ABSTRACT
Introduction: Studies have found associations between air pollution and pneumonia and air pollution is an established risk factors for common COVID-19 complications including pneumonia. Additionally, air pollutants have been identified as possible risk factors for MS onset and relapses. To our knowledge, only one study explored the impact of air pollution on Covid-19 severity specifically among MS patients but has only focused on PM2.5 exposures. Aim(s): We aim to evaluate the association between long-term exposure to air pollution and COVID-19 severity, described as developing pneumonia in a population of COVID-19-positive MS patients. Method(s): Data on COVID-19 infection among MS patients were extracted from an Italian web-based platform (Musc-19). A casecontrol study was designed including patients with and without pneumonia at a case-control ratio of 1:2 and 615 patients were included. The included patients were asked to provide information on the geographical area where they had spent most time in the previous 5 years. When this information was missing, the address of the MS center was used as a proxy and evaluated in sensitivity analysis. Air quality was assessed as annual average particulate matter (PM2.5 and PM10) and Nitrogen Dioxide (NO2) ground-level concentrations derived from air quality model results as provided by the 'Copernicus Atmospheric Monitoring Service', and evaluated as categorical exposures (terciles). The association between pollutants and COVID-19 pneumonia was studied using logistic regression models, also adjusting for confounders (age, sex, BMI, comorbidities, EDSS, MS type, duration and treatments). Result(s): Detailed exposure was obtained for 491 patients, of whom 34% had pneumonia. Higher concentrations of air pollutants were associated with increased odds of developing COVID-19 pneumonia in both unadjusted and adjusted models (Adjusted models estimates: PM2.5: 2nd vs 1st tercile OR(95% CI)=2.09 (1.20;3.65), 3rd vs 1st tercile OR(95% CI)=2.26(1.29;3.96);PM10: 2nd vs 1st tercile OR(95% CI)=1.83(1.05;3.20), 3rd vs 1st tercile OR(95% CI)=2.12(1.22;3.68);NO2: 3rd vs 1st tercile OR(95% CI)=2.12(1.21;3.69)). Results remained consistent in the sensitivity analysis. Conclusion(s): Higher long-term concentrations of PM2.5, PM10 and NO2 were associated with COVID-19 pneumonia among MS patients. Urgent measures to reduce air pollution should be adopted especially to protect the most vulnerable population.
ABSTRACT
INTRODUCTION: Few data are available on adverse events (AE) associated to vaccines in persons with multiple sclerosis (pwMS). AIMS: to study the incidence of acute phase AE (AP-AE) related to SARS-CoV-2 mRNA vaccines in pwMS compared to a control group, and to analyze the association between AP-AE and disease modifying treatments (DMT). METHODS: This was a cross-sectional study on 438 PwMS and 481 age- and sex-matched subjects not affected by dysimmune diseases that underwent two doses of SARS-CoV-2 mRNA BNT162b2 vaccine (Pfizer/BioNtech). RESULTS: Two hundred and twenty five (51.4%) pwMS complained of ≥1 AP-AE after the first dose, 269 (61.4%) after the second dose. A logistic regression analysis revealed that only pwMS on Fingolimod and Ocrelizumab did not show a higher risk of developing AP-AE. The likelihood to present with ≥1 AP-AE, after correcting for age and sex, was significantly higher in pwMS than controls. CONCLUSIONS: This study reports qualitative and quantitative features of AP-AE associated with the first and second doses of SARS-CoV-2 vaccine in a large sample of pwMS. The only risk factor identified for developing AP-AE is female gender. AntiCD-20 monoclonal antibodies and S1P inhibitors are associated with a lower risk of AP-AE occurrence.
ABSTRACT
Introduction: Studies have pointed out that air pollution longterm exposure may play a role in the severity and prognosis of SARS-CoV-2 infections. Additionally, air pollution has been associated to MS prevalence and course. However, the role of air pollution in COVID-19 severity has never been explored specifically among MS patients. Aims: To explore the association between air pollution assessed by PM2.5 levels and COVID-19 severity among MS patients. Methods: Demographic and clinical characteristics as well as data about Covid-19 severity were extracted from an Italian webbased platform (Musc-19 project) containing clinician-reported data from 118 Italian MS centers. PM2.5 ground-level concentrations were derived from air quality model results, as provided by the 'Copernicus Atmospheric Monitoring Service' (CAMS). Ordered logistic regression models were used to assess the association between PM2.5 (continuous and in tertiles) and Covid-19 prognosis (defined on three levels as mild course, hospitalization, and intensive care unit (ICU) admission or death) while controlling for possible confounders. Results: PM2.5 concentrations were available for 1517 MS patients, of whom 1321(87%) were classified as mild Covid-19 cases, 172(11%) were hospitalized and 24(2%) were admitted to ICU or died. Higher concentrations of PM2.5 were associated with increased odds of developing a worst Covid-19 prognosis (10-unit increase in PM2.5: OR(95% CI)=1.76(1.16-2.67) p-value=0.008;3rd vs 1st tertile: OR(95% CI)=1.74(1.17-2.59) p-value=0.006). Results remained consistent when we included only the Covid-19 cases confirmed by a nasopharyngeal swab (N=1087). Conclusions: Higher concentrations of PM2.5 are associated with Covid-19 severity among MS patients. Further studies are needed to evaluate the impact of other air pollutants, but urgent measures to reduce air pollution must be surely adopted.
