Clinical implications for the association of psoriasis and multiple sclerosis: an observational study.

BACKGROUND: Multiple sclerosis (MS) and psoriasis (PsO) are distinct chronic autoimmune conditions with varying impacts on patients' lives. While the co-occurrence of MS and PsO has been reported, the underlying pathogenic link remains unclear. This study aimed to investigate the prevalence of PsO in a MS outpatient clinic population and explore the potential interplay between these conditions. METHODS: 316 MS patients who had at least one visit at our MS center in the last year, were selected from our outpatient MS Clinic electronic database and were e-mailed in August 2023 and inquired about a previous diagnosis of PsO. Demographic and MS history data were retrospectively gathered for two groups: MS patients without and with PsO. Information about MS phenotype, Expanded Disability Status Scale (EDSS) score at the diagnosis and at last follow-up, disease modifying therapy (DMT) were collected retrospectively from our MS data set. PsO diagnosis was confirmed by an experienced dermatologist and severity was assessed with the Psoriasis Area and Severity Index (PASI). RESULTS: Among 253 respondents, 5.85% reported a PsO diagnosis that was confirmed after the dermatological evaluation Among patients with psoriasis 66.67% had progressive course of MS (p = 0.032) and the onset of PsO typically occurred after MS diagnosis. 9 out 15 patients had a PASI score of 0 and 6 are currently undergoing treatment with an anti-CD20 therapy. Notably, a subset of our patients were on anti-CD20 therapy and did not experience a worsening of dermatological symptoms. DISCUSSION AND CONCLUSION: The prevalence of PsO in our outpatient MS population aligns with previous studies. Treatment approaches should be tailored to individual patient needs, emphasizing collaboration between neurologists and dermatologists. Medications like dimethyl fumarate, effective in both conditions, could be considered. The data from our study also suggest that anti-CD20 therapy may be a viable option for some patients with concurrent MS and mild PsO, without a significant worsening of dermatological symptoms. Further research is needed to elucidate the complex relationship between MS and PsO and to develop more effective therapeutic strategies for patients with both conditions.

Identifying definite patterns of unmet needs in patients with multiple sclerosis using unsupervised machine learning.

INTRODUCTION: People with multiple sclerosis (PwMS) exhibit a spectrum of needs that extend beyond solely disease-related determinants. Investigating unmet needs from the patient perspective may address daily difficulties and optimize care. Our aim was to identify patterns of unmet needs among PwMS and their determinants. METHODS: We conducted a cross-sectional multicentre study. Data were collected through an anonymous, self-administered online form. To cluster PwMS according to their main unmet needs, we performed agglomerative hierarchical clustering algorithm. Principal component analysis (PCA) was applied to visualize cluster distribution. Pairwise comparisons were used to evaluate demographics and clinical distribution among clusters. RESULTS: Out of 1764 mailed questionnaires, we received 690 responses. Access to primary care was the main contributor to the overall unmet need burden. Four patterns were identified: cluster C1, 'information-seekers with few unmet needs'; cluster C2, 'high unmet needs'; cluster C3, 'socially and assistance-dependent'; cluster C4, 'self-sufficient with few unmet needs'. PCA identified two main components in determining the patterns: the 'public sphere' (access to information and care) and the 'private sphere' (need for assistance and social life). Older age, lower education, longer disease duration and higher disability characterized clusters with more unmet needs in the private sphere. However, demographic and clinical factors failed in explaining the four identified patterns. CONCLUSION: Our study identified four unmet need patterns among PwMS, emphasizing the importance of personalized care. While clinical and demographic factors provide some insight, additional variables warrant further investigation to fully understand unmet needs in PwMS.

Validation of the swallowing disturbance questionnaire in people with multiple sclerosis.

BACKGROUND: The DYSPHAGIA IN MULTIPLE SCLEROSIS (DYMUS) questionnaire is the only specific tool developed to screen for dysphagia in people with Multiple Sclerosis (pwMS). However, some limitations of DYMUS could potentially be addressed by the SWALLOWING DISTURBANCE QUESTIONNAIRE (SDQ), which has not yet been validated in pwMS. The objective of this study was to translate and validate the SDQ into the Italian language for use in pwMS to detect swallowing disturbances. METHODS: We translated the SDQ into Italian and adapted it for use in Italian pwMS. PwMS aged > 18 years, assessed for disability using the Expanded Disability Status Scale (EDSS), completed the SDQ and DYMUS questionnaires and performed the 3-OUNCE WATER SWALLOW TEST (WST). Clinical and demographic data were collected for each patient. The Italian version of the SDQ was retested after 30 days. RESULTS: A total of 84 pwMS were recruited for the study, consisting of 73.8 % women and 48.8 % with a relapsing-remitting form of MS. The mean age of participants was 44.5 years (SD: ±12.46), with a mean disease duration of 17 years (SD: ±10.27), and a median EDSS of 4 (range 1.5-7.5). The Cronbach's alpha for SDQ (to assess internal consistency) was 0.902, which increased to 0.908 after the elimination of item 15, resulting in the SDQ composed of 14 items. ROC analysis demonstrated good accuracy of the 14-item SDQ in pwMS (AUC: 0.811). By dividing the 14-item SDQ score into quartiles, three risk levels for dysphagia were identified: low (score 1-3), intermediate (score 4-8), and high (score ≥9). 14-item SDQ scores significantly correlated with DYMUS (r = 0.820; p<0.0001) and with EDSS (r = 0.541; p<0.0001). PwMS who reported dysphagia had a significantly higher mean 14-item SDQ score (8.27 ± SD 8.15) compared to those without swallowing problems (2.77 ± SD 4.25; p = 0.003). Additionally, pwMS with a positive WST had a significantly higher mean 14-item SDQ score (10.17 ± SD 8.96) than those with a negative WST (2.96 ± SD 3.93; p = 0.02). The Intraclass Correlation Coefficient for the retest, calculated on 48 pwMS in a stable phase of the disease, was 0.91 (95 % CI 0.84-0.95). CONCLUSION: The 14-item SDQ has demonstrated high internal consistency, good accuracy, and reliability in pwMS, making it a readily applicable tool for investigating dysphagia in MS.

