Time to diagnosis in multiple sclerosis: Epidemiological data from the German Multiple Sclerosis Registry

Identification and management of subclinical disease activity in early multiple sclerosis: a review

IMPORTANCE

Early treatment initiation in multiple sclerosis (MS) is crucial in preventing irreversible neurological damage and disability progression. The current assessment of disease activity relies on relapse rates and magnetic resonance imaging (MRI) lesion activity, but inclusion of other early, often "hidden," indicators of disease activity may describe a more comprehensive picture of MS.

OBSERVATIONS

Early indicators of MS disease activity other than relapses and MRI activity, such as cognitive impairment, brain atrophy, and fatigue, are not typically captured by routine disease monitoring. Furthermore, silent progression (neurological decline not clearly captured by standard methods) may occur undetected by relapse and MRI lesion activity monitoring. Consequently, patients considered to have no disease activity actually may have worsening disease, suggesting a need to revise MS management strategies with respect to timely initiation and escalation of disease-modifying therapy (DMT). Traditionally, first-line MS treatment starts with low- or moderate-efficacy therapies, before escalating to high-efficacy therapies (HETs) after evidence of breakthrough disease activity. However, multiple observational studies have shown that early initiation of HETs can prevent or reduce disability progression. Ongoing randomized clinical trials are comparing escalation and early HET approaches.

CONCLUSIONS AND RELEVANCE

There is an urgent need to reassess how MS disease activity and worsening are measured. A greater awareness of "hidden" indicators, potentially combined with biomarkers to reveal silent disease activity and neurodegeneration underlying MS, would provide a more complete picture of MS and allow for timely therapeutic intervention with HET or switching DMTs to address suboptimal treatment responses.

Disease-modifying therapy initiation patterns in multiple sclerosis in three large MS populations

Background

Treatment guidelines recommend early disease-modifying therapy (DMT) initiation after diagnosis of multiple sclerosis (MS). Multinational comparative studies that assess time to DMT initiation in MS may allow detection of barriers inherent to healthcare systems to explain potential adverse systematic delays in commencing DMTs.

Objectives

To investigate and compare the time to first DMT and its association with sociodemographic and clinical variables after MS diagnosis in three large MS registries.

Design

This observational study was conducted using data from the German MS Registry (GMSR), the North American Research Committee on MS Registry (NARCOMS, US data only), and the United Kingdom MS Registry (UKMSR, both self- and clinician-reported).

Methods

Data from relapsing people with MS (PwMS), with a diagnosis of MS between 2014 and 2019, and available DMT and disability status were pooled using a meta-analytic approach.

Results

A total of 5395 PwMS were included in the analysis (GMSR: n = 2658; NARCOMS: n = 447; UKMSR: n = 2290). Kaplan-Meier estimates for the time to first DMT [median months (95% CI)] were 2.0 (1.9-2.0), 3.0 (2-4), and 9.0 (7.7-10.6) for GMSR, NARCOMS, and UKMSR, respectively. Pooled multivariable Cox regression demonstrated shorter time to first DMT for PwMS diagnosed after 2017 [1.65 (1.42-1.92), p < 0.01], and longer time to DMT when a higher-efficacy DMT was selected (0.69 (0.54-0.90), p < 0.0001].

Conclusion

Time to DMT initiation differs across the populations studied, indicating that barriers may exist in early access to DMT, particularly in the United Kingdom. However, a consistent decrease in time to DMT initiation was noted since 2017 across all registries. Further studies are warranted comparing the effects of time to DMT and time to higher-efficacy DMT on long-term outcome.

Building digital patient pathways for the management and treatment of multiple sclerosis

Recent advances in the field of artificial intelligence (AI) could yield new insights into the potential causes of multiple sclerosis (MS) and factors influencing its course as the use of AI opens new possibilities regarding the interpretation and use of big data from not only a cross-sectional, but also a longitudinal perspective. For each patient with MS, there is a vast amount of multimodal data being accumulated over time. But for the application of AI and related technologies, these data need to be available in a machine-readable format and need to be collected in a standardized and structured manner. Through the use of mobile electronic devices and the internet it has also become possible to provide healthcare services from remote and collect information on a patient's state of health outside of regular check-ups on site. Against this background, we argue that the concept of pathways in healthcare now could be applied to structure the collection of information across multiple devices and stakeholders in the virtual sphere, enabling us to exploit the full potential of AI technology by e.g., building digital twins. By going digital and using pathways, we can virtually link patients and their caregivers. Stakeholders then could rely on digital pathways for evidence-based guidance in the sequence of procedures and selection of therapy options based on advanced analytics supported by AI as well as for communication and education purposes. As far as we aware of, however, pathway modelling with respect to MS management and treatment has not been thoroughly investigated yet and still needs to be discussed. In this paper, we thus present our ideas for a modular-integrative framework for the development of digital patient pathways for MS treatment.

