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BackgroundRheumatoid arthritis (RA) and spondyloarthritis, including either Psoriatic Arthritis (PsA) and Ankylosing Spondylitis (AS), are some of the most diagnosed autoimmune rheumatic diseases (AIRDs) in rheumatologists' routine clinical practice [1]. Understanding patients' health and functional status is crucial to provide personalized management strategies to optimize disease control and enhance the quality of life.ObjectivesWe aimed to compare disease burden in patients with RA, PsA or AS by assessing Patient-Reported Outcome Measurement Information System (PROMIS) Physical Health, Global Mental Health, Physical Function and Fatigue 4a together with VAS Pain.MethodsData were obtained in the international COVID vaccination in autoimmune rheumatic diseases study second e-survey (COVAD study). Demographics, AIRD diagnosis, disease activity, PROMIS Global Physical health, PROMIS Global Mental Health, PROMIS Physical Function SF10 and PROMIS Fatigue 4a score were extracted from the COVAD study database. For this study, we only included patients with self-reported RA or spondyloarthritis (either PsA or AS) undergoing active treatment with conventional synthetic disease-modifying drugs (DMARDs) and/or biologic DMARDs, who answered all the survey questions. Active disease was defined as the patient's perception of their disease as active in the four weeks before their first COVID-19 vaccine shot. Analysis of Variance with Bartlett's and Tukey's test was used to compare continuous variables between groups.ResultsFrom January to June 2022, n.1907 patients with RA, female 87.62% (1671/1907), with mean age (±SD) 50.95 ±13.67, n.311 patients with PsA, female 67.20% (209/311), with a mean age of 50.42 ±12.70, and n.336 patients with AS, male 51.31% (209/311), with a mean age of 43.13 ±12.75 years, responded to the COVAD e-survey.In those with active disease, neither physical health, global mental health, physical function, fatigue, nor pain were different among groups (Table 1, Figure 1). Patients with inactive AS had higher mean global physical health scores than RA patients (13.13 ±2.93 VS RA 12.48 ±2.90, p=0.01, Table 1). Those with inactive RA or PsA showed more severe fatigue (PsA 10.58 ±2.22, RA 10.45 ±4.08 VS 9.4 ±4.13, p =0.01 for both). Patients with inactive RA also reported poorer physical function and more residual pain than those with AS (37.79 ±8.86 VS 41.13 ±7.79, p<0.001;3.87 ±2.45 VS 3.34 ±2.39, p=0.01, respectively). Similarly, residual pain was perceived as higher in patients with inactive PsA than those with AS (4.04 ±2.50 VS 3.34 ±2.39, p=0.01)ConclusionDisease burden is roughly comparable in patients with active RA, PsA or AS. Patients with inactive RA and PsA suffer higher disease burden than those with inactive AS.Reference[1]Mease PJ, Liu M, Rebello S, Kang H, Yi E, Park Y, Greenberg JD. Comparative Disease Burden in Patients with Rheumatoid Arthritis, Psoriatic Arthritis, or Axial Spondyloarthritis: Data from Two Corrona Registries. Rheumatol Ther. 2019 Dec;6(4):529-542.Table 1.Patient-Reported Outcome Measures between groups.Inactive diseaseAS (n.185)PsA (n.179)RA (n.1167)MeanSDMeanSDMeanSDPROMIS Global Physical Health13.13*2.9512.433.2712.482.90p=0.01, VS RAPROMIS Global Mental Health13.313.3612.973.3312.843.17PROMIS Fatigue 4a9.44.1310.58*4.2210.45*4.08p=0.01, bothPROMIS Physical Function SF10 Score41.137.3939.279.0137.79*8.86p<0.001, VS ASVAS Pain3.342.394.04*2.503.87*2.45p=0.01, bothActive DiseaseAS (n.35)PsA (n.38)RA (n.189)MeanSDMeanSDMeanSDPROMIS Global Physical Health11.053.1910.102.7611.243.41PROMIS Global Mental Health11.313.2610.843.6311.893.30PROMIS Fatigue 4a12.944.8712.844.4211.754.68PROMIS Physical Function SF10 Score35.829.6233.528.7634.909.80VAS Pain4.682.775.02.544.682.61Figure 1.Violin plots showing kernel densities, quartiles and median for Patient-Reported Outcome Measures for patients with RA, PsA and AS, stratified by disease activity status.