ObjectivesThe aims of this study were to update the evidence on the incidence and prevalence rates of vaccine preventable infections (VPI) in patients with autoimmune inflammatory rheumatic diseases (AIIRD) and compare the data to the general population when available.MethodsA literature search was performed using Medline, Embase and Cochrane library (October 2009 to August 2018). The primary outcome was the incidence or prevalence of VPI in the adult AIIRD population. Meta-analysis was performed when appropriate.ResultsSixty-three publications out of 3876 identified records met the inclusion criteria: influenza (n=4), pneumococcal disease (n=7), hepatitis B (n=10), herpes zoster (HZ) (n=29), human papillomavirus (HPV) infection (n=13). An increased incidence of influenza and pneumococcal disease was reported in patients with AIIRD. HZ infection-pooled incidence rate ratio (IRR) was 2.9 (95% CI 2.4 to 3.3) in patients with AIIRD versus general population. Among AIIRD, inflammatory myositis conferred the highest incidence rate (IR) of HZ (pooled IRR 5.1, 95% CI 4.3 to 5.9), followed by systemic lupus erythematosus (SLE) (pooled IRR 4.0, 95% CI 2.3 to 5.7) and rheumatoid arthritis (pooled IRR 2.3, 95% CI 2.1 to 2.6). HPV infection-pooled prevalence ratio was 1.6, 95% CI 0.7 to 3.4 versus general population, based on studies mainly conducted in the SLE population in Latin America and Asia. Pooled prevalence of hepatitis B surface antigen and hepatitis B core antibody in patients with AIIRD was similar to the general population, 3%, 95% CI 1% to 5% and 15%, 95% CI 7% to 26%, respectively.ConclusionCurrent evidence shows an increased risk of VPI in patients with AIIRD, emphasising that prevention of infections is essential in these patients.

Machine learning as a field of artificial intelligence is increasingly applied in medicine to assist patients and physicians. Growing datasets provide a sound basis with which to apply machine learning methods that learn from previous experiences. This review explains the basics of machine learning and its subfields of supervised learning, unsupervised learning, reinforcement learning and deep learning. We provide an overview of current machine learning applications in rheumatology, mainly supervised learning methods for e-diagnosis, disease detection and medical image analysis. In the future, machine learning will be likely to assist rheumatologists in predicting the course of the disease and identifying important disease factors. Even more interestingly, machine learning will probably be able to make treatment propositions and estimate their expected benefit (e.g. by reinforcement learning). Thus, in future, shared decision-making will not only include the patient’s opinion and the rheumatologist’s empirical and evidence-based experience, but it will also be influenced by machine-learned evidence.

During the past 10 yrs, over 700 patients suffering from severe autoimmune disease (AD) have received an autologous haematopoietic stem cell transplant as treatment of their disorder with durable remission being obtained in around one-third. The most commonly transplanted ADs have been systemic sclerosis (scleroderma), multiple sclerosis, rheumatoid arthritis, juvenile idiopathic arthritis and systemic lupus erythematosus. A fewer number of patients have received an allogeneic transplant. The initially reported overall treatment-related mortality of 7% has since fallen, with no further cases being reported in systemic sclerosis or multiple sclerosis in the past 3 yrs. This is thought to be due to more careful patient selection. The phase I/II data has led to currently running prospective randomised trials in systemic sclerosis, multiple sclerosis and systemic lupus erythematosus in Europe and North America. Immune reconstitution data suggests a 'resetting' of autoimmunity in those patients achieving stable remission, rather than simply prolonged immunosuppression. Recent results from in vitro experiments, animal models and early human experience in severe acute graft vs host disease suggest that multipotent mesenchymal stromal cells obtained from the bone marrow and expanded ex vivo, may exert a clinically useful immunomodulatory effect. Such cells are immune privileged and apparently of low toxicity. Further characterization of these cells and consideration of their possible clinical application in AD is underway.