Characterizing cognitive deficits and potential predictors in multiple sclerosis: A large nationwide study applying Brief International Cognitive Assessment for Multiple Sclerosis in standard clinical care. Issue 3 (13th February 2020)

• Record Type: Journal Article
• Authors: Renner, Alina; Baetge, Sharon J.; Filser, Melanie; Ullrich, Sebastian; Lassek, Christoph; Penner, Iris‐Katharina
• Is Part Of: Journal of neuropsychology. Volume 14:Issue 3(2020)
• Page Start: 347
• Page End: 369
• Publication Date: 2020-02-13
• Subjects: multiple sclerosis -- cognitive impairment -- BICAMS -- risk factors -- disease subtype -- disease duration; Neuropsychology -- Periodicals; Brain -- Diseases -- Psychological aspects -- Periodicals; 612.82305
• DOI: 10.1111/jnp.12202
• Languages: English
• ISSNs: 1748-6645

Abstract

Abstract : With the proposal of the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) battery, the need to screen for cognitive deficits within standard clinical care of patients with multiple sclerosis (MS) has been acknowledged. Data regarding how patient characteristics might predict low cognitive performance and therefore require particularly close monitoring is, however, limited so far. We investigated a large, nationwide patient cohort from ambulatory settings, representing the typical distribution of different subtypes, levels of physical disability, and disease durations. Besides cognitive testing with BICAMS, additional sampling of multiple demographics and clinical variables allowed us to characterize general and domain‐specific prevalence patterns of cognitive impairment (CI) as well as to delineate which factors are associated with cognitive performance. In a total of 1, 094 patients, CI was present in 28% (using a conservative cut‐off of the 5th percentile below normative values), with information‐processing speed being most frequently affected. Impairment was overall higher in patients with primary progressive (PPMS) and secondary progressive MS than in patients with relapsing–remitting (RR)MS. Regression modelling revealed that disease subtype (i.e., PPMS), long disease duration, high physical disability, unemployment, low educational level, high age, male sex, and the absence of current disease‐modifying treatment were important predictors for worse BICAMS' test performance. These results emphasize the importance of continuous cognitive assessment during regular neurological follow‐up visits, with a particular focus on patients being identified as high‐risk subjects for CI according to the reported factors.