NORdic trial of oral Methylprednisolone as add-on therapy to Interferon beta-1a for treatment of relapsing-remitting Multiple Sclerosis (NORMIMS study): a randomised, placebo-controlled trial

Treatment of relapsing-remitting multiple sclerosis with interferon beta is only partly effective, and new more effective and safe strategies are needed. Our aim was to assess the efficacy of oral methylprednisolone as an add-on therapy to subcutaneous interferon beta-1a to reduce the yearly relapse rate in patients with relapsing-remitting multiple sclerosis. Methods: NORMIMS (NORdic trial of oral Methylprednisolone as add-on therapy to Interferon beta-1a for treatment of relapsing-remitting Multiple Sclerosis) was a randomised, placebo-controlled trial done in 29 neurology departments in Denmark, Norway, Sweden, and Finland. We enrolled outpatients with relapsing-remitting multiple sclerosis who had had at least one relapse within the previous 12 months despite subcutaneous interferon beta-1a treatment (44 microg three times per week). We randomly allocated patients by computer to add-on therapy of either 200 mg methylprednisolone or matching placebo, both given orally on 5 consecutive days every 4 weeks for at least 96 weeks. The primary outcome measure was mean yearly relapse rate. Primary analyses were by intention to treat. This trial is registered, number ISRCTN16202527. Findings: 66 patients were assigned to interferon beta and oral methylprednisolone and 64 were assigned to interferon beta and placebo. A high proportion of patients withdrew from the study before week 96 (26% [17 of 66] on methylprednisolone vs 17% [11 of 64] on placebo). The mean yearly relapse rate was 0.22 for methylprednisolone compared with 0.59 for placebo (62% reduction, 95% CI 39-77%; p<0.0001). Sleep disturbance and neurological and psychiatric symptoms were the most frequent adverse events recorded in the methylprednisolone group. Bone mineral density had not changed after 96 weeks. Interpretation: Oral methylprednisolone given in pulses every 4 weeks as an add-on therapy to subcutaneous interferon beta-1a in patients with relapsing-remitting multiple sclerosis leads to a significant reduction in relapse rate. However, because of the small number of patients and the high dropout rate, these findings need to be corroborated in larger cohorts

Respiratory dysfunction three months after severe COVID-19 is associated with gut microbiota alterations

Background: Although coronavirus disease 2019 (COVID-19) is primarily a respiratory infection, mounting evidence suggests that the gastrointestinal (GI) tract is involved in the disease, with gut barrier dysfunction and gut microbiota alterations being related to disease severity. Whether these alterations persist and are related to long-term respiratory dysfunction remains unknown. Methods: Plasma was collected during hospital admission and after three months from the NOR-Solidarity trial (n = 181) and analysed for markers of gut barrier dysfunction and inflammation. At the three-month follow-up, pulmonary function was assessed by measuring the diffusing capacity of the lungs for carbon monoxide (DLCO ). Rectal swabs for gut microbiota analyses were collected (n = 97) and analysed by sequencing the 16S rRNA gene. Results: Gut microbiota diversity was reduced in COVID-19 patients with respiratory dysfunction, defined as DLCO below the lower limit of normal three months after hospitalisation. These patients also had an altered global gut microbiota composition, with reduced relative abundance of 20 bacterial taxa and increased abundance of five taxa, including Veillonella, potentially linked to fibrosis. During hospitalisation, increased plasma levels of lipopolysaccharide-binding protein (LBP) were strongly associated with respiratory failure, defined as pO2 /fiO2 -(P/F ratio)Respiratory dysfunction three months after severe COVID-19 is associated with gut microbiota alterationsacceptedVersio

Efficacy and safety of baricitinib in hospitalized adults with severe or critical COVID‑19 (Bari‑SolidAct): a randomised, double‑blind, placebo‑controlled phase 3 trial

Background Baricitinib has shown efcacy in hospitalized patients with COVID-19, but no placebo-controlled trials have focused specifcally on severe/critical COVID, including vaccinated participants. Methods Bari-SolidAct is a phase-3, multicentre, randomised, double-blind, placebo-controlled trial, enrolling participants from June 3, 2021 to March 7, 2022, stopped prematurely for external evidence. Patients with severe/ critical COVID-19 were randomised to Baricitinib 4 mg once daily or placebo, added to standard of care. The primary endpoint was all-cause mortality within 60 days. Participants were remotely followed to day 90 for safety and patient related outcome measures. Results Two hundred ninety-nine patients were screened, 284 randomised, and 275 received study drug or placebo and were included in the modifed intent-to-treat analyses (139 receiving baricitinib and 136 placebo). Median age was 60 (IQR 49–69) years, 77% were male and 35% had received at least one dose of SARS-CoV2 vaccine. There were 21 deaths at day 60 in each group, 15.1% in the baricitinib group and 15.4% in the placebo group (adjusted absolute diference and 95% CI −0.1% [−8·3 to 8·0]). In sensitivity analysis censoring observations after drug discontinuation or rescue therapy (tocilizumab/increased steroid dose), proportions of death were 5.8% versus 8.8% (−3.2% [−9.0 to 2.7]), respectively. There were 148 serious adverse events in 46 participants (33.1%) receiving baricitinib and 155 in 51 participants (37.5%) receiving placebo. In subgroup analyses, there was a potential interaction between vaccination status and treatment allocation on 60-day mortality. In a subsequent post hoc analysis there was a signifcant interac‑ tion between vaccination status and treatment allocation on the occurrence of serious adverse events, with more respiratory complications and severe infections in vaccinated participants treated with baricitinib. Vaccinated partici‑ pants were on average 11 years older, with more comorbidities. Conclusion This clinical trial was prematurely stopped for external evidence and therefore underpowered to con‑ clude on a potential survival beneft of baricitinib in severe/critical COVID-19. We observed a possible safety signal in vaccinated participants, who were older with more comorbidities. Although based on a post-hoc analysis, these fnd‑ ings warrant further investigation in other trials and real-world studies