ChatGPT vs. neurologists: a cross-sectional study investigating preference, satisfaction ratings and perceived empathy in responses among people living with multiple sclerosis.

BACKGROUND: ChatGPT is an open-source natural language processing software that replies to users' queries. We conducted a cross-sectional study to assess people living with Multiple Sclerosis' (PwMS) preferences, satisfaction, and empathy toward two alternate responses to four frequently-asked questions, one authored by a group of neurologists, the other by ChatGPT. METHODS: An online form was sent through digital communication platforms. PwMS were blind to the author of each response and were asked to express their preference for each alternate response to the four questions. The overall satisfaction was assessed using a Likert scale (1-5); the Consultation and Relational Empathy scale was employed to assess perceived empathy. RESULTS: We included 1133 PwMS (age, 45.26 ± 11.50 years; females, 68.49%). ChatGPT's responses showed significantly higher empathy scores (Coeff = 1.38; 95% CI = 0.65, 2.11; p > z < 0.01), when compared with neurologists' responses. No association was found between ChatGPT' responses and mean satisfaction (Coeff = 0.03; 95% CI = - 0.01, 0.07; p = 0.157). College graduate, when compared with high school education responder, had significantly lower likelihood to prefer ChatGPT response (IRR = 0.87; 95% CI = 0.79, 0.95; p < 0.01). CONCLUSIONS: ChatGPT-authored responses provided higher empathy than neurologists. Although AI holds potential, physicians should prepare to interact with increasingly digitized patients and guide them on responsible AI use. Future development should consider tailoring AIs' responses to individual characteristics. Within the progressive digitalization of the population, ChatGPT could emerge as a helpful support in healthcare management rather than an alternative.

Health related quality of life in the domain of physical activity predicts confirmed disability progression in people with relapsing remitting multiple sclerosis.

INTRODUCTION: The diagnosis of the progression phase of Multiple Sclerosis (MS) is still retrospective and based on the objectivation of clinical disability accumulation. OBJECTIVES: To assess whether the Patient Reported Outcomes Measures (PROMs) scores predict the occurrence of disease progression within three years of follow-up. METHODS: Observational prospective multicenter study. Stable Relapsing-Remitting MS (RRMS) patients were enrolled. At enrollment, patients completed the following PROMs: Beck Depression Inventory- II, The Treatment Satisfaction Questionnaire for Medications, Medical Outcomes Study Short Form 36- Item (SF36), Fatigue Severity Scale. EDSS was assessed at enrollment and three years later. The outcome measure was defined as the occurrence of confirmed disability progression (CDP) within three years of follow-up. Univariable and multivariable logistic regression models were performed to study the association between the final score of each test and the outcome. RESULTS: SF36-Physical Functioning (SF36-PF) was the only independent variable associated with the outcome. The ROC curve analysis determined a score of 77.5 at SF36-PF as the cut-off point identifying patients experiencing CDP within three years of follow-up [AUC: 0.66 (95% CI: 0.56-0.75)]. CONCLUSIONS: RRMS patients scoring higher (>77.5) at SF36-PF subscale have a higher likelihood to experience CDP within the next three years.

Disease Reactivation in Secondary Progressive Multiple Sclerosis Patients Switching from Fingolimod to Siponimod: A Case Series.

Siponimod, a selective modulator of sphingosine 1-phosphate receptors 1 (S1P1) and 5 (S1P5), has recently been marketed for patients with Secondary Progressive Multiple Sclerosis (SPMS). Herein, we report three SPMS patients presenting disease reactivation in the first three months after switching from fingolimod to siponimod. Fingolimod binds to S1P1, S1P3, S1P4 and S1P5 receptors. S1P3 holds a central role in eliciting central proinflammatory responses, thus it has been hypothesized that upregulation of S1P3 may be the mechanism behind relapses after switching from fingolimod to siponimod. Further studies are needed to investigate the safety and efficacy of this treatment sequencing.