Longitudinal Trajectories of Digital Cognitive Biomarkers for Multiple Sclerosis

被引:0
|
作者
Foong, Yi Chao [1 ,2 ,3 ,4 ]
Merlo, Daniel [1 ,3 ]
Gresle, Melissa [1 ,2 ,5 ]
Zhu, Chao [1 ]
Buzzard, Katherine [3 ,5 ]
Lechner-Scott, Jeannette [6 ,7 ]
Barnett, Michael [8 ,9 ]
Wang, Chenyu [8 ,9 ]
Taylor, Bruce V. [10 ]
Kalincik, Tomas [11 ,12 ]
Kilpatrick, Trevor [12 ,13 ]
Darby, David [1 ,2 ,3 ]
Dobay, Pamela [14 ]
van Beek, Johan [14 ]
Hyde, Robert [14 ]
Simpson-Yap, Steve [10 ,11 ,13 ,15 ]
Butzkueven, Helmut [1 ,2 ]
van Der Walt, Anneke [1 ,2 ]
机构
[1] Monash Univ, Cent Clin Sch, Dept Neurosci, Melbourne, Vic, Australia
[2] Alfred Hlth, Melbourne, Vic, Australia
[3] Eastern Hlth, Melbourne, Vic, Australia
[4] Royal Hobart Hosp, Hobart, Tas, Australia
[5] Melbourne Hlth, Melbourne, Vic, Australia
[6] Univ Newcastle, Newcastle, NSW, Australia
[7] Hunter New England Hlth, Newcastle, NSW, Australia
[8] Univ Sydney, Brain & Mind Ctr, Sydney, NSW, Australia
[9] Sydney Neuroimaging Anal Ctr, Camperdown, NSW, Australia
[10] Univ Tasmania, Menzies Inst Med Res, MS Flagship, Hobart, Tas, Australia
[11] Univ Melbourne, Dept Med, CORE, Melbourne, Vic, Australia
[12] Royal Melbourne Hosp, Neuroimmunol Ctr, Dept Neurol, Melbourne, Vic, Australia
[13] Univ Melbourne, Florey Dept Neurosci & Mental Hlth, Melbourne, Vic, Australia
[14] Biogen Int GmbH, Zug, Switzerland
[15] Univ Melbourne, Melbourne Sch Populat & Global Hlth, Neuroepidemiol Unit, Melbourne, Vic, Australia
来源
ANNALS OF CLINICAL AND TRANSLATIONAL NEUROLOGY | 2025年
基金
英国医学研究理事会;
关键词
cognition; digital biomarkers; latent class; multiple sclerosis; processing speed test; MODALITIES TEST; VALIDITY; DYSFUNCTION; IMPAIRMENT; TESTS; MRI;
D O I
10.1002/acn3.70015
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Background: Cognitive impairment is one of the most common and debilitating symptoms of relapsing-remitting multiple sclerosis (RRMS). Digital cognitive biomarkers require less time and resources and are rapidly gaining popularity in clinical settings. We examined the longitudinal trajectory of the iPad-based Processing Speed Test (PST) and predictors of PST scores. Methods: We prospectively enrolled RRMS patients between 2017 and 2021 across six Australian MS centres. Longitudinal data was analysed with mixed effect modelling and latent class mixed models. We then examined whether latent class group membership predicted confirmed decrease in correct PST responses. Results: We recruited a total of 1093 participants, of which 724 had complete baseline data with a median follow up duration of 2 years. At a population level, PST trajectory was stable. A small practice effect was present up to the 4th visit. Age, baseline disability, T2 lesion volume, male sex and depression were associated with lower correct PST responses, whilst years of education and full/part-time employment were associated with more correct PST responses. We identified four latent class trajectories of PST. The worst latent class was typified by low baseline PST and lack of a practice effect. Being in the worst latent class was associated with a greater hazard of time to sustained 5% decrease in PST (HR 2.84, 95% CI 1.16-6.94, p = 0.02). Conclusion: Worse baseline cognitive performance and lack of a practice effect predicted future cognitive decline in RRMS.
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页数:9
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