XXXX diagnostics and predictors of conversion to CDMS.

@entity1 @entity17 @entity7995 @entity15 @entity922
@entity922 ( @entity922 ) is a term used to define an episode suggestive of central nervous system (CNS) inflammatory @entity17 . The majority of @entity922 will evolve to @entity15 ( @entity15 ), a chronic disease characterised by further relapses and accumulation of disability. Current evidence suggests that disease modifying treatment (DMT) should be started at early stages since it is likely to have a significant impact on the evolution of the disease. Thus, accurately identifying which @entity1 will remain as @entity922 or which will develop @entity15 and, above all, determining the degree of disability they could develop over the mid- to long term is considered crucial for a more individualized treatment. Natural history studies have shown that a younger age at disease onset is related to a higher risk of conversion to clinically definite @entity15 (CDMS) and that male gender is associated to a higher disability accumulation as measured by the Kurtzke Expanded Disability Status Scale (EDSS). Among clinical factors, @entity922 @entity1 presenting with an @entity7995 have been related to a lower risk of developing both @entity15 and disability accumulation in comparison to @entity922 affecting other topographies. Regarding biological factors, a recent meta-analysis showed that presence of IgG oligoclonal bands (OB) increases both the risk of having a second attack and the risk of disability accumulation. To date, brain MRI remains the most reliable prognostic marker for developing @entity15 or disability. It has been demonstrated that a higher number of brain T2 lesions or Barkhof criteria (BC) on baseline MRI increases the risk of developing @entity15 and disability in the mid- to long term. However, although the abovementioned natural history studies are indeed based on large multicentre cohorts with long follow-up, they have a number of limitations: they usually comprised data obtained both retrospectively and prospectively, which could lead to information bias. Baseline and follow-up visits do not follow a standardized protocol, compromising the homogenization among the different centres of the data acquired. Absence of MRI data is frequent and when present, a systematic MRI protocol is lacking. These limitations often result in the fact that MRI and OB have not been taken into account as joint covariates in the models. Finally, quantification of @entity1 lost to follow-up and its causes are not registered, leading to survival bias. On the other hand, the longitudinal MRI cohorts have a small sample size, follow-up is not regular, and @entity7995 is frequently over-represented, deeming subgroup analyses impossible. Overcoming some of these limitations, I will present the Barcelona inception cohort study on 1000 @entity922 . We have tried to identify and stratify which baseline demographic, clinical, radiological or biological factors predict @entity15 development and disability accumulation in a unique multivariate approach on a large prospective cohort.
