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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. [ABSTRACT FROM AUTHOR]

Background: COVID-19 pandemic has affected the management of multiple sclerosis (MS). Objective: To explore the impact of COVID-19 on healthcare delivery to people with MS and the subsequent recovery of the system. Methods: In this population-based study in the Campania Region (Italy), we included people with MS across pre-COVID-19, lockdown, pre-vaccination, and vaccination periods. Differences in continuous outcomes between periods were explored using linear mixed models (annualized hospitalization rate (AHR) and adherence measured as medication possession ratio (MPR)). Differences in disease-modifying treatment (DMT) prescription rates (first DMT prescription, any DMT switch, switch from platform to highly effective DMT, and combination of first DMT prescription and any DMT switch) were assessed using an interrupted time series design. Results: Compared with pre-COVID-19, AHR decreased during the lockdown (Coeff = 0.64;95%CI = -0.69, -0.59; p < 0.01), and remained lower during pre-vaccination and vaccination periods. Adherence decreased during pre-vaccination (Coeff = -0.04;95%CI = -0.05, -0.03; p < 0.01) and vaccination periods (Coeff = -0.07;95%CI = -0.08, -0.07; p < 0.01). After the lockdown, there was an increase in any DMT switch (IRR 2.05 95%CI 1.38,3.05; p < 0.01), in switch from platform to highly effective DMTs (IRR 4.45;95%CI 2.48,8.26; p < 0.01) and in first DMT prescriptions (IRR 2.48;95%CI 1.64,3.74; p < 0.01). Conclusions: DMT prescriptions quickly returned to pre-pandemic levels, reflecting good health system recovery. However, adherence has remained lower than the past, as from suboptimal care. Assessing long-term COVID-19 impact on MS healthcare is warranted. [ABSTRACT FROM AUTHOR]

Aims: We aim to provide real-world evidence on the use of ocrelizumab for treating multiple sclerosis (MS), with specific regard to prescription pattern, adherence, persistence, healthcare resource utilization and related costs, also in relation to other disease-modifying treatments (DMTs). Methods: We included 2495 people with MS from the Campania Region (South Italy) who received first or switch DMT prescription from Jan 2018 to Dec 2020, and with at least 6-month follow-up. We collected hospital discharge records, drug prescriptions, and related costs, and calculated persistence (time from first prescription to discontinuation or switch to other DMT), adherence (proportion of days covered (PDC)), annualized hospitalization rate (AHR) for MS-related hospital admissions, and DMT costs. Results: Ocrelizumab was the most commonly prescribed DMT (n = 399; age = 45.74 ± 10.98 years; females = 224), after dimethyl fumarate (n = 588) and fingolimod (n = 401); 26% patients treated with ocrelizumab were naïve. When compared with ocrelizumab, the risk of discontinuation was higher for other highly active DMTs (HR = 3.78; p = 0.01), and low/medium efficacy DMTs (HR = 7.59; p < 0.01). When compared with ocrelizumab, PDC was similar to other highly active DMTs (Coeff = 0.01; p = 0.31), but higher for low/medium efficacy DMTs (Coeff = 0.09; p < 0.01). When compared with ocrelizumab, AHR was similar to other highly active DMTs (Coeff = 0.01; p = 0.51), and low/medium efficacy DMTs (Coeff = 0.01; p = 0.55). When compared with ocrelizumab, DMT monthly costs were higher for other highly active DMTs (Coeff = 92.30; p < 0.01), but lower for low/medium efficacy DMTs (Coeff = − 1043.61; p < 0.01). Discussion: Ocrelizumab was among the most frequently prescribed DMTs, with 26% prescriptions to treatment-naïve patients, suggesting its relevance in addressing unmet clinical needs (e.g., first approved treatment for primary progressive MS). Ocrelizumab was associated with the highest persistence, confirming its favorable benefit-risk profile. Costs for ocrelizumab were lower than those associated to similarly effective DMTs, in absence of changes in healthcare resource utilization. [ABSTRACT FROM AUTHOR]