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1.
Mult Scler Relat Disord ; 89: 105755, 2024 Sep.
Article in English | MEDLINE | ID: mdl-39018643

ABSTRACT

BACKGROUND: Because secondary progressive multiple sclerosis (SPMS) is associated with worse prognosis, early predictive tools are needed. We aimed to use systematic literature review and advanced methods to create and validate a clinical tool for estimating individual patient risk of transition to SPMS over five years. METHODS: Data from the Jacobs Multiple Sclerosis Center (JMSC) and the Multiple Sclerosis Center Amsterdam (MSCA) was collected between 1994 and 2022. Participants were relapsing-remitting adult patients at initial evaluation. We created the tool in four stages: (1) identification of candidate predictors from systematic literature review, (2) ordinal cutoff determination, (3) feature selection, (4) feature weighting. RESULTS: Patients in the development/internal-validation/external-validation datasets respectively (n = 787/n = 522/n = 877) had a median age of 44.1/42.4/36.6 and disease duration of 7.7/6.2/4.4 years. From these, 12.6 %/10.2 %/15.4 % converted to SPMS (median=4.9/5.2/5.0 years). The DAAE Score was named from included predictors: Disease duration, Age at disease onset, Age, EDSS. It ranges from 0 to 12 points, with risk groups of very-low=0-2, low=3-7, medium=8-9, and high≥10. Risk of transition to SPMS increased proportionally across these groups in development (2.7 %/7.4 %/18.8 %/40.2 %), internal-validation (2.9 %/6.8 %/26.8 %/36.5 %), and external-validation (7.5 %/9.6 %/22.4 %/37.5 %). CONCLUSION: The DAAE Score estimates individual patient risk of transition to SPMS consistently across datasets internationally using clinically-accessible data. With further validation, this tool could be used for clinical risk estimation.


Subject(s)
Disease Progression , Multiple Sclerosis, Chronic Progressive , Humans , Multiple Sclerosis, Chronic Progressive/diagnosis , Adult , Female , Male , Middle Aged , Risk Assessment/methods , Multiple Sclerosis, Relapsing-Remitting/diagnosis , Reproducibility of Results
2.
Neuroimage Clin ; 42: 103609, 2024.
Article in English | MEDLINE | ID: mdl-38718640

ABSTRACT

BACKGROUND: Prior research has established a link between thalamic pathology and cognitive impairment (CI) in people with multiple sclerosis (pwMS). However, the translation of these findings to pwMS in everyday clinical settings has been insufficient. OBJECTIVE: To assess which global and/or thalamic imaging biomarkers can be used to identify pwMS at risk for CI and cognitive worsening (CW) in a real-world setting. METHODS: This was an international, multi-center (11 centers), longitudinal, retrospective, real-word study of people with relapsing-remitting MS (pwRRMS). Brain MRI exams acquired at baseline and follow-up were collected. Cognitive status was evaluated using the Symbol Digit Modalities Test (SDMT). Thalamic volume (TV) measurement was performed on T2-FLAIR, as well as on T1-WI, when available. Thalamic dysconnectivity, T2-lesion volume (T2-LV), and volumes of gray matter (GM), whole brain (WB) and lateral ventricles (LVV) were also assessed. RESULTS: 332 pwMS were followed for an average of 2.8 years. At baseline, T2-LV, LVV, TV and thalamic dysconnectivity on T2-FLAIR (p < 0.016), and WB, GM and TV volumes on T1-WI (p < 0.039) were significantly worse in 90 (27.1 %) CI vs. 242 (62.9 %) non-CI pwRRMS. Greater SDMT decline over the follow-up was associated with lower baseline TV on T2-FLAIR (standardized ß = 0.203, p = 0.002) and greater thalamic dysconnectivity (standardized ß = -0.14, p = 0.028) in a linear regression model. CONCLUSIONS: PwRRMS with thalamic atrophy and worse thalamic dysconnectivity present more frequently with CI and experience greater CW over mid-term follow-up in a real-world setting.


Subject(s)
Atrophy , Cognitive Dysfunction , Magnetic Resonance Imaging , Multiple Sclerosis, Relapsing-Remitting , Thalamus , Humans , Multiple Sclerosis, Relapsing-Remitting/pathology , Multiple Sclerosis, Relapsing-Remitting/diagnostic imaging , Multiple Sclerosis, Relapsing-Remitting/physiopathology , Multiple Sclerosis, Relapsing-Remitting/complications , Female , Male , Adult , Thalamus/pathology , Thalamus/diagnostic imaging , Cognitive Dysfunction/pathology , Cognitive Dysfunction/physiopathology , Cognitive Dysfunction/etiology , Cognitive Dysfunction/diagnostic imaging , Atrophy/pathology , Middle Aged , Magnetic Resonance Imaging/methods , Retrospective Studies , Longitudinal Studies
3.
J Neurol ; 271(5): 2195-2206, 2024 May.
Article in English | MEDLINE | ID: mdl-38409536

ABSTRACT

BACKGROUND: The heterogeneous nature of cognitive impairment in people with multiple sclerosis (PwMS) hampers understanding of the underlying mechanisms and developing patient-tailored interventions. We aim to identify and classify cognitive profiles in PwMS, comparing these to cognitive status (preserved versus impaired). METHODS: We included 1213 PwMS (72% female, age 45.4 ± 10.7 years, 83% relapsing-remitting MS). Cognitive test scores were converted to Z-scores compared to healthy controls for the functions: attention, inhibition, information processing speed (IPS), verbal fluency and verbal/visuospatial memory. Concerning cognitive status, impaired cognition (CI) was defined as performing at Z ≤ - 1.5 SD on ≥ 2 functions. Cognitive profiles were constructed using latent profile analysis on all cognitive functions. Cognitive profiles or status was classified using gradient boosting decision trees, providing the importance of each feature (demographics, clinical, cognitive and psychological functioning) for the overall classification. RESULTS: Six profiles were identified, showing variations in overall performance and specific deficits (attention, inhibition, IPS, verbal fluency, verbal memory and visuospatial memory). Across the profiles, IPS was the most impaired function (%CI most preserved profile, Profile 1 = 22.4%; %CI most impaired profile, Profile 6 = 76.6%). Cognitive impairment varied from 11.8% in Profile 1 to 95.3% in Profile 6. Of all cognitive functions, visuospatial memory was most important in classifying profiles and IPS the least (area under the curve (AUC) = 0.910). For cognitive status, IPS was the most important classifier (AUC = 0.997). CONCLUSIONS: This study demonstrated that cognitive heterogeneity in MS reflects a continuum of cognitive severity, distinguishable by distinct cognitive profiles, primarily explained by variations in visuospatial memory functioning.


Subject(s)
Cognitive Dysfunction , Multiple Sclerosis , Humans , Female , Male , Adult , Middle Aged , Cognitive Dysfunction/etiology , Cognitive Dysfunction/physiopathology , Cognitive Dysfunction/diagnosis , Multiple Sclerosis/complications , Multiple Sclerosis/physiopathology , Multiple Sclerosis/psychology , Spatial Memory/physiology , Neuropsychological Tests , Multiple Sclerosis, Relapsing-Remitting/physiopathology , Multiple Sclerosis, Relapsing-Remitting/complications , Multiple Sclerosis, Relapsing-Remitting/psychology
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