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

BACKGROUND AND OBJECTIVE: The diagnosis of rare diseases (RDs) is often challenging due to their rarity, variability and the high number of individual RDs, resulting in a delay in diagnosis with adverse effects for patients and healthcare systems. The development of computer assisted diagnostic decision support systems could help to improve these problems by supporting differential diagnosis and by prompting physicians to initiate the right diagnostic tests. Towards this end, we developed, trained and tested a machine learning model implemented as part of the software called Pain2D to classify four rare diseases (EDS, GBS, FSHD and PROMM), as well as a control group of unspecific chronic pain, from pen-and-paper pain drawings filled in by patients. METHODS: Pain drawings (PDs) were collected from patients suffering from one of the four RDs, or from unspecific chronic pain. The latter PDs were used as an outgroup in order to test how Pain2D handles more common pain causes. A total of 262 (59 EDS, 29 GBS, 35 FSHD, 89 PROMM, 50 unspecific chronic pain) PDs were collected and used to generate disease specific pain profiles. PDs were then classified by Pain2D in a leave-one-out-cross-validation approach. RESULTS: Pain2D was able to classify the four rare diseases with an accuracy of 61-77% with its binary classifier. EDS, GBS and FSHD were classified correctly by the Pain2D k-disease classifier with sensitivities between 63 and 86% and specificities between 81 and 89%. For PROMM, the k-disease classifier achieved a sensitivity of 51% and specificity of 90%. CONCLUSIONS: Pain2D is a scalable, open-source tool that could potentially be trained for all diseases presenting with pain.

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

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.