ABSTRACT
BackgroundPsoriasis (PsO) and psoriatic arthritis (PsA) can greatly impact quality of life and result in substantial personal and societal costs. Complete and up to date data on the prevalence and incidence of these conditions and whether these change over time and vary by age is important for healthcare service planning so that specialist care and funding can be appropriately allocated.ObjectivesTo determine the prevalence and incidence of PsO and PsA in males and females from 2009-2019 across all age groups in England.MethodsWe used Clinical Practice Research Datalink AURUM, a primary care electronic health record database, including 20% of the English population. The codes used to identify patients with PsO and PsA were selected by rheumatologists and dermatologists and cross-checked with published code lists from other studies to ensure inclusion of all relevant codes. All included patients must have data for at least 1 year before their diagnosis. The annual incidence and point prevalence were calculated from 2009-2019 and stratified by age/sex. The study period ended in 2019 to avoid COVID-19 pandemic affecting results.ResultsThe prevalence of PsO and PsA in males and females increased annually, peaking in 2019 (PsO males 2.41% [95% confidence interval (CI) 2.40, 2.42];PsO females 2.60% [95% CI 2.59-2.61];PsA males 0.20% [95% CI 0.20-0.20];PsA females 0.21% [95% CI 0.21- 0.22]), as illustrated in Table 1. In 2019, the prevalence of PsO and PsA was highest in the over 65 years age group;PsO 4.25% [95% CI 4.22-4.28] and PsA 0.38% [95% CI 0.37-0.38]. The annual incidence (per 100,000 person years) of PsO has gradually decreased in males (from 168 (164-171) in 2009 to 148 (145-151) in 2019) but in females it has been stable with a slight annual decrease (from 180 (177-184) in 2009 to 173 (170-176) in 2019). The annual incidence for PsA has increased in both males and females (13 (12-14) in 2009 and 15 (14-16) in 2019 for males and 12 (11-13) in 2009 and 18 (17-19) in 2019 for females).ConclusionThe increasing prevalence of PsO and PsA highlights the importance of organising healthcare services to meet this need, particularly in the elderly population.ReferencesNIL.Table 1.Prevalence of PsO and PsA from 2009-2019 in EnglandYear20092010201120122013201420152016201720182019Population (n)1073383110910802110318501118036711343299112249341137842211657996119336261223432512420998PsO (n)216841229106239819250667259988268032276804286499295712304568311104PsO prevalence (%, 95%CI)-Male1.98 (1.96-1.99)2.06 (2.05- 2.07)2.13 (2.12-2.14)2.19 (2.18-2.20)2.24 (2.23- 2.25)2.33 (2.32- 2.34)2.37 (2.36- 2.38)2.39 (2.38- 2.40)2.40 (2.39- 2.41)2.40 (2.39- 2.42)2.41 (2.40- 2.42)-Female2.07 (2.05- 2.08)2.14 (2.13- 2.16)2.22 (2.21- 2.23)2.29 (2.28- 2.31)2.35 (2.33- 2.36)2.45 (2.43- 2.46)2.50 (2.49- 2.51)2.53 (2.52- 2.54)2.56 (2.54- 2.57)2.58 (2.56- 2.59)2.60 (2.59- 2.61)PsO incidence (100,000 person years)-Male168 (164-171)158 (155- 162)161 (158-165)153 (150-157)161 (157- 164)156 (153- 159)155 (152- 159)154 (151- 157)153 (150-156)150 (147-153)148 (145-151)-Female180 (177-184)176 (172-179)181 (177-184)171 (167-174)175 (171-178)176 (172-180)179 (176-183)178 (174-181)177 (174-181)174 (170-177)173 (170-176)PsA (n)1444515443164681752218545196182072021994232572451425683PsA prevalence (%, 95%CI)-Male0.14 (0.14- 0.14)0.15 (0.14- 0.15)0.15 (0.15- 0.16)0.16 (0.16- 0.16)0.17 (0.16- 0.17)0.18 (0.17- 0.18)0.18 (0.18- 0.19)0.19 (0.18- 0.19)0.19 (0.19- 0.20)0.20 (0.19- 0.20)0.20 (0.20- 0.20)-Female0.13 (0.13- 0.13)0.14 (0.13- 0.14)0.15 (0.14- 0.15)0.15 (0.15- 0.16)0.16 (0.16- 0.16)0.17 (0.17- 0.18)0.18 (0.18- 0.18)0.19 (0.19- 0.19)0.20 (0.19- 0.20)0.20 (0.20- 0.21)0.21 (0.21- 0.22)PsA incidence (100,000 person years)-Male13 (12- 14)12 (11- 13)13 (12- 14)12 (11- 13)13 (12-14)14 (13- 15)14 (13- 15)14 (13-15)1514-16)14(13- 15)15 (14-16)-Female12 (11- 13)13 (12- 14)13 (12- 14)14 (13-15)14 (13-15)15 (14-16)17 (16- 18)16 (15- 17)17 (16- 18)18 (17-19)18 (17-19)Acknowledgements:NIL.Disclosure of InterestsArani Vivekanantham: None declared, Edward Burn: None dec ared, Marta Pineda-Moncusí: None declared, Sara Khalid Grant/research support from: SK has received research grant funding from the UKRI and Alan Turing Institute outside this work. SK's research group has received grant support from Amgen and UCB Biopharma., Daniel Prieto-Alhambra Grant/research support from: DPA's department has received grant/s from Amgen, Chiesi-Taylor, Lilly, Janssen, Novartis, and UCB Biopharma. His research group has received consultancy fees from Astra Zeneca and UCB Biopharma. Amgen, Astellas, Janssen, Synapse Management Partners and UCB Biopharma have funded or supported training programmes organised by DPA's department., Laura Coates Speakers bureau: LC has been paid as a speaker for AbbVie, Amgen, Biogen, Celgene, Eli Lilly, Galapagos, Gilead, Janssen, Medac, Novartis, Pfizer and UCB., Consultant of: LC has worked as a paid consultant for AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Eli Lilly, Gilead, Galapagos, Janssen, Novartis, Pfizer and UCB., Grant/research support from: LC has received grants/research support from AbbVie, Amgen, Celgene, Eli Lilly, Novartis and Pfizer.
