Predicting long-term disability outcomes in patients with MS treated with teriflunomide in TEMSO

Maria Pia Sormani, Philippe Truffinet, Karthinathan Thangavelu, Pascal Rufi, Catherine Simonson, Nicola De Stefano, Maria Pia Sormani, Philippe Truffinet, Karthinathan Thangavelu, Pascal Rufi, Catherine Simonson, Nicola De Stefano

Abstract

Objective: To predict long-term disability outcomes in TEMSO core (NCT00134563) and extension (NCT00803049) studies in patients with relapsing forms of MS treated with teriflunomide.

Methods: A post hoc analysis was conducted in a subgroup of patients who received teriflunomide in the core study, had MRI and clinical relapse assessments at months 12 (n = 552) and 18, and entered the extension. Patients were allocated risk scores for disability worsening (DW) after 1 year of teriflunomide treatment: 0 = low risk; 1 = intermediate risk; and 2-3 = high risk, based on the occurrence of relapses (0 to ≥2) and/or active (new and enlarging) T2-weighted (T2w) lesions (≤3 or >3) after the 1-year MRI. Patients in the intermediate-risk group were reclassified as responders or nonresponders (low or high risk) according to relapses and T2w lesions on the 18-month MRI. Long-term risk (7 years) of DW was assessed by Kaplan-Meier survival curves.

Results: In patients with a score of 2-3, the risk of 12-week-confirmed DW over 7 years was significantly higher vs those with a score of 0 (hazard ratio [HR] = 1.96, p = 0.0044). Patients reclassified as high risk at month 18 (18.6%) had a significantly higher risk of DW vs those in the low-risk group (81.4%; HR = 1.92; p = 0.0004).

Conclusions: Over 80% of patients receiving teriflunomide were classified as low risk (responders) and had a significantly lower risk of DW than those at increased risk (nonresponders) over 7 years of follow-up in TEMSO. Close monitoring of relapses and active T2w lesions after short-term teriflunomide treatment predicts a differential rate of subsequent DW long term.

Clinicaltrialsgov identifier: TEMSO, NCT00134563; TEMSO extension, NCT00803049.

Figures

Figure 1. Scoring assessment
Figure 1. Scoring assessment
T2w = T2-weighted.
Figure 2. Patient disposition
Figure 2. Patient disposition
Figure 3. Probability of disability worsening by…
Figure 3. Probability of disability worsening by scoring classification
(A) At the end of year 1 and (B) on reclassification of patients with intermediate score 1, 6 months later. *Nonresponders vs responders. HR = hazard ratio.
Figure 4. Distribution of patients by scoring…
Figure 4. Distribution of patients by scoring classification
(A) At the end of year 1 and (B) on reclassification of patients with score 1, 6 months later.
Figure 5. Effect of MRI lesions on…
Figure 5. Effect of MRI lesions on the probability of disability worsening in patients with no relapses
HR = hazard ratio; T2w = T2-weighted.

References

    1. Sormani MP, De Stefano N. Defining and scoring response to IFN-beta in multiple sclerosis. Nat Rev Neurol 2013;9:504–512.
    1. Ziemssen T, De Stefano N, Pia Sormani M, Van Wijmeersch B, Wiendl H, Kieseier BC. Optimizing therapy early in multiple sclerosis: an evidence-based view. Mult Scler Relat Disord 2015;4:460–469.
    1. Rio J, Comabella M, Montalban X. Predicting responders to therapies for multiple sclerosis. Nat Rev Neurol 2009;5:553–560.
    1. Rio J, Castillo J, Rovira A, et al. . Measures in the first year of therapy predict the response to interferon beta in MS. Mult Scler 2009;15:848–853.
    1. Rio J, Rovira A, Tintore M, et al. . Evaluating the response to glatiramer acetate in relapsing-remitting multiple sclerosis (RRMS) patients. Mult Scler 2014;20:1602–1608.
    1. Romeo M, Martinelli V, Rodegher M, et al. . Validation of 1-year predictive score of long-term response to interferon-beta in everyday clinical practice multiple sclerosis patients. Eur J Neurol 2015;22:973–980.
    1. Sormani MP, Rio J, Tintore M, et al. . Scoring treatment response in patients with relapsing multiple sclerosis. Mult Scler 2013;19:605–612.
    1. Sormani MP, Gasperini C, Romeo M, et al. . Assessing response to interferon-beta in a multicenter dataset of patients with MS. Neurology 2016;87:134–140.
    1. O'Connor P, Wolinsky JS, Confavreux C, et al. . Randomized trial of oral teriflunomide for relapsing multiple sclerosis. N Engl J Med 2011;365:1293–1303.
    1. McDonald WI, Compston A, Edan G, et al. . Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis. Ann Neurol 2001;50:121–127.
    1. O'Connor P, Comi G, Freedman MS, et al. . Long-term safety and efficacy of teriflunomide: nine-year follow-up of the randomized TEMSO study. Neurology 2016;86:920–930.
    1. Giovannoni G, Turner B, Gnanapavan S, Offiah C, Schmierer K, Marta M. Is it time to target no evident disease activity (NEDA) in multiple sclerosis? Mult Scler Relat Disord 2015;4:329–333.
    1. Havrdova E, Galetta S, Stefoski D, Comi G. Freedom from disease activity in multiple sclerosis. Neurology 2010;74(suppl 3):S3–S7.
    1. Romeo M, Martinelli-Boneschi F, Rodegher M, et al. . Clinical and MRI predictors of response to interferon-beta and glatiramer acetate in relapsing-remitting multiple sclerosis patients. Eur J Neurol 2013;20:1060–1067.
    1. Prosperini L, Gallo V, Petsas N, Borriello G, Pozzilli C. One-year MRI scan predicts clinical response to interferon beta in multiple sclerosis. Eur J Neurol 2009;16:1202–1209.
    1. Sormani MP, Li DK, Bruzzi P, et al. . Combined MRI lesions and relapses as a surrogate for disability in multiple sclerosis. Neurology 2011;77:1684–1690.
    1. Lattanzi S, Danni M, Cerqua R, Taffi R, Provinciali L, Silvestrini M. Prediction of disability progression in fingolimod-treated patients. J Neurol Sci 2015;358:432–434.
    1. Sormani M, Signori A, Stromillo M, De Stefano N. Refining response to treatment as defined by the modified Rio score. Mult Scler 2013;19:1246–1247.

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