Prognostication and contemporary management of clinically isolated syndrome

A mixture model for differentiating longitudinal courses of multiple sclerosis

BACKGROUND

Multiple sclerosis has a broad spectrum of clinical courses. Early identification of patients at greater risk of accumulating disability is essential.

OBJECTIVES

Identify groups of patients with similar presentation through a mixture model and predict their trajectories over the years.

METHODS

Retrospective study of patients from 1994 to 2019. We performed a latent profile analysis followed by a latent transition analysis based on eight parameters: age, disease duration, EDSS, number of relapses, multi-topographic symptoms, motor impairment, sphincter impairment, and infratentorial lesions.

RESULTS

We included 629 patients, regardless of the phenotypical classification. We identified three distinct groups at the beginning and end of the follow-up. The three-classes model disclosed the "No disability regardless disease duration" (NDRDD) class with low EDSS and younger patients, the "Disability within a short disease duration" (DSDD) class with the worse disability besides short illness, and the "Disability within a long disease duration" (DLDD) class that achieved high EDSS over a long disease duration. EDSS, disease duration, and no sphincter impairment had the best entropy to distinguish classes at the initial presentation. Over time, the patients from NDRDD had a 52.1 % probability of changing to DLDD and 7.7 % of changing to DSDD.

CONCLUSIONS

We identified three groups of clinical presentations and their evolution over time based on considered prognostic factors. The most likely transition is from NDRDD to DLDD.

Clinical and radiologic characteristics associated with multiple sclerosis misdiagnosis at a tertiary referral center in the United States

BACKGROUND

Misdiagnosis of multiple sclerosis (MS) is common and can have harmful effects on patients and healthcare systems. Identification of factors associated with misdiagnosis may aid development of prevention strategies.

OBJECTIVE

To identify clinical and radiological predictors of MS misdiagnosis.

METHODS

We retrospectively reviewed medical records of all patients who were referred to Johns Hopkins MS Center from January 2018 to June 2019. Patients who carried a diagnosis of MS were classified as correctly diagnosed or misdiagnosed with MS by the Johns Hopkins clinician. Demographics, clinical, laboratory, and radiologic data were collected. Differences between the two groups were evaluated, and a regression model was constructed to identify predictors of misdiagnosis.

RESULTS

Out of 338 patients who were previously diagnosed with MS, 41 (12%) had been misdiagnosed. An alternative diagnosis was confirmed in 28 (68%) of the misdiagnosed patients; cerebrovascular disease was the most common alternate diagnosis. Characteristics associated with misdiagnosis were female sex (odds ratio (OR): 5.81 (95% confidence interval (CI): 1.60, 21.05)) and non-specific brain magnetic resonance imaging (MRI) lesions (OR: 7.66 (3.42, 17.16)).

CONCLUSION

Misdiagnosis is a frequent problem in MS care. Non-specific brain lesions were the most significant predictor of misdiagnosis. Interventions aimed to reduce over-reliance on imaging findings and misapplication of the McDonald criteria may prevent MS misdiagnosis.

Cerebrospinal fluid inflammatory biomarkers for disease progression in Alzheimer's disease and multiple sclerosis: a systematic review