ABSTRACT
Introduction: Patients with multiple sclerosis (MS) often receive disease-modifying therapies (DMTs) which can reduce the response to vaccines. BNT162b2 (Pfizer-BioNTech) is the first COVID-19 vaccine authorized in Italy but was not evaluated in MS patients receiving DMTs. Objectives: To evaluate serological response and safety to BNT162b2 in patients with MS. Methods: This is an early multicenter, case-control and prospective study. Patients were healthcare workers (HCWs) with MS, receiving at least one DMT, and having received BNT162b2. Blood samples were collected between 2 and 6 weeks after the second vaccine dose and analyzed to quantify anti-Spike antibodies (Abbott). Anti-Spike cut-off for response was set at 7.1 BAU/ ml. Anti-Spike levels in patients considered at-risk of reduced response were compared to those considered non-at-risk, according to literature and expert consensus. Anti-Spike levels were compared to those of a control population of HCWs, without MS or immune-related disease, untreated, and having received BNT162b2. Total follow up was of 9 weeks from the first vaccine dose. Results: From February 2020, 39 MS patients were enrolled. One patient, treated with ocrelizumab, did not develop serological response (1.8 BAU/ml). The remaining patients responded to the vaccine, including two ocrelizumab-treated patients. The control population consisted of 273 HCWs. All controls responded to BNT162b2. Median anti-Spike levels in patients (1471.0 BAU/ ml;range 779.7-2357.0) and controls (1479.0 BAU/ml;range 813.1-2528.0) were comparable. Patients receiving at-risk treatments (n=9;5 fingolimod, 3 ocrelizumab, 1 natalizumab) showed significantly reduced median anti-Spike levels (241.9 BAU/ml;range 40.2-530.0) compared to non-at-risk (n=30;15 dimethyl fumarate, 5 teriflunomide, 4 interferons, 3 glatiramer acetate, 2 cladribine, 1 alemtuzumab) ones (1707.7 BAU/ml;range 1356.2- 2432.8) (p<0.001). No COVID-19 cases were reported. Two patients had a clinical MS relapse after 17 and 30 days after the second dose. A causal relationship with the vaccination could not be established. Conclusions: In our study, most MS patients produce a serological response to BNT162b2 similar to non-MS controls;however, at-risk DMTs resulted in reduced anti-Spike levels and one ocrelizumab- treated patient did not respond. These observations should be better investigated and replicated in larger studies to support clinical decision in COVID-19 vaccine management.
ABSTRACT
Purpose/Background: There is no sufficient evidence as to whether stool DNA methylation tests allow prioritizing patients to colonoscopy. Due to the COVID-19 pandemic, there will be a waitlist for rescheduling colonoscopies once the mitigation is lifted. The aim of this meta-analysis was to evaluate the accuracy of stool DNA methylation tests in detecting colorectal cancer. Methods/Interventions: The PubMed, Cochrane Library, and MEDLINE via Ovid were searched. Studies reporting accuracy (Sackett phase 2 or 3) of stool DNA methylation tests to detect sporadic colorectal cancer were included. The DerSimonian-Laird method with random-effects model was utilized for meta-analysis. Results/Outcome(s): Forty-six studies totaling 16,149 patients were included in the meta-analysis. Pooled sensitivity and specificity of all single genes and combinations was 62.7% (57.7%, 67.4%) and 91% (89.5%, 92.2%), respectively. Combinations of genes provided higher sensitivity as compared to single genes [80.8% (75.1%, 85.4%) vs. 57.8% (52.3%, 63.1%)] with no significant decrease in specificity [87.8% (84.1%, 90.7%) vs. 92.1% (90.4%, 93.5%)]. The most accurate single gene was found to be SDC2 with a sensitivity of 83.1% (72.6%, 90.2%) and a specificity of 91.2% (88.6%, 93.2%). Conclusions/Discussion: Stool DNA methylation tests have high specificity with lower sensitivity allowing to rule in the diagnosis of colorectal cancer. Combination of genes increases sensitivity as compared to single gene tests. The single most accurate gene is SDC2, which should be considered in future tests.
ABSTRACT
Purpose/Background: Multitarget stool DNA testing has been increasingly used during the screening colonoscopy moratorium in COVID-19 pandemic epicenters. The aim of this meta-analysis was to evaluate the accuracy of NDRG4 alone or in combination with other genes included in commercially available stool tests to detect colorectal cancer. Methods/Interventions: The PubMed, Cochrane Library, and MEDLINE via Ovid were searched. Studies reporting accuracy (Sackett phase 2 or 3) of stool DNA methylation tests to detect sporadic colorectal cancer were included. The DerSimonian-Laird method with random-effects model was utilized for meta-analysis. Pooled sensitivity, specificity, positive and negative likelihood ratios, and area under curve (AUC) were calculated. Results/Outcome(s): The pooled sensitivity and specificity of NDRG4 were found to be [0.564 (0.383, 0.729);I2=88.3%] and [0.897 (0.824, 0.941);I2=41.2%], respectively. The pooled negative and positive likelihood ratios were found to be [0.460 (0.311, 0.682);I2=0%] and [4.959 (3.349, 7.344);I2=0%]. AUC was 0.65 (0.56, 0.73). The pooled sensitivity and specificity of the combination of genes were [0.911 (0.839, 0.952)] and [0.819 (0.685, 0.904)], respectively. The pooled negative and positive likelihood ratios were found to be [0.106 (0.075, 0.151);I2=86.6%] and [5.084 (2.856, 9.048);I2=95.1%]. AUC was 0.87 (0.66, 0.90). Conclusions/Discussion: NDRG4 has high specificity with lower sensitivity allowing to rule in the diagnosis of colorectal cancer. Combination of genes increases sensitivity as compared to single gene tests, while slightly decreasing specificity. Further performance evaluation research is required to better understand potential role of stool DNA methylation tests, especially in a screening setting.