Annals of clinical and translational neurology · 2025
Cognitive Impairment in Multiple Sclerosis: The Role of Clinical and Sociodemographic Factors - A Systematic Review and Meta-Analysis.
СтатьяСистематический обзорМетаанализНазвание и аннотация: Перевод в очереди
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Lugosi Katalin, Engh Marie A, Kói Tamás, Molnár Zsolt, Csukly Gábor, Horváth Klaudia, Hargitai Emma, Hegyi Péter, Mezei Zsolt
Аннотация
OBJECTIVE: Cognitive impairment (CI) affects the quality of life in multiple sclerosis (MS). Identifying influencing factors is key to improving CI monitoring. This systematic review and meta-analysis examines clinical and sociodemographic variables impacting the cognitive screening Symbol Digit Modalities Test (SDMT) performance across MS subtypes, identifying subgroups at greater risk of cognitive impairment.
METHODS: Registered on PROSPERO (CRD42023451696), a literature search was conducted on August 6, 2023, using PubMed, Embase, and CENTRAL. Following the PRISMA 2020 guideline, a random-effects meta-analysis addressed heterogeneity in correlation and meta-regression analyses. Multivariable regression model results were qualitatively synthesized (systematic review). The JBI Critical Appraisal Tool assessed bias risk. Primary outcome was SDMT raw scores, with EDSS and disease duration as primary exposures, extended with age, sex, education, depression, fatigue, mobility scores, and treatment as secondary exposures, according to our protocol. Associations were evaluated via univariate study-level correlations, univariate meta-regressions, study-level multivariable regression models, and multivariate meta-regressions, assessing covariate interdependence. Heterogeneity was quantified with I2. Only observational cross-sectional data (or baseline data from longitudinal studies) were included.
RESULTS: A total of 155 studies with 22,828 patients were analyzed. In mixed and relapsing-remitting MS (RRMS), EDSS was the strongest negative correlate of SDMT (mixed MS: -0.44 CI:[-0.50; -0.36]; RRMS: -0.47 [-0.66; -0.23]). Education showed a moderate positive correlation (mixed MS: 0.31 [0.20; 0.42]; RRMS: 0.32 [-0.02; 0.59]). Due to cross-sectional design, heterogeneity, and potential aggregation/ecological bias, findings are exploratory.
INTERPRETATION: Poor SDMT performance is mainly driven by physical disability and cognitive reserve (education), modulated by sex, depression, and age, highlighting the need to integrate clinical and sociodemographic data in MS cognitive monitoring.
METHODS: Registered on PROSPERO (CRD42023451696), a literature search was conducted on August 6, 2023, using PubMed, Embase, and CENTRAL. Following the PRISMA 2020 guideline, a random-effects meta-analysis addressed heterogeneity in correlation and meta-regression analyses. Multivariable regression model results were qualitatively synthesized (systematic review). The JBI Critical Appraisal Tool assessed bias risk. Primary outcome was SDMT raw scores, with EDSS and disease duration as primary exposures, extended with age, sex, education, depression, fatigue, mobility scores, and treatment as secondary exposures, according to our protocol. Associations were evaluated via univariate study-level correlations, univariate meta-regressions, study-level multivariable regression models, and multivariate meta-regressions, assessing covariate interdependence. Heterogeneity was quantified with I2. Only observational cross-sectional data (or baseline data from longitudinal studies) were included.
RESULTS: A total of 155 studies with 22,828 patients were analyzed. In mixed and relapsing-remitting MS (RRMS), EDSS was the strongest negative correlate of SDMT (mixed MS: -0.44 CI:[-0.50; -0.36]; RRMS: -0.47 [-0.66; -0.23]). Education showed a moderate positive correlation (mixed MS: 0.31 [0.20; 0.42]; RRMS: 0.32 [-0.02; 0.59]). Due to cross-sectional design, heterogeneity, and potential aggregation/ecological bias, findings are exploratory.
INTERPRETATION: Poor SDMT performance is mainly driven by physical disability and cognitive reserve (education), modulated by sex, depression, and age, highlighting the need to integrate clinical and sociodemographic data in MS cognitive monitoring.