Search

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 p = 0.31), but higher for low/medium efficacy DMTs (Coeff = 0.09; p 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 p 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.

Aims: Natalizumab is approved as an infusion every 4 weeks (standard-interval dosing [SID]) in relapsing-remitting multiple sclerosis (MS). Extended-interval dosing (EID) reduces risk of progressive multifocal leukoencephalopathy (PML) compared with SID, but the impact on healthcare resources and costs remains unknown. Methods: In this population-based study, we included 208 natalizumab-treated MS patients who were classified into EID (≤15 infusions in the previous 18 months; n = 51; age = 33.7 ± 11.1 years; female = 72.5%) and SID (>15 infusions in the previous 18 months; n = 157; age = 36.5 ± 10.8 years; female = 68.1%) groups. Results: Natalizumab EID had fewer MS outpatient visits (p = 0.01) and related costs (p = 0.03), and lower natalizumab costs (p

Spinal cord and gadolinium (Gd)-enhanced magnetic resonance imaging (MRI) can provide additional information to brain MRI to determine prognosis of multiple sclerosis (MS). However, the real-world impact of routine use of brain MRI with spinal cord and/or Gd sequences is unknown. Our aim was to evaluate the effect of brain, spinal cord and Gd MRI on treatment decisions in MS.In this 2015-2020 population-based study, we performed a retrospective analysis on MS patients resident in the Campania Region (South Italy), with disease modifying treatment (DMT) prescription (n = 6,161). DMTs were classified as platform (dimethyl fumarate, glatiramer acetate, interferon-beta, peg-interferon-beta, teriflunomide), or high-efficacy (alemtuzumab, cladribine, fingolimod, natalizumab, ocrelizumab). We evaluated the association between binary MRI variables and switch from platform to high-efficacy DMT using multivariable logistic regression.The likelihood of switch from platform to high-efficacy DMT was 47% higher when including post-Gd acquisitions to brain and/or spinal cord MRI, 59% higher when including spinal cord acquisitions to brain MRI, and 132% higher when including any MRI compared with no MRI (all p 0.05). The likelihood of switch to high-efficacy DMT decreased over time from treatment start.Our results show that spinal cord and Gd MRI acquisitions can provide relevant information to influence subsequent treatment decisions, especially in early treatment phases, compared with stand-alone brain MRI.

Objective: We aim to validate an algorithm based on routinely-collected healthcare data to detect incidence of multiple sclerosis (MS) in the Campania Region (South Italy) and to explore its spatial and temporal variations. Methods: We included individuals resident in the Campania Region who had at least one MS record in administrative datasets (drug prescriptions, hospital discharge, outpatients), from 2015 to 2020. We merged administrative to the clinical datasets to ascertain the actual date of diagnosis, and validated the minimum interval from our study baseline (Jan 1, 2015) to first MS records in administrative datasets to detect incident cases. We used Bayesian approach to explore geographical distribution, also including deprivation index as a covariate in the estimation model. We used the capture-recapture method to estimate the proportion of undetected cases. Results: The best performance was achieved by the 12-month interval algorithm, detecting 2,150 incident MS cases, with 74.4% sensitivity (95%CI = 64.1%, 85.9%) and 95.3% specificity (95%CI = 90.7%, 99.8%). The cumulative incidence was 36.68 (95%CI = 35.15, 38.26) per 100,000 from 2016 to 2020. The mean annual incidence was 7.34 (95%CI = 7.03, 7.65) per 100,000 people-year. The geographical distribution of MS relative risk shows a decreasing east-west incidence gradient. The number of expected MS cases was 11% higher than the detected cases. Conclusions: We validated a case-finding algorithm based on administrative data to estimate MS incidence, and its spatial/temporal variations. This algorithm provides up-to-date estimates of MS incidence, and will be used in future studies to evaluate changes in MS incidence in relation to different risk factors.

Cardiovascular disease is one of the most frequent causes of long-term sickness absence from work. The study aims to develop and validate a score to assess the 10-year risk of unsuitability for work accounting for the cardiovascular risk. The score can be considered as a prevention tool that would improve the cardiovascular risk assessment during health surveillance visits under the assumption that a high cardiovascular risk might also translate into high risk of unsuitability for work. A total of 11,079 Italian workers were examined, as part of their scheduled occupational health surveillance. Cox proportional hazards regression models were employed to derive risk equations for assessing the 10-year risk of a diagnosis of unsuitability for work. Two scores were developed: the CROMA score (Cardiovascular Risk in Occupational Medicine) included age, sex, smoking status, blood pressure (systolic and diastolic), body mass index, height, diagnosis of hypertension, diabetes, ischemic heart disease, mental disorders and prescription of antidiabetic and antihypertensive medications. The CROMB score was the same as CROMA score except for the inclusion of only variables statistically significant at the 0.05 level. For both scores, the expected risk of unsuitability for work was higher for workers in the highest risk class, as compared with the lowest. Moreover results showed a positive association between most of cardiovascular risk factors and the risk of unsuitability for work. The CROMA score demonstrated better calibration than the CROMB score (11.624 (p-value: 0.235)). Moreover, the CROMA score, in comparison with existing CVD risk scores, showed the best goodness of fit and discrimination.