| Literature DB >> 24972678 |
Aaron E Miller1, Richard Macdonell, Giancarlo Comi, Mark S Freedman, Ludwig Kappos, Mathias Mäurer, Tomas P Olsson, Jerry S Wolinsky, Sylvie Bozzi, Catherine Dive-Pouletty, Paul W O'Connor.
Abstract
Teriflunomide is a once-daily oral immunomodulator approved for the treatment of relapsing-remitting multiple sclerosis. This post hoc analysis of the Phase III TOWER study evaluated the effects of teriflunomide treatment on five severe relapse outcomes: relapses with sequelae defined by an increase in Expanded Disability Status Scale (EDSS)/functional system (FS) score (sequelae-EDSS/FS) 30 days post relapse; relapses with sequelae defined by the investigator (sequelae-investigator); relapses leading to hospitalization; relapses treated with intravenous corticosteroids; and intense relapses using the definition of Panitch et al. from the EVIDENCE study based on specified increases in EDSS for severe relapses. Adjusted annualized rates for the five severe relapse outcomes were derived using a Poisson model with robust error variance, with treatment, baseline EDSS strata and region as covariates. Compared with placebo, teriflunomide significantly reduced annualized rates of relapses with sequelae-EDSS/FS [14 mg, 36.6 % (p = 0.0021); 7 mg, 31.3 % (p = 0.0104)] and sequelae-investigator [14 mg only, 53.5 % (p = 0.0004)], relapses leading to hospitalization [14 mg only, 33.6 % (p = 0.0155)], relapses requiring intravenous corticosteroids [14 mg, 35.7 % (p = 0.0002); 7 mg, 21.5 % (p = 0.0337)], and intense relapses [14 mg only, 52.5 % (p = 0.0015)]. Patients treated with teriflunomide 14 mg spent significantly fewer nights in hospital for relapse (p = 0.009) and had lower annualized rates of all hospitalizations (p = 0.030). Taken together, the positive effects of teriflunomide on severe relapses indicate that teriflunomide may reduce relapse-related healthcare costs.Entities:
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Year: 2014 PMID: 24972678 PMCID: PMC4155167 DOI: 10.1007/s00415-014-7395-7
Source DB: PubMed Journal: J Neurol ISSN: 0340-5354 Impact factor: 4.849
Fig. 1Adjusted annualized rates for each relapse outcome analyzed in TOWER: a relapses with sequelae-EDSS/FS; b relapses with sequelae-investigator; c relapses leading to hospitalization; d relapses requiring IV corticosteroids; e intense relapses (intense relapses using the definition of Panitch et al. from the EVIDENCE study, based on specified increases in EDSS for severe relapses [14]). EDSS Expanded Disability Status Scale, FS functional system, IV intravenous
Fig. 2Adjusted annualized rate of relapse with sequelae-EDSS/FS over time in TOWER. EDSS Expanded Disability Status Scale, FS functional system
Adjusted annualized number of nights spent in hospital for relapse per patient and adjusted annualized rate of all hospitalization for relapse or serious AE (TOWER modified-ITT population)
| Teriflunomide 14 mg ( | Teriflunomide 7 mg ( | Placebo ( | |
|---|---|---|---|
| Adjusted annualized number of nights spent in hospital for relapse per patienta | |||
| Estimate (95 % CI) | 0.81 (0.55, 1.21) | 1.10 (0.61, 1.99) | 1.51 (1.00, 2.27) |
| Relative risk vs. placebo (95 % CI) | 0.54 (0.34, 0.86) | 0.73 (0.41, 1.30) | |
| | 0.0086 | 0.2816 | – |
| Adjusted annualized rate of all hospitalization for relapse or serious AEb | |||
| Adjusted annualized rate (95 % CI) | 0.21 (0.17, 0.27) | 0.25 (0.20, 0.31) | 0.29 (0.23, 0.37) |
| Relative risk vs. placebo (95 % CI) | 0.72 (0.54, 0.97) | 0.86 (0.64, 1.15) | – |
| | 0.0299 | 0.3145 | – |
AE adverse event, CI confidence interval, ITT intention to treat
aDerived using Poisson regression model with robust error variance with total number of nights of hospitalization for relapse as response variable; treatment, Expanded Disability Status Scale strata at baseline and region as covariates; and log-transformed patient years as an offset variable
bDerived using Poisson regression model with robust error variance with total number of nights spent in hospital (for relapse or AE) as response variable; treatment, Expanded Disability Status Scale strata at baseline and region as covariates; and log-transformed patient years as an offset variable