MPX-RESPONSE

A clinical research network to improve the management of Mpox virus diseas

The Analysis of Continuous Mark-Recapture Data

The purpose of this thesis is to develop a general methodology for the analysis of continuously sampled data from open populations. The thesis consists of four parts and one appendix. The four parts may be read independently of each other. The appendix consists of a submitted article based on the developments in Part III. The aim of Part I is to present the major contributions to the mark-recapture methodology over the last century. It is not a complete reference to the subject, but gives the reader an introduction to mark-recapture models. In addition to the classic models, some recent development of interest is included. The introduction of Bayesian statistics to mark-recapture models is covered, in addition to the analysis of continuously sampled data from closed populations. With the ever increasing amount of models available, the need for model selection tools is grave. We look at some of the most used methods such as the Likelihood Ratio Test (LRT) and the Akaike Information Criterion in connection with mark-recapture models. For the Bayesian models, we review some of the latest developments in model selection such as the Deviance Information Criterion. Part II addresses the challenge of analysing a set of continuously sampled markrecapture data from a Norwegian coastal cod population (the Risør data set). These data are already analysed with discrete models by Julliard et al. (2001), but it is suggested that this approach may lead to biased estimates of the survival. The approach taken in Part II is to renounce the discrete models for mark-recapture data, and to develop an new, continuous model. The analysis of this model is preformed by a Monte Carlo EM algorithm. The survival and capture estimates are presented and compared with the estimates of Julliard et al. (2001). The Risør data set contains much auxilliary information such as size at release and capture, release location and capture gear. A semi-parametric multiplicative hazard model is implemented to include some of this information. The EM algorithm from Part II is developed further in Part III. Instead of a Monte Carlo simulation in the E step of the algorithm, an analytic solution is presented. The algorithm is developed for the discrete Cormack-Jolly-Seber(CJS) model, and shows nice convergence and stability properties for this model. An argument is then given for applying the CJS model directly to continuous data. The stability of the EM algorithm makes it suitable for such analysis. When covariate information is to be included into the analysis of continuous data, the CJS model is no longer appropriate. A semi-parametric multiplicative model for the survial and capture processes is presented as an answer to this challenge. The EM algorithm is still used for analysis. The methodology is applied to a set of continuously sampled data on the Eurpean Dipper, gathered by G. Marzolin (Marzolin (2002)). These data have been analysed discretely by Lebreton et al. (1992) (frequentistic) and by Brooks et al. (2000) (Bayesian). One of the assumptions of the CJS model is that the sampling is done instantaneously. The aim of Part IV is to assess the consequences of violating this assumption. A simulation analysis showes that there is potential for substantial bias of the survival estimates when the sampling periods are long

Instrumental Variable Analysis with Categorical Treatment

Current instrumental variable (IV) methodology focuses mainly on estimating causal effects for a dichotomous or an ordinal treatment variable. Situations with more than two unordered treatments are less explored. The challenge is that assumptions needed to derive point-estimators become increasingly stronger with the number of relevant treatment alternatives. In this paper, we aim at deriving causal point-estimators for head-to-head comparisons of the effect of multiple relevant treatments or interventions. We will achieve this with a set of plausible and well-defined rationality assumptions while only considering ordinal instruments. We demonstrate that our methodology provides asymptotically unbiased estimators in the presence of unobserved confounding effects in a simulation study. We then apply the method to compare the effectiveness of five anti-inflammatory drugs in the treatment of rheumatoid arthritis (RA). For this, we use a clinical data set from an observational study in Norway, where price is the primary determinant of the preferred drug and can therefore be considered as an instrument. The developed methodology provides an important addition to the toolbox for causal inference when comparing more than two interventions influenced by an IV

TBCOX2 - A phase I/II randomized trial on Safety and Immunogenicity of the Therapeutic H56:IC31 Vaccine and adjunctive Cyclooxygenase-2-inhibitor in patients with Tuberculosis

This first-in-human randomized clinical trial at Oslo University Hospital, Norway on patients with tuberculosis shows that the vaccine H56:I31 developed by Statens Serum Institut is safe and immunogenic during active tuberculosis disease and could serve as host-directed-therapy to improve prognosis and combat the tuberculosis pandemi

NESTIMATOR

The Norwegian tender system for biologic drugs used as an instrument for head-to-head comparisons of treatment in inflammatory arthriti