Association of health behaviour and clinical manifestation in early multiple sclerosis in Germany - Baseline characteristics of the POWER@MS1 randomised controlled trial

BACKGROUND

Receiving a multiple sclerosis (MS) diagnosis is a significant stressor. Therefore, highly individualised counselling is needed, especially in early MS. Modifiable risk factors (e.g. smoking and obesity) are gaining relevance in MS. Despite evidence for worse MS-related health outcomes, prevalence of adverse health behaviours, such as smoking and physical inactivity, is high across all MS stages. However, knowledge regarding health behaviours as well as their association with MS-related health outcomes among newly diagnosed PwMS in Germany is scarce. Currently, the efficacy of an interactive digital lifestyle management application intended to be used as an add-on to standard care among newly diagnosed PwMS in Germany is evaluated in an ongoing multicentre randomised controlled trial (RCT) ('POWER@MS1').

OBJECTIVES

To describe baseline disease characteristics and health behaviours of the POWER@MS1 cohort and investigate associations between MS characteristics, quality of life (QOL), health behaviours and intention to optimise health behaviour habits.

METHODS

This study included 234 persons with early MS from 20 study centres located across Germany who participate in the POWER@MS1 RCT. Participants were recruited by treating neurologists from different regions and health-care settings in Germany. Baseline data was obtained using paper-based questionnaires and a web-based healthy diet screener between July 2019 and end of March 2022 and analysed descriptively.

RESULTS

In this early MS cohort (mean disease duration 4 months), a screening tool showed severe symptoms of anxiety in 15 % of the participants. Better means for stress management appeared to be particularly relevant for the whole cohort. Moreover, 19 % were current smokers, 15 % were obese and 36 % were insufficiently physically active. On average, participants only moderately adhered to dietary guidelines for recommended intake of key food groups (e.g. vegetables, fruits and fatty marine fish). Higher EDSS scores were associated with approximately 20 % higher T2-lesion burden (rate ratio RR=1.2, p<0.001) and 13 % higher relapse rate (RR=1.13,p=0.02) per EDSS disability level. Moreover, a higher T2-lesion burden was associated with current smoking (RR=0.76, p=0.033), resulting in approximately 24 % less T2-lesions at disease onset among non-smokers. In addition, smoking was associated with unhealthier dietary habits according to lower diet scores (linear regression coefficient β=-1.27, p<0.001). Higher EDSS scores (β=0.19,p<0.001) and higher BMI (β=0.013,p=0.03) were associated with higher HAQUAMS (lower QOL). Further, lower diet scores (β=-0.044,p=0.039) were associated with lower QOL. Moreover, higher HAQUAMS (lower QOL) indicated a higher intention to optimise stress management (β=0.98,p<0.001), physical activity (β=0.74,p=0.046) and sleep behaviour (β=1.82,p<0.001). Further, higher intention to optimise stress management was accounted for by higher EDSS scores (β=0.39,p=0.004) and a higher number of T2-lesions (β=0.029,p=0.015) in this newly diagnosed MS cohort.

CONCLUSION

Results indicate a clear need for modifications of health behaviours among newly diagnosed PwMS participating in POWER@MS1. Individualised psychological and health behaviour counselling appears to be an important factor in treatment, also for similar early MS cohorts and particularly in those who demonstrate a more severe disease in clinical and MRI metrics.

Data monitoring roadmap. The experience of the Italian Multiple Sclerosis and Related Disorders Register

INTRODUCTION

Over the years, disease registers have been increasingly considered a source of reliable and valuable population studies. However, the validity and reliability of data from registers may be limited by missing data, selection bias or data quality not adequately evaluated or checked. This study reports the analysis of the consistency and completeness of the data in the Italian Multiple Sclerosis and Related Disorders Register.

METHODS

The Register collects, through a standardized Web-based Application, unique patients. Data are exported bimonthly and evaluated to assess the updating and completeness, and to check the quality and consistency. Eight clinical indicators are evaluated.

RESULTS

The Register counts 77,628 patients registered by 126 centres. The number of centres has increased over time, as their capacity to collect patients. The percentages of updated patients (with at least one visit in the last 24 months) have increased from 33% (enrolment period 2000-2015) to 60% (enrolment period 2016-2022). In the cohort of patients registered after 2016, there were ≥ 75% updated patients in 30% of the small centres (33), in 9% of the medium centres (11), and in all the large centres (2). Clinical indicators show significant improvement for the active patients, expanded disability status scale every 6 months or once every 12 months, visits every 6 months, first visit within 1 year and MRI every 12 months.