ABSTRACT
Background: Characterization studies of COVID-19 patients with chronic obstructive pulmonary disease (COPD) are limited in size and scope. The aim of the study is to provide a large-scale characterization of COVID-19 patients with COPD. Methods: We included thirteen databases contributing data from January-June 2020 from North America (US), Europe and Asia. We defined two cohorts of patients with COVID-19 namely a ‘diagnosed' and ‘hospitalized' cohort. We followed patients from COVID-19 index date to 30 days or death. We performed descriptive analysis and reported the frequency of characteristics and outcomes among COPD patients with COVID-19. Results: The study included 934,778 patients in the diagnosed COVID-19 cohort and 177,201 in the hospitalized COVID-19 cohort. Observed COPD prevalence in the diagnosed cohort ranged from 3.8% (95%CI 3.5-4.1%) in French data to 22.7% (95%CI 22.4-23.0) in US data, and from 1.9% (95%CI 1.6-2.2) in South Korean to 44.0% (95%CI 43.1-45.0) in US data, in the hospitalized cohorts. COPD patients in the hospitalized cohort had greater comorbidity than those in the diagnosed cohort, including hypertension, heart disease, diabetes and obesity. Mortality was higher in COPD patients in the hospitalized cohort and ranged from 7.6% (95%CI 6.9-8.4) to 32.2% (95%CI 28.0-36.7) across databases. ARDS, acute renal failure, cardiac arrhythmia and sepsis were the most common outcomes among hospitalized COPD patients. Conclusion: COPD patients with COVID-19 have high levels of COVID-19-associated comorbidities and poor COVID-19 outcomes. Further research is required to identify patients with COPD at high risk of worse outcomes. Copyright: © 2023 Moreno-Martos D et al.
ABSTRACT
This document reports the numbers of prostheses recorded and reported to the NJR between 1 January and 31 December 2020. The tables show volumes of components as they have been entered into the registry, regardless of construct. The procedure counts in this document are presented without adjustment and may vary from counts found in the corresponding main NJR Annual Report analysis. If a procedure has been submitted with missing implant information this will also cause numbers to differ. Procedure counts below four have been suppressed. Components are listed and described according to the current classifications used in the registry. It must be noted that due to COVID-19, the ratio of revision to primary procedures increased in 2020 and this may affect the relative changes in the types and brands of implants used in comparison to previous years. As this document was not published for 2019 Annual Report data, comparison has been made with the 2018 Annual Report data.
ABSTRACT
Background/Aims Infections on conventional synthetic disease modifying anti-rheumatic drugs (csDMARDs) are an important concern for rheumatoid arthritis (RA) patients, especially during the COVID-19 pandemic. However comparative safety data between csDMARDs have been conflicting and limited in power. The objective was to assess the comparative safety of serious, opportunistic and all infections (including nonserious) of first-line csDMARDs in RA through a large multinational observational study. Methods We evaluated first-line new users of methotrexate (MTX), hydroxychloroquine (HCQ), sulfasalazine (SZ) and leflunomide (LEF) monotherapy. Data was obtained from four US databases (IQVIA US Ambulatory EMR (AMBER), Optum® De-identified Clinformatics® Datamart (Optum), IBM MarketScan® Medicare Supplemental Database (MDCR), and IBM MarketScan Commercial Database (CCAE)), one from Germany (IQVIA Disease Analyser Germany EMR (Germany)), and another from the UK (IQVIA UK The Health Improvement Network). Patients included were ≥18 years with a RA diagnosis between 2005-2019, without prior inflammatory arthritis, cancer or infection (in the preceding 30 days). Serious infections were defined as those requiring hospitalisation or resulting in death within 30 days;opportunistic infections were defined as per published EULAR consensus. Patients were followed from 1-day following treatment initiation to the earliest of treatment discontinuation, switching, or addon plus 14 days, or loss to follow-up. Cox proportional-hazards models for MTX against each csDMARD with large-scale propensity score stratification were performed. A large set of negative control outcomes were used to calibrate hazard ratios (cHR) to account for potential residual confounding. Estimates were pooled where homogeneity across sources was adequate (I2<0.4). Results A total of 247,511 patients were included (MTX: 141,647;HCQ: 73,286, SSZ: 16,521, LEF: 16,057), with pooled incidence rates of serious, opportunistic and all infections across sources for MTX users of 33.7, 20.1 and 311.8 per 1,000 pyrs, respectively. With MTX as the referent, for all infections, the pooled cHR (with 95% Confidence Intervals) for SSZ was 0.73 (0.62, 0.86);HCQ, 0.96 (0.89, 1.04);and LEF, 0.74 (0.50, 1.08). The serious infection pooled cHR for SSZ was 0.75 (0.58, 0.97) and for LEF, 0.93 (0.61, 1.40). For opportunistic infections, pooled cHR for HCQ was 1.04 (0.92, 1.19). Conclusion SSZ, LEF and less consistently HCQ had a lower risk of all (including non-serious) infections, compared to MTX. SSZ and LEF were associated with a 25% reduction in the expected risk of all infections. SSZ was associated with a 25% lower risk of serious infections relative to MTX. In the first large scale observational network study assessing comparative risk of infection with csDMARDs there were differences between drugs in risk for all infections, with potential implications for clinical care.