Ponesimod Compared with Teriflunomide in Patients with Relapsing Multiple Sclerosis in the Active-Comparator Phase 3 OPTIMUM Study : A Randomized Clinical Trial

Importance: To our knowledge, the Oral Ponesimod Versus Teriflunomide In Relapsing Multiple Sclerosis (OPTIMUM) trial is the first phase 3 study comparing 2 oral disease-modifying therapies for relapsing multiple sclerosis (RMS). Objective: To compare the efficacy of ponesimod, a selective sphingosine-1-phosphate receptor 1 (S1P) modulator with teriflunomide, a pyrimidine synthesis inhibitor, approved for the treatment of patients with RMS. Design, Setting, and Participants: This multicenter, double-blind, active-comparator, superiority randomized clinical trial enrolled patients from April 27, 2015, to May 16, 2019, who were aged 18 to 55 years and had been diagnosed with multiple sclerosis per 2010 McDonald criteria, with a relapsing course from the onset, Expanded Disability Status Scale (EDSS) scores of 0 to 5.5, and recent clinical or magnetic resonance imaging disease activity. Interventions: Patients were randomized (1:1) to 20 mg of ponesimod or 14 mg of teriflunomide once daily and the placebo for 108 weeks, with a 14-day gradual up-titration of ponesimod starting at 2 mg to mitigate first-dose cardiac effects of S1Pmodulators and a follow-up period of 30 days. Main Outcomes and Measures: The primary end point was the annualized relapse rate. The secondary end points were the changes in symptom domain of Fatigue Symptom and Impact Questionnaire-Relapsing Multiple Sclerosis (FSIQ-RMS) at week 108, the number of combined unique active lesions per year on magnetic resonance imaging, and time to 12-week and 24-week confirmed disability accumulation. Safety and tolerability were assessed. Exploratory end points included the percentage change in brain volume and no evidence of disease activity (NEDA-3 and NEDA-4) status. Results: For 1133 patients (567 receiving ponesimod and 566 receiving teriflunomide; median [range], 37.0 [18-55] years; 735 women [64.9%]), the relative rate reduction for ponesimod vs teriflunomide in the annualized relapse rate was 30.5% (0.202 vs 0.290; P <.001); the mean difference in FSIQ-RMS, -3.57 (-0.01 vs 3.56; P <.001); the relative risk reduction in combined unique active lesions per year, 56% (1.405 vs 3.164; P <.001); and the reduction in time to 12-week and 24-week confirmed disability accumulation risk estimates, 17% (10.1% vs 12.4%; P =.29) and 16% (8.1% vs 9.9; P =.37), respectively. Brain volume loss at week 108 was lower by 0.34% (-0.91% vs -1.25%; P <.001); the odds ratio for NEDA-3 achievement was 1.70 (25.0% vs 16.4%; P <.001). Incidence of treatment-emergent adverse events (502 of 565 [88.8%] vs 499 of 566 [88.2%]) and serious treatment-emergent adverse events (49 [8.7%] vs 46 [8.1%]) was similar for both groups. Treatment discontinuations because of adverse events was more common in the ponesimod group (49 of 565 [8.7%] vs 34 of 566 [6.0%]). Conclusions and Relevance: In this study, ponesimod was superior to teriflunomide on annualized relapse rate reduction, fatigue, magnetic resonance imaging activity, brain volume loss, and no evidence of disease activity status, but not confirmed disability accumulation. The safety profile was in line with the previous safety observations with ponesimod and the known profile of other S1P receptor modulators

Temporal changes in fecal microbiota of patients infected with COVID-19: a longitudinal cohort

Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a multifaceted disease potentially responsible for various clinical manifestations including gastro-intestinal symptoms. Several evidences suggest that the intestine is a critical site of immune cell development, gut microbiota could therefore play a key role in lung immune response. We designed a monocentric longitudinal observational study to describe the gut microbiota profile in COVID-19 patients and compare it to a pre-existing cohort of ventilated non-COVID-19 patients. Methods From March to December 2020, we included patients admitted for COVID-19 in medicine (43 not ventilated) or intensive care unit (ICU) (14 ventilated) with a positive SARS-CoV-2 RT-PCR assay in a respiratory tract sample. 16S metagenomics was performed on rectal swabs from these 57 COVID-19 patients, 35 with one and 22 with multiple stool collections. Nineteen non-COVID-19 ICU controls were also enrolled, among which 14 developed ventilator-associated pneumonia (pneumonia group) and five remained without infection (control group). SARS-CoV-2 viral loads in fecal samples were measured by qPCR. Results Although similar at inclusion, Shannon alpha diversity appeared significantly lower in COVID-19 and pneumonia groups than in the control group at day 7. Furthermore, the microbiota composition became distinct between COVID-19 and non-COVID-19 groups. The fecal microbiota of COVID-19 patients was characterized by increased Bacteroides and the pneumonia group by Prevotella. In a distance-based redundancy analysis, only COVID-19 presented significant effects on the microbiota composition. Moreover, patients in ICU harbored increased Campylobacter and decreased butyrate-producing bacteria, such as Lachnospiraceae, Roseburia and Faecalibacterium as compared to patients in medicine. Both the stay in ICU and patient were significant factors affecting the microbiota composition. SARS-CoV-2 viral loads were higher in ICU than in non-ICU patients. Conclusions Overall, we identified distinct characteristics of the gut microbiota in COVID-19 patients compared to control groups. COVID-19 patients were primarily characterized by increased Bacteroides and decreased Prevotella. Moreover, disease severity showed a negative correlation with butyrate-producing bacteria. These features could offer valuable insights into potential targets for modulating the host response through the microbiota and contribute to a better understanding of the disease's pathophysiology. Trial registration CER-VD 2020–00755 (05.05.2020) & 2017–01820 (08.06.2018)

