Natalizumab Improves Language Processing in Patients With Multiple Sclerosis

From Medscape Medical News - by: Jim Kling

July 7, 2010 (San Antonio, Texas) — Treatment with natalizumab (Tysabri, Biogen Idec and Elan) leads to improved language processing and retrieval of newly learned verbal material in patients with multiple sclerosis (MS), according to research presented here at the Consortium of Multiple Sclerosis Centers 24th Annual Conference and the Third Joint Meeting of Americas Committee for Treatment and Research in Multiple Sclerosis.

The researchers compared the effects of natalizumab with treatment with other disease-modifying therapies in patients with MS. The study included 46 patients taking natalizumab (mean ± SD age, 43.2 ± 9.1 years; mean ± SD years of education, 15.1 ± 2.5 years; 76% female; mean ± SD intertest interval, 14.9 ± 3.9 months; mean ± SD Expanded Disability Status Scale [EDSS] score, 3.8 ± 2.2; and disease duration <5 years, 9%; 5 – 10 years, 50%; and >10 years, 41%).

Investigators with South Shore Neurologic Associates of Patchogue, New York, and NeuroTrax Corporation of Newark, New Jersey, tested patients with a 30- to 60-minute computerized test designed to assess mild cognitive impairment (Mindstreams, NeuroTrax Corp). Patients were tested once, either before treatment or early in the treatment cycle (0-3 infusions), and again after the completion of more extended treatment (>9 infusions).

The comparison group included 37 stable patients, of whom 10 were receiving Avonex, 5 Betaseron, 5 Rebif, 5 CombiRX, 4 Copaxone, and 8 no treatment. In this group, mean ± SD age was 45.8 ± 10.8 years; mean ± SD years of education was 14.9 ± 3.6 years; 78% were female; mean ± SD intertest interval was 18.3 ± 5.0 months; mean ± SD EDSS score was 2.8 ± 1.8; and disease duration was less than 5 years for 32%, 5 to 10 years for 43%, and more than 10 years for 24%.

The researchers used repeated-measures analysis of variance (ANOVA) to assess improvements in EDSS, age- and education-adjusted cognitive domain scores, and raw data from individual tests. To measure effect size, the researchers computed Cohen's d (<.05 [1-tailed] was considered significant). The team used mixed-model ANOVA, controlled for EDSS, to analyze change over time between the groups.

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