231 research outputs found

    Cerebrospinal fluid neurofilament light predicts longitudinal diagnostic change in patients with psychiatric and neurodegenerative disorders

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    OBJECTIVE: People with neuropsychiatric symptoms often experience delay in accurate diagnosis. Although cerebrospinal fluid neurofilament light (CSF NfL) shows promise in distinguishing neurodegenerative disorders (ND) from psychiatric disorders (PSY), its accuracy in a diagnostically challenging cohort longitudinally is unknown. METHODS: We collected longitudinal diagnostic information (mean = 36 months) from patients assessed at a neuropsychiatry service, categorising diagnoses as ND/mild cognitive impairment/other neurological disorders (ND/MCI/other) and PSY. We pre-specified NfL > 582 pg/mL as indicative of ND/MCI/other. RESULTS: Diagnostic category changed from initial to final diagnosis for 23% (49/212) of patients. NfL predicted the final diagnostic category for 92% (22/24) of these and predicted final diagnostic category overall (ND/MCI/other vs. PSY) in 88% (187/212), compared to 77% (163/212) with clinical assessment alone. CONCLUSIONS: CSF NfL improved diagnostic accuracy, with potential to have led to earlier, accurate diagnosis in a real-world setting using a pre-specified cut-off, adding weight to translation of NfL into clinical practice

    Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression

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    Background and Objectives: Research in Multiple Sclerosis (MS) has recently focused on extracting knowledge from real-world clinical data sources. This type of data is more abundant than data produced during clinical trials and potentially more informative about real-world clinical practice. However, this comes at the cost of less curated and controlled data sets. In this work we aim to predict disability progression by optimally extracting information from longitudinal patient data in the real-world setting, with a special focus on the sporadic sampling problem. Methods: We use machine learning methods suited for patient trajectories modeling, such as recurrent neural networks and tensor factorization. A subset of 6682 patients from the MSBase registry is used. Results: We can predict disability progression of patients in a two-year horizon with an ROC-AUC of 0.85, which represents a 32% decrease in the ranking pair error (1-AUC) compared to reference methods using static clinical features. Conclusions: Compared to the models available in the literature, this work uses the most complete patient history for MS disease progression prediction and represents a step forward towards AI-assisted precision medicine in MS

    Persistence on therapy and propensity matched outcome comparison of two subcutaneous interferon beta 1a dosages for multiple sclerosis

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    To compare treatment persistence between two dosages of interferon β-1a in a large observational multiple sclerosis registry and assess disease outcomes of first line MS treatment at these dosages using propensity scoring to adjust for baseline imbalance in disease characteristics. Treatment discontinuations were evaluated in all patients within the MSBase registry who commenced interferon β-1a SC thrice weekly (n = 4678). Furthermore, we assessed 2-year clinical outcomes in 1220 patients treated with interferon β-1a in either dosage (22 µg or 44 µg) as their first disease modifying agent, matched on propensity score calculated from pre-treatment demographic and clinical variables. A subgroup analysis was performed on 456 matched patients who also had baseline MRI variables recorded. Overall, 4054 treatment discontinuations were recorded in 3059 patients. The patients receiving the lower interferon dosage were more likely to discontinue treatment than those with the higher dosage (25% vs. 20% annual probability of discontinuation, respectively). This was seen in discontinuations with reasons recorded as “lack of efficacy” (3.3% vs. 1.7%), “scheduled stop” (2.2% vs. 1.3%) or without the reason recorded (16.7% vs. 13.3% annual discontinuation rate, 22 µg vs. 44 µg dosage, respectively). Propensity score was determined by treating centre and disability (score without MRI parameters) or centre, sex and number of contrast-enhancing lesions (score including MRI parameters). No differences in clinical outcomes at two years (relapse rate, time relapse-free and disability) were observed between the matched patients treated with either of the interferon dosages. Treatment discontinuations were more common in interferon β-1a 22 µg SC thrice weekly. However, 2-year clinical outcomes did not differ between patients receiving the different dosages, thus replicating in a registry dataset derived from “real-world” database the results of the pivotal randomised trial. Propensity score matching effectively minimised baseline covariate imbalance between two directly compared sub-populations from a large observational registry

    Clinical correlates of grey matter pathology in multiple sclerosis

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    Traditionally, multiple sclerosis has been viewed as a disease predominantly affecting white matter. However, this view has lately been subject to numerous changes, as new evidence of anatomical and histological changes as well as of molecular targets within the grey matter has arisen. This advance was driven mainly by novel imaging techniques, however, these have not yet been implemented in routine clinical practice. The changes in the grey matter are related to physical and cognitive disability seen in individuals with multiple sclerosis. Furthermore, damage to several grey matter structures can be associated with impairment of specific functions. Therefore, we conclude that grey matter damage - global and regional - has the potential to become a marker of disease activity, complementary to the currently used magnetic resonance markers (global brain atrophy and T2 hyperintense lesions). Furthermore, it may improve the prediction of the future disease course and response to therapy in individual patients and may also become a reliable additional surrogate marker of treatment effect

