Therapeutic options for patients with rare rheumatic diseases: a systematic review and meta-analysis

Abstract

Background Rare diseases (RDs) in rheumatology as a group have a high prevalence, but randomized controlled trials are hampered by their heterogeneity and low individual prevalence. To survey the current evidence of pharmacotherapies for rare rheumatic diseases, we conducted a systematic review and meta-analysis. Randomized controlled trials (RCTs) of RDs in rheumatology for different pharmaco-interventions were included into this meta-analysis if there were two or more trials investigating the same RD and using the same assessment tools or outcome parameters. The Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, and PUBMED were searched up to April 2nd 2020. The overall objective of this study was to identify RCTs of RDs in rheumatology, evaluate the overall quality of these studies, outline the evidence of pharmacotherapy, and summarize recommended therapeutic regimens. Results We screened 187 publications, and 50 RCTs met our inclusion criteria. In total, we analyzed data of 13 different RDs. We identified several sources of potential bias, such as a lack of description of blinding methods and allocation concealment, as well as small size of the study population. Meta-analysis was possible for 26 studies covering six RDs: Hunter disease, Behçet’s disease, giant cell arteritis, ANCA-associated vasculitis, reactive arthritis, and systemic sclerosis. The pharmacotherapies tested in these studies consisted of immunosuppressants, such as corticosteroids, methotrexate and azathioprine, or biologicals. We found solid evidence for idursulfase as a treatment for Hunter syndrome. In Behçet’s disease, apremilast and IF-α showed promising results with regard to total and partial remission, and Tocilizumab with regard to relapse-free remission in giant cell arteritis. Rituximab, cyclophosphamide, and azathioprine were equally effective in ANCA-associated vasculitis, while mepolizumab improved the efficacy of glucocorticoids. The combination of rifampicin and azithromycin showed promising results in reactive arthritis, while there was no convincing evidence for the efficacy of pharmacotherapy in systemic sclerosis. Conclusion For some diseases such as systemic sclerosis, ANCA-associated vasculitis, or Behcet's disease, higher quality trials were available. These RCTs showed satisfactory efficacies for immunosuppressants or biological drugs, except for systemic sclerosis. More high quality RCTs are urgently warranted for a wide spectrum of RDs in rheumatology.

Discovery of a novel antibacterial protein CB6-C to target methicillin-resistant Staphylococcus aureus

“…Additionally, seven antibiotics from different classes were tested in combination with antibacterial protein CB6-C. We found that antibacterial protein CB6-C showed synergy with ampicillin, and the combination with other antibiotics produced an additive effect. Some studies reported that the antibacterial effect of ciprofloxacin act on DNA gyrase and polymyxin B act on the cell outer membrane, enrofloxacin inhibit bacterial DNA replication, kanamycin inhibit protein synthesis, ampicillin inhibit cell wall synthesis, azithromycin inhibit bacterial transpeptide and rifampicin inhibits RNA synthesis [ 25 – 28 ]. Based on these antibiotic action mechanisms, the combination of antibacterial protein CB6-C and other antibiotics improved the binding efficiency and ultimately enhanced the antibacterial activity.…”

A diagnostic support system based on pain drawings: binary and k-disease classification of EDS, GBS, FSHD, PROMM, and a control group with Pain2D

“…On the other hand, while deep learning with, e.g., convoluted neural networks (CNNs) works well on images, they need large training data sets. These are difficult to obtain for rare diseases, which poses problems for most studies with rare diseases, including clinical trials [ 23 ]. Therefore, we searched for alternative approaches and decided to utilize Ružička similarity, which is a suitable measure to calculate similarity between images.…”