ECTRIMS eLearning

Long term outcome after presentation with a clinically isolated syndrome: evidence for therapeutic modulation
Author(s):
M. Tintore
M. Tintore
Affiliations:
ECTRIMS Learn. Tintoré M. 09/16/16; 147032; 185
Mar Tintoré
Mar Tintoré
Contributions Biography
Abstract

Abstract: 185

Type: Oral

In a long-lasting disease duration, such MS, observational studies are key to study early predictors of poor outcome in longer term. Accurately identifying prognosis at the early stages of the disease and determining the degree of disability that patients are likely to develop over the mid- to long-term is crucial for providing more individualized treatment counselling. We have determined predictors of EDSS score change, including treatment effects, in a large, real-world, prospectively acquired clinically isolated syndromes (CIS) cohort. We have developed a dynamic model for predicting long-term prognosis using classical modelling and classification and regression trees. We have further studied the role of disease modifying treatment (DMT) in modifying the risk of disability accumulation using propensity scores and structural marginal models. The contribution of hormonal and environmental factors will also be discussed.

Disclosure: M Tintore has received compensation for consulting services and speaking honoraria from Almirall, Bayer-Schering, Biogen-Idec, Genzyme, Merck-Serono, Novartis, Sanofi, Roche and Teva

Abstract: 185

Type: Oral

In a long-lasting disease duration, such MS, observational studies are key to study early predictors of poor outcome in longer term. Accurately identifying prognosis at the early stages of the disease and determining the degree of disability that patients are likely to develop over the mid- to long-term is crucial for providing more individualized treatment counselling. We have determined predictors of EDSS score change, including treatment effects, in a large, real-world, prospectively acquired clinically isolated syndromes (CIS) cohort. We have developed a dynamic model for predicting long-term prognosis using classical modelling and classification and regression trees. We have further studied the role of disease modifying treatment (DMT) in modifying the risk of disability accumulation using propensity scores and structural marginal models. The contribution of hormonal and environmental factors will also be discussed.

Disclosure: M Tintore has received compensation for consulting services and speaking honoraria from Almirall, Bayer-Schering, Biogen-Idec, Genzyme, Merck-Serono, Novartis, Sanofi, Roche and Teva

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