Search results for "data-driven algorithm"
showing 2 items of 2 documents
Towards a validated definition of the clinical transition to secondary progressive multiple sclerosis: A study from the Italian MS Register.
2022
Background: Definitions for reliable identification of transition from relapsing-remitting multiple sclerosis (MS) to secondary progressive (SP)MS in clinical cohorts are not available. Objectives: To compare diagnostic performances of two different data-driven SPMS definitions. Methods: Data-driven SPMS definitions based on a version of Lorscheider’s algorithm (DDA) and on the EXPAND trial inclusion criteria were compared, using the neurologist’s definition (ND) as gold standard, in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), Akaike information criterion (AIC) and area under the curve (AUC). Results: A cohort of 10,240 MS patients wi…
Transition to secondary progression in relapsing-onset multiple sclerosis: Definitions and risk factors
2021
Background: No uniform criteria for a sensitive identification of the transition from relapsing–remitting multiple sclerosis (MS) to secondary-progressive multiple sclerosis (SPMS) are available. Objective: To compare risk factors of SPMS using two definitions: one based on the neurologist judgment (ND) and an objective data-driven algorithm (DDA). Methods: Relapsing-onset MS patients ( n = 19,318) were extracted from the Italian MS Registry. Risk factors for SPMS and for reaching irreversible Expanded Disability Status Scale (EDSS) 6.0, after SP transition, were estimated using multivariable Cox regression models. Results: SPMS identified by the DDA ( n = 2343, 12.1%) were older, more disa…