CONCLUSIONS

Data from disease registers provide guidance for evidence-based health policies and research, so methods and strategies ensuring their quality and reliability are crucial and have several potential applications.

Diagnostic delay of multiple sclerosis: prevalence, determinants and consequences

BACKGROUND

Early diagnosis and treatment of patients with multiple sclerosis (MS) are associated with better outcomes; however, diagnostic delays remain a major problem.

OBJECTIVE

Describe the prevalence, determinants and consequences of delayed diagnoses.

METHODS

This single-centre ambispective study analysed 146 adult relapsing-remitting MS patients (2016-2021) for frequency and determinants of diagnostic delays and their associations with clinical, cognitive, imaging and biochemical measures.

RESULTS

Diagnostic delays were identified in 77 patients (52.7%), including 42 (28.7%) physician-dependent cases and 35 (24.0%) patient-dependent cases. Diagnosis was delayed in 22 (15.1%) patients because of misdiagnosis by a neurologist. A longer diagnostic delay was associated with trends towards greater Expanded Disability Status Scale (EDSS) scores (B = 0.03; p = 0.034) and greater z-score of the blood neurofilament light chain (B = 0.35; p = 0.031) at the time of diagnosis. Compared with patients diagnosed at their first clinical relapse, patients with a history of >1 relapse at diagnosis (n = 63; 43.2%) had a trend towards greater EDSS scores (B = 0.06; p = 0.006) and number of total (B = 0.13; p = 0.040) and periventricular (B = 0.06; p = 0.039) brain lesions.

CONCLUSION

Diagnostic delays in MS are common, often determined by early misdiagnosis and associated with greater disease burden.

Improvement in time to multiple sclerosis diagnosis: 25-year retrospective analysis from New York State MS Consortium (NYSMSC)

Judicious multiple sclerosis (MS) diagnosis and early start of disease modifying therapy significantly improves long-term disability outcomes in persons with MS (pwMS). Retrospective analysis based on 25-year New York State MS Consortium (NYSMSC) data determined the effect of changes in the respective diagnostic criteria in shortening the time between symptom onset to MS diagnosis. Based on 9378 current and historical MS cases, there was a significant decrease in time to diagnosis in pwMS from 1982–2001 to >2017 periods (average 4.2 vs. 1.1 years, p < 0.001). Additional improvements and better implementation of the MS diagnostic criteria can further decrease the diagnosis lag.

Genetic risk variants for multiple sclerosis are linked to differences in alternative pre-mRNA splicing

BACKGROUND

Multiple sclerosis (MS) is a chronic immune-mediated disease of the central nervous system to which a genetic predisposition contributes. Over 200 genetic regions have been associated with increased disease risk, but the disease-causing variants and their functional impact at the molecular level are mostly poorly defined. We hypothesized that single-nucleotide polymorphisms (SNPs) have an impact on pre-mRNA splicing in MS.

METHODS

Our study focused on 10 bioinformatically prioritized SNP-gene pairs, in which the SNP has a high potential to alter alternative splicing events (ASEs). We tested for differential gene expression and differential alternative splicing in B cells from MS patients and healthy controls. We further examined the impact of the SNP genotypes on ASEs and on splice isoform expression levels. Novel genotype-dependent effects on splicing were verified with splicing reporter minigene assays.

RESULTS

We were able to confirm previously described findings regarding the relation of MS-associated SNPs with the ASEs of the pre-mRNAs from GSDMB and SP140. We also observed an increased IL7R exon 6 skipping when comparing relapsing and progressive MS patients to healthy subjects. Moreover, we found evidence that the MS risk alleles of the SNPs rs3851808 (EFCAB13), rs1131123 (HLA-C), rs10783847 (TSFM), and rs2014886 (TSFM) may contribute to a differential splicing pattern. Of particular interest is the genotype-dependent exon skipping of TSFM due to the SNP rs2014886. The minor allele T creates a donor splice site, resulting in the expression of the exon 3 and 4 of a short TSFM transcript isoform, whereas in the presence of the MS risk allele C, this donor site is absent, and thus the short transcript isoform is not expressed.

CONCLUSION

In summary, we found that genetic variants from MS risk loci affect pre-mRNA splicing. Our findings substantiate the role of ASEs with respect to the genetics of MS. Further studies on how disease-causing genetic variants may modify the interactions between splicing regulatory sequence elements and RNA-binding proteins can help to deepen our understanding of the genetic susceptibility to MS.