Search

Abstract Background Antibiotic-induced disturbances of the human microbiota have been implicated in the development of chronic autoimmune conditions. This study aimed to assess whether antibiotic use is associated with the onset of rheumatoid arthritis (RA). Methods A nested case-control study was conducted utilising data from the primary care Clinical Practice Research Datalink (CPRD). Patients with an incident diagnosis of RA were identified (1995–2017). Each case was matched on age, gender, and general practice to ≥ 5 controls without RA. Conditional logistic regression was used to examine previous antibiotic prescriptions and RA onset after controlling for confounding factors. Results We identified 22,677 cases of RA, matched to 90,013 controls, with a median follow-up of 10 years before RA diagnosis. The odds of developing RA were 60% higher in those exposed to antibiotics than in those not exposed (OR 1.60; 95% CI 1.51–1.68). A dose- or frequency-dependent association was observed between the number of previous antibiotic prescriptions and RA. All classes of antibiotics were associated with higher odds of RA, with bactericidal antibiotics carrying higher risk than bacteriostatic (45% vs. 31%). Those with antibiotic-treated upper respiratory tract (URT) infections were more likely to be RA cases. However, this was not observed for URT infections not treated with antibiotics. Antifungal (OR = 1.27; 95% CI 1.20–1.35) and antiviral (OR = 1.19; 95% CI 1.14–1.24) prescriptions were also associated with increased odds of RA. Conclusion Antibiotic prescriptions are associated with a higher risk of RA. This may be due to microbiota disturbances or underlying infections driving risk. Further research is needed to explore these mechanisms.

Abstract Background Glucocorticoids are associated with increased fracture risk and are the mainstay of treatment in polymyalgia rheumatica (PMR) and giant cell arteritis (GCA). However, fracture risk in these conditions has not been previously quantified. The aim of this study was to quantify the risk of fracture among patients with PMR and GCA. Methods A retrospective cohort study was conducted using primary care records from the UK-based Clinical Practice Research Datalink. Individuals aged 40 years and over, with incident diagnoses of PMR or GCA were separately identified from 1990–2004 and followed up until 2015. For each exposed individual, four age-, sex- and practice-matched controls were randomly selected. Incidence rates of fracture per 10,000 person-years were calculated for each disease group and hazard rates were compared to the unexposed using Cox regression models. Results Overall, 12,136 and 2673 cases of PMR and GCA, respectively, were identified. The incidence rate of fracture was 148.05 (95% CI 141.16–155.28) in PMR and 147.15 (132.91–162.91) in GCA per 10,000 person-years. Risk of fracture was increased by 63% in PMR (adjusted hazard ratio 1.63, 95% CI 1.54–1.73) and 67% in GCA (1.67, 1.49–1.88) compared to the control populations. Fewer than 13% of glucocorticoid-treated cases were prescribed bisphosphonates. Conclusions This study reports, for the first time, a similar increase in fracture risk for patients with PMR and GCA. More needs to be done to improve adherence to guidelines to co-prescribe bisphosphonates. Further research needs to identify whether lower glucocorticoid starting doses and/or aggressive dose reduction reduces fracture risk.

Abstract Background Giant cell arteritis (GCA), if untreated, can lead to blindness and stroke. The study’s objectives were to (1) determine a new evidence-based benchmark of the extent of diagnostic delay for GCA and (2) examine the role of GCA-specific characteristics on diagnostic delay. Methods Medical literature databases were searched from inception to November 2015. Articles were included if reporting a time-period of diagnostic delay between onset of GCA symptoms and diagnosis. Two reviewers assessed the quality of the final articles and extracted data from these. Random-effects meta-analysis was used to pool the mean time-period (95% confidence interval (CI)) between GCA symptom onset and diagnosis, and the delay observed for GCA-specific characteristics. Heterogeneity was assessed by I 2 and by 95% prediction interval (PI). Results Of 4128 articles initially identified, 16 provided data for meta-analysis. Mean diagnostic delay was 9.0 weeks (95% CI, 6.5 to 11.4) between symptom onset and GCA diagnosis (I 2 = 96.0%; P