    Neurological update: MOG antibody disease

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    Myelin oligodendrocyte glycoprotein (MOG) antibody disease (MOG-AD) is now recognised as a nosological entity with specific clinical and paraclinical features to aid early diagnosis. Although no age group is exempt, median age of onset is within the fourth decade of life, with optic neuritis being the most frequent presenting phenotype. Disease course can be either monophasic or relapsing, with subsequent relapses most commonly involving the optic nerve. Residual disability develops in 50–80% of patients, with transverse myelitis at onset being the most significant predictor of long-term outcome. Recent advances in MOG antibody testing offer improved sensitivity and specificity. To avoid misdiagnosis, MOG antibody testing should be undertaken in selected cases presenting clinical and paraclinical features that are felt to be in keeping with MOG-AD, using a validated cell-based assay. MRI characteristics can help in differentiating MOG-AD from other neuroinflammatory disorders, including multiple sclerosis and neuromyelitis optica. Cerebrospinal fluid oligoclonal bands are uncommon. Randomised control trials are limited, but observational open-label experience suggests a role for high-dose steroids and plasma exchange in the treatment of acute attacks, and for immunosuppressive therapies, such as steroids, oral immunosuppressants and rituximab as maintenance treatment

    Comparative effectiveness of autologous hematopoietic stem cell transplant vs fingolimod, natalizumab, and ocrelizumab in highly active relapsing-remitting multiple sclerosis

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    Importance: Autologous hematopoietic stem cell transplant (AHSCT) is available for treatment of highly active multiple sclerosis (MS). Objective: To compare the effectiveness of AHSCT vs fingolimod, natalizumab, and ocrelizumab in relapsing-remitting MS by emulating pairwise trials. Design, Setting, and Participants: This comparative treatment effectiveness study included 6 specialist MS centers with AHSCT programs and international MSBase registry between 2006 and 2021. The study included patients with relapsing-remitting MS treated with AHSCT, fingolimod, natalizumab, or ocrelizumab with 2 or more years study follow-up including 2 or more disability assessments. Patients were matched on a propensity score derived from clinical and demographic characteristics. Exposure: AHSCT vs fingolimod, natalizumab, or ocrelizumab. Main outcomes: Pairwise-censored groups were compared on annualized relapse rates (ARR) and freedom from relapses and 6-month confirmed Expanded Disability Status Scale (EDSS) score worsening and improvement. Results: Of 4915 individuals, 167 were treated with AHSCT; 2558, fingolimod; 1490, natalizumab; and 700, ocrelizumab. The prematch AHSCT cohort was younger and with greater disability than the fingolimod, natalizumab, and ocrelizumab cohorts; the matched groups were closely aligned. The proportion of women ranged from 65% to 70%, and the mean (SD) age ranged from 35.3 (9.4) to 37.1 (10.6) years. The mean (SD) disease duration ranged from 7.9 (5.6) to 8.7 (5.4) years, EDSS score ranged from 3.5 (1.6) to 3.9 (1.9), and frequency of relapses ranged from 0.77 (0.94) to 0.86 (0.89) in the preceding year. Compared with the fingolimod group (769 [30.0%]), AHSCT (144 [86.2%]) was associated with fewer relapses (ARR: mean [SD], 0.09 [0.30] vs 0.20 [0.44]), similar risk of disability worsening (hazard ratio [HR], 1.70; 95% CI, 0.91-3.17), and higher chance of disability improvement (HR, 2.70; 95% CI, 1.71-4.26) over 5 years. Compared with natalizumab (730 [49.0%]), AHSCT (146 [87.4%]) was associated with marginally lower ARR (mean [SD], 0.08 [0.31] vs 0.10 [0.34]), similar risk of disability worsening (HR, 1.06; 95% CI, 0.54-2.09), and higher chance of disability improvement (HR, 2.68; 95% CI, 1.72-4.18) over 5 years. AHSCT (110 [65.9%]) and ocrelizumab (343 [49.0%]) were associated with similar ARR (mean [SD], 0.09 [0.34] vs 0.06 [0.32]), disability worsening (HR, 1.77; 95% CI, 0.61-5.08), and disability improvement (HR, 1.37; 95% CI, 0.66-2.82) over 3 years. AHSCT-related mortality occurred in 1 of 159 patients (0.6%). Conclusion: In this study, the association of AHSCT with preventing relapses and facilitating recovery from disability was considerably superior to fingolimod and marginally superior to natalizumab. This study did not find evidence for difference in the effectiveness of AHSCT and ocrelizumab over a shorter available follow-up time

    Assessing treatment outcomes in multiple sclerosis trials and in the clinical setting

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    Increasing numbers of drugs are being developed for the treatment of multiple sclerosis (MS). Measurement of relevant outcomes is key for assessing the efficacy of new drugs in clinical trials and for monitoring responses to disease-modifying drugs in individual patients. Most outcomes used in trial and clinical settings reflect either clinical or neuroimaging aspects of MS (such as relapse and accrual of disability or the presence of visible inflammation and brain tissue loss, respectively). However, most measures employed in clinical trials to assess treatment effects are not used in routine practice. In clinical trials, the appropriate choice of outcome measures is crucial because the results determine whether a drug is considered effective and therefore worthy of further development; in the clinic, outcome measures can guide treatment decisions, such as choosing a first-line disease-modifying drug or escalating to second-line treatment. This Review discusses clinical, neuroimaging and composite outcome measures for MS, including patient-reported outcome measures, used in both trials and the clinical setting. Its aim is to help clinicians and researchers navigate through the multiple options encountered when choosing an outcome measure. Barriers and limitations that need to be overcome to translate trial outcome measures into the clinical setting are also discussed
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