Inflammatory processes are involved in the pathophysiology of both Alzheimer's disease (AD) and multiple sclerosis (MS) but their exact contribution to disease progression remains to be deciphered. Biomarkers are needed to define pathophysiological processes of these disorders, who may increasingly co-exist in the elderly generations of the future, due to the rising prevalence in both and ameliorated treatment options with improved life expectancy in MS. The purpose of this review was to provide a systematic overview of inflammatory biomarkers, as measured in the cerebrospinal fluid (CSF), that are associated with clinical disease progression. International peer-reviewed literature was screened using the PubMed and Web of Science databases. Disease progression had to be measured using clinically validated tests representing baseline functional and/or cognitive status, the evolution of such clinical scores over time and/or the transitioning from one disease stage to a more severe stage. The quality of included studies was systematically evaluated using a set of questions for clinical, neurochemical and statistical characteristics of the study. A total of 84 papers were included (twenty-five for AD and 59 for MS). Elevated CSF levels of chitinase-3-like protein 1 (YKL-40) were associated with disease progression in both AD and MS. Osteopontin and monocyte chemoattractant protein-1 were more specifically related to disease progression in AD, whereas the same was true for interleukin-1 beta, tumor necrosis factor alpha, C-X-C motif ligand 13, glial fibrillary acidic protein and IgG oligoclonal bands in MS. We observed a broad heterogeneity of studies with varying cohort characterization, non-disclosure of quality measures for neurochemical analyses and a lack of adequate longitudinal designs. Most of the retrieved biomarkers are related to innate immune system activity, which seems to be an important mediator of clinical disease progression in AD and MS. Overall study quality was limited and we have framed some recommendations for future biomarker research in this field.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42021264741.

Longitudinal clinical study of patients with iron rim lesions in multiple sclerosis

Background:

Iron rims (IRs) surrounding white matter lesions (WMLs) are suggested to predict a more severe disease course. Only small longitudinal cohorts of patients with and without iron rim lesions (IRLs) have been reported so far.

Objective:

To assess whether the presence and number of IRLs in patients with clinically isolated syndrome (CIS) and multiple sclerosis (MS) are associated with long-term disability or progressive disease.

Methods:

Ninety-one CIS/MS patients were recruited between 2008 and 2013 and scanned with 7 T magnetic resonance imaging (MRI). Expanded Disability Status Scale (EDSS) was used to calculate Age-related Multiple Sclerosis Severity Score (ARMSS) at the time of scan and at the latest clinical follow-up after 9 years. WMLs were assessed for the presence of IRL using Susceptibility weighted imaging (SWI)-filtered phase images.

Results:

In all, 132 IRLs were detected in 42 patients (46%); 9% of WMLs had IRs; 54% of the cohort had no rims, 30% had 1–3 rims and 16% had ⩾4. Patients with IRL had a higher EDSS and ARMSS. Presence of IRL was also a predictor of long-term disability, especially in patients with ⩾4 IRLs. IRLs have a greater impact on disability compared to the WML number and volume.

Conclusion:

The presence and number of perilesional IR on MRI hold prognostic value for long-term clinical disability in MS.

Biological Markers in Early Multiple Sclerosis: the Paved Way for Radiologically Isolated Syndrome

Radiologically Isolated Syndrome (RIS) is characterized by MRI-typical brain lesions fulfilling the 2009 Okuda criteria, detected in patients without clinical conditions suggestive of MS. Half of all RIS patients convert to MS within 10 years. The individual course of the disease, however, is highly variable with 12% of RIS converting directly to progressive MS. Demographic and imaging markers have been associated with the risk of clinical MS in RIS: male sex, younger age, infra-tentorial, and spinal cord lesions on the index scan and gadolinium-enhancing lesions on index or follow-up scans. Although not considered as a distinct MS phenotype, RIS certainly shares common pathological features with early active and progressive MS. In this review, we specifically focus on biological markers that may help refine the risk stratification of clinical MS and disability for early treatment. Intrathecal B-cell activation with cerebrospinal fluid (CSF) oligoclonal bands, elevated kappa free light chains, and cytokine production is specific to MS, whereas neurofilament light chain (NfL) levels reflect disease activity associated with neuroaxonal injury. Specific microRNA profiles have been identified in RIS converters in both CSF and blood. CSF levels of chitinases and glial acidic fibrillary protein (GFAP) reflecting astrogliosis might help predict the evolution of RIS to progressive MS. Innovative genomic, proteomic, and metabolomic approaches have provided several new candidate biomarkers to be explored in RIS. Leveraging data from randomized controlled trials and large prospective RIS cohorts with extended follow-up to identify, as early as possible, biomarkers for predicting greater disease severity would be invaluable for counseling patients, managing treatment, and monitoring.