[Figure omitted. See PDF]Acknowledgements:NIL.Disclosure of InterestsVincenzo Venerito: None declared, Marc Fornaro: None declared, Florenzo Iannone: None declared, Lorenzo Cavagna: None declared, Masataka Kuwana: None declared, Vishwesh Agarwal: None declared, Naveen Ravichandran: None declared, Jessica Day Grant/research support from: JD has received research funding from CSL Limited., Mrudula Joshi: None declared, Sreoshy Saha: None declared, Syahrul Sazliyana Shaharir: None declared, Wanruchada Katchamart: None declared, Phonpen Akarawatcharangura Goo: None declared, Lisa Traboco: None declared, Yi-Ming Chen: None declared, Parikshit Sen: None declared, James B. Lilleker Speakers bureau: JBL has received speaker honoraria/participated in advisory boards for Sanofi Genzyme, Roche, and Biogen. None is related to this manuscript., Consultant of: JBL has received speaker honoraria/participated in advisory boards for Sanofi Genzyme, Roche, and Biogen. None is related to this manuscript., Arvind Nune: None declared, John Pauling: None declared, Chris Wincup: None declared, Ai Lyn Tan Speakers bureau: ALT has received honoraria for advisory boards and speaking for Abbvie, Gilead, Janssen, Lilly, Novartis, Pfizer, and UCB., Nelly Ziade Speakers bureau: NZ has received speaker fees, advisory board fees, and research grants from Pfizer, Roche, Abbvie, Eli Lilly, NewBridge, Sanofi-Aventis, Boehringer Ingelheim, Janssen, and Pierre Fabre;none are related to this manuscript, Grant/research support from: NZ has received speaker fees, advisory board fees, and research grants from Pfizer, Roche, Abbvie, Eli Lilly, NewBridge, Sanofi-Aventis, Boehringer Ingelheim, Janssen, and Pierre Fabre;none are related to this manuscript, Marcin Milchert: None declared, Abraham Edgar Gracia-Ramos: None declared, Carlo Vinicio Caballero: None declared, COVAD Study: None declared, Vikas Agarwal: None declared, Rohit Aggarwal Speakers bureau: RA has a consultancy relationship with and/or has received research funding from the following companies: Bristol Myers-Squibb, Pfizer, Genentech, Octapharma, CSL Behring, Mallinckrodt, AstraZeneca, Corbus, Kezar, Abbvie, Janssen, Alexion, Argenx, Q32, EMD-Serono, Boehringer Ingelheim, and Roivant., Grant/research support from: RA has a consultancy relationship with and/or has received research funding from the following companies: Bristol Myers-Squibb, Pfizer, Genentech, Octapharma, CSL Behring, Mallinckrodt, AstraZeneca, Corbus, Kezar, Abbvie, Janssen, Alexion, Argenx, Q32, EMD-Serono, Boehringer Ingelheim, and Roivant., Latika Gupta: None declared.
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BackgroundAlthough many studies have been conducted on COVID-19 in recent years, there are still unanswered questions regarding breakthrough infections (BTIs), particularly in patients with systemic lupus erythematosus (SLE).ObjectivesThis study aimed to determine the occurrence of breakthrough COVID-19 infections in patients with SLE versus other autoimmune rheumatic diseases (AIRDs), non-rheumatic autoimmune diseases (nrAIDs), and healthy controls (HCs).MethodsThe study was based on data from the COVAD questionnaire which amassed a total of 10,783 complete responses from patients with SLE, AIRD, or nrAIRD, and HCs. After exclusion of individuals who were unvaccinated, those who received one vaccine dose only, and those with uncertain responses regarding the vaccine doses, a total of 9,595 patients formed the study population of the present investigation. If a COVID-19 infection occurred after the initial two vaccine doses and at least one booster dose (at least three doses in total, herein termed full vaccination), it was considered a BTI. Data were analysed using multivariable regression models. Statistically significant results were denoted by p values <0.05.ResultsA total of 7,016/9,595 (73.1%) individuals were fully vaccinated. Among those, 1,002 (14.2%) reported at least one BTI, and 166 (2.3%) reported at least two BTIs. Among SLE patients, 867/1,218 (71.2%) were fully vaccinated. Among fully vaccinated SLE patients, 137 (15.8%) reported at least one BTI while 28 (3.2%) reported at least two BTIs. BTI frequencies in fully vaccinated SLE patients were comparable to those of other AIRDs (OR: 1.0;95% CI: 0.8–1.3;p=0.447) and nrAIDS (OR: 0.9;95% CI: 0.6–1.3;p=0.856) but higher compared with HCs (OR: 1.2;95% CI: 1.0–1.6;p=0.022).For SLE patients with three vaccine doses, 113/137 (82.5%) reported at least one BTI while the corresponding number for four vaccine doses was 24/137 (17.5%). Compared with HCs (OR: 10.6;95% CI: 1.2–93.0;p=0.032) and other AIRDs (OR: 3.5;95% CI: 1.08–11.5;p=0.036), SLE patients showed higher frequencies of hospitalisation.AID multimorbidity was associated with a 15-fold increased risk for a need of advanced treatment for COVID-19 (OR: 15.3;95% CI: 2.6–88.2;p=0.002).ConclusionCOVID-19 BTIs occurred in nearly 1 every 6th fully vaccinated patient with SLE, and 20% more frequently in this patient population compared with fully vaccinated HCs. Moreover, BTIs in SLE patients were more severe compared with BTIs in HCs or patients with AIRDs other than SLE, resulting in a greater need for hospitalisation. AID multimorbidity contributed to a more severe COVID-19 BTI requiring advanced management. These insights call for greater attention to vaccination in the vulnