We aim to validate a case-finding algorithm to detect individuals with multiple sclerosis (MS) using routinely collected healthcare data, and to assess the prevalence of MS in the Campania Region (South Italy). To identify individuals with MS living in the Campania Region, we employed an algorithm using different routinely collected healthcare administrative databases (hospital discharges, drug prescriptions, outpatient consultations with payment exemptions), from 1 January 2015 to 31 December 2017. The algorithm was validated towards the clinical registry from the largest regional MS centre (n = 1460). We used the direct method to standardise the prevalence rate and the capture-recapture method to estimate the proportion of undetected cases. The case-finding algorithm including individuals with at least one MS record during the study period captured 5362 MS patients (females = 64.4%; age = 44.6 ± 12.9 years), with 99.0% sensitivity (95% CI = 98.3%, 99.4%). Standardised prevalence rate per 100,000 people was 89.8 (95% CI = 87.4, 92.2) (111.8 for females [95% CI = 108.1, 115.6] and 66.2 for males [95% CI = 63.2, 69.2]). The number of expected MS cases was 2.7% higher than cases we detected. We developed a case-finding algorithm for MS using routinely collected healthcare data from the Campania Region, which was validated towards a clinical dataset, with high sensitivity and low proportion of undetected cases. Our prevalence estimates are in line with those reported by international studies conducted using similar methods. In the future, this cohort could be used for studies with high granularity of clinical, environmental, healthcare resource utilisation, and pharmacoeconomic variables.

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Background. We compared the prevalence of SARS-CoV-2 IgG/IgM in multiple sclerosis (MS), low-risk, and high-risk populations and explored possible clinical correlates. Methods. In this cross-sectional study, we recruited MS patients, low-risk (university staff from non-clinical departments), and high-risk individuals (healthcare staff from COVID-19 wards) from 11 May to 15 June 2020. We used lateral flow immunoassay to detect SARS-CoV-2 IgG and IgM. We used t-test, Fisher’s exact test, chi square test, or McNemar’s test, as appropriate, to evaluate between-group differences. Results. We recruited 310 MS patients (42.3 ± 12.4 years; females 67.1%), 862 low-risk individuals (42.9 ± 13.3 years; females 47.8%), and 235 high-risk individuals (39.4 ± 10.9 years; females 54.5%). The prevalence of SARS-CoV-2 IgG/IgM in MS patients (n = 9, 2.9%) was significantly lower than in the high-risk population (n = 25, 10.6%) (p < 0.001), and similar to the low-risk population (n = 11, 1.3%) (p = 0.057); these results were also confirmed after random matching by age and sex (1:1:1). No significant differences were found in demographic, clinical, treatment, and laboratory features. Among MS patients positive to SARS-CoV-2 IgG/IgM (n = 9), only two patients retrospectively reported mild and short-lasting COVID-19 symptoms. Conclusions. MS patients have similar risk of SARS-CoV-2 infection to the general population, and can be asymptomatic from COVID-19, also if using treatments with systemic immunosuppression.

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Pivotal trials showed the effectiveness of the monoclonal antibody ocrelizumab in relapsing and progressive multiple sclerosis (MS). However, data on everyday practice in MS patients and markers of treatment effectiveness are scarce. We aimed to collect real-world data from ocrelizumab-treated MS patients, relapsing-remitting (RR) and progressive MS patients (PMS), including active secondary progressive MS (aSPMS) and primary progressive MS (PPMS) patients, and to explore potential prognostic factors of clinical outcome. Patients were enrolled at MS centres in the Campania region, Italy. We collected clinic-demographic features retrospectively one year before ocrelizumab start (T−1), at ocrelizumab start (T0), and after one year from ocrelizumab start (T1). We explored possible clinical markers of treatment effectiveness in those patients receiving ocrelizumab treatment for at least one year using multilevel-mixed models. We included a total of 383 MS patients (89 RRMS and 294 PMS; 205 females, mean age: 45.8 ± 11.2, disease duration: 12.7 ± 11.6 years). Patients had a mean follow-up of 12.4 ± 8.2 months, and 217 patients completed one-year ocrelizumab treatment. Overall, EDSS increased from T−1 to T0 (coeff. = 0.30, 95% coefficient interval [CI] = 0.19–0.41, p < 0.001) without a further change between T0 and T1 (p = 0.61). RRMS patients did not show an EDSS change between T−1 and T0 nor between T0 and T1. Conversely, PMS patients showed EDSS increase from T−1 to T0 (coeff. = 0.34, 95% CI = 0.22–0.45, p < 0.001) without a further change between T0 and T1 (p = 0.21). PMS patients with a time from conversion shorter than 2 years showed increased EDSS from T−1 to T0 (coeff. = 0.63, 95% CI = 0.18–1.08, p = 0.006) without a further change between T0 and T1 (p = 0.94), whereas PMS patients with a time from conversion longer than 2 years showed increased EDSS from T0 to T1 (coeff. = 0.30, 95% CI = 0.11–0.49, p = 0.002). Naïve patients showed an EDSS decrease between T0 and T1 (coeff. = −0.30, 95% CI = −0.50–−0.09, p = 0.004). In conclusion, our study highlighted that early ocrelizumab treatment is effective in modifying the disability accrual in MS patients.