Additional file 1 of Temporal changes in fecal microbiota of patients infected with COVID-19: a longitudinal cohort

Additional file 1: Figure S1. Flow chart of the study. Figure S2. Alpha diversity changes over time in ventilated and non-ventilated groups. Figure S3. Jaccard beta-diversity of ventilated and non-ventilated patients at day 0 depicted on NMDS

Additional file 2 of Temporal changes in fecal microbiota of patients infected with COVID-19: a longitudinal cohort

Additional file 2: Table S1. Demographic characteristics of participants based on the ventilatory status in the COVID-19 cohort. Table S2. COVID-19 symptoms, status and treatment of participants based on the ventilatory status in the COVID-19 cohort. Table S3. Risk factors of COVID-19 infected participants. Table S4. Demographic characteristics of Non-COVID-19 ventilated patients. Table S5. Nutrition characteristics of the patients

Siponimod versus placebo in secondary progressive multiple sclerosis (EXPAND): a double-blind, randomised, phase 3 study

International audienc

Prospective observational cohort study on grading the severity of postoperative complications in global surgery research

Background The Clavien–Dindo classification is perhaps the most widely used approach for reporting postoperative complications in clinical trials. This system classifies complication severity by the treatment provided. However, it is unclear whether the Clavien–Dindo system can be used internationally in studies across differing healthcare systems in high- (HICs) and low- and middle-income countries (LMICs). Methods This was a secondary analysis of the International Surgical Outcomes Study (ISOS), a prospective observational cohort study of elective surgery in adults. Data collection occurred over a 7-day period. Severity of complications was graded using Clavien–Dindo and the simpler ISOS grading (mild, moderate or severe, based on guided investigator judgement). Severity grading was compared using the intraclass correlation coefficient (ICC). Data are presented as frequencies and ICC values (with 95 per cent c.i.). The analysis was stratified by income status of the country, comparing HICs with LMICs. Results A total of 44 814 patients were recruited from 474 hospitals in 27 countries (19 HICs and 8 LMICs). Some 7508 patients (16·8 per cent) experienced at least one postoperative complication, equivalent to 11 664 complications in total. Using the ISOS classification, 5504 of 11 664 complications (47·2 per cent) were graded as mild, 4244 (36·4 per cent) as moderate and 1916 (16·4 per cent) as severe. Using Clavien–Dindo, 6781 of 11 664 complications (58·1 per cent) were graded as I or II, 1740 (14·9 per cent) as III, 2408 (20·6 per cent) as IV and 735 (6·3 per cent) as V. Agreement between classification systems was poor overall (ICC 0·41, 95 per cent c.i. 0·20 to 0·55), and in LMICs (ICC 0·23, 0·05 to 0·38) and HICs (ICC 0·46, 0·25 to 0·59). Conclusion Caution is recommended when using a treatment approach to grade complications in global surgery studies, as this may introduce bias unintentionally

The surgical safety checklist and patient outcomes after surgery: a prospective observational cohort study, systematic review and meta-analysis

© 2017 British Journal of Anaesthesia Background: The surgical safety checklist is widely used to improve the quality of perioperative care. However, clinicians continue to debate the clinical effectiveness of this tool. Methods: Prospective analysis of data from the International Surgical Outcomes Study (ISOS), an international observational study of elective in-patient surgery, accompanied by a systematic review and meta-analysis of published literature. The exposure was surgical safety checklist use. The primary outcome was in-hospital mortality and the secondary outcome was postoperative complications. In the ISOS cohort, a multivariable multi-level generalized linear model was used to test associations. To further contextualise these findings, we included the results from the ISOS cohort in a meta-analysis. Results are reported as odds ratios (OR) with 95% confidence intervals. Results: We included 44 814 patients from 497 hospitals in 27 countries in the ISOS analysis. There were 40 245 (89.8%) patients exposed to the checklist, whilst 7508 (16.8%) sustained ≥1 postoperative complications and 207 (0.5%) died before hospital discharge. Checklist exposure was associated with reduced mortality [odds ratio (OR) 0.49 (0.32–0.77); P\u3c0.01], but no difference in complication rates [OR 1.02 (0.88–1.19); P=0.75]. In a systematic review, we screened 3732 records and identified 11 eligible studies of 453 292 patients including the ISOS cohort. Checklist exposure was associated with both reduced postoperative mortality [OR 0.75 (0.62–0.92); P\u3c0.01; I2=87%] and reduced complication rates [OR 0.73 (0.61–0.88); P\u3c0.01; I2=89%). Conclusions: Patients exposed to a surgical safety checklist experience better postoperative outcomes, but this could simply reflect wider quality of care in hospitals where checklist use is routine