of progressive multifocal leukoencephalopathy (PML), and utility preference scores. Outputs were long-term risks (PML risk and other non-PML risks), benefits (average relapse rate and time to disability [EDSS >7]), and quality-adjusted life years (QALYs).
Results: Compared with GA, natalizumab resulted in 4.6 fewer relapses, 0.6 more years of disability free time, 0.0165 more cases of PML per treated patient, and an incremental 1.2 QALYs gained. Compared with fingolimod, natalizumab resulted in 1.7 fewer relapses, 0.1 more years of disability free time, 0.0165 more cases of PML per treated patient, and an incremental 0.4 QALYs gained. The probability that incremental QALYs favored natalizumab over GA was 0.963 and natalizumab over fingolimod was 0.720.
Conclusions: Average QALYs, a measure that aggregates across risks and benefits, favored natalizumab, suggesting more aggressive early intervention with natalizumab in the negative anti-JCV population. For certain decision makers, more evidence may be needed to further reduce the uncertainty in these comparative projections prior to making population-based adoption decisions.
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