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

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

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

Neurological update: MOG antibody disease

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

The prevalence of epileptic seizures in multiple sclerosis in a large tertiary hospital in Australia.

Rationale: To determine the prevalence of epileptic seizures in multiple sclerosis (MS) at an Australian tertiary hospital and to define their clinical features. Methods: We retrospectively analysed adult patients at the Royal Melbourne Hospital electronically identified to have ICD codes for MS and seizures and/or epilepsy between 1996 to 2019, utilising paper and electronic-based records. Results: Of the 2,125 MS patients identified, 16 (0.75%) experienced epileptic seizures during a mean follow-up period of 12.9 years. Median age of MS diagnosis (SD) was 38 (9.3) years. Four patients had relapsing remitting MS (25%), 10 secondary progressive MS (63.5%), and 2 primary progressive MS (12.5%). More than two-thirds of patients had seizure onset following the diagnosis of MS, and the majority of these had advanced disease (approximate EDSS >6) at the time of seizure onset. Focal onset-seizures occurred in 87.5% of patients with seizures. Conclusion: The estimated prevalence of seizures in our cohort was lower than in previous studies (0.75 vs 2-4%). In most cases, seizures occurred after the diagnosis of MS in the context of advanced disease. Further studies are required to determine if MS disease modifying treatments reduce the risk of seizures in this cohort

Cost of multiple sclerosis in the Czech Republic: The COMS study

Background: Information about cost of multiple sclerosis (MS) is available from a number of European countries, but no data from the Czech Republic have been published so far. Objective: The objective of this study was to establish the cost of MS in the Czech Republic, overall and by level of disease severity. Methods: Data on demographics, disease history, resource consumption and production losses were collected from 909 patients recruited in 7 MS centres in the Czech Republic. Annual costs were estimated in the societal perspective, using 2007 unit costs. To evaluate the relationship between disability and costs, patients were stratified into those with mild (67%), moderate (27%) and severe (10%) disability using the Expanded Disability Status Scale. Results: Mean total annual costs per patient were (sic)12,272, of which 51% were direct medical costs, 4% direct non-medical costs and 45% indirect costs. The average annual costs in patients with mild, moderate and severe disability amounted to (sic)9905, (sic)14,064 and (sic)22,880, respectively. Conclusion: The total costs of MS in the Czech Republic are estimated at (sic)208.6 million per year. Consistent with other studies, the costs increase significantly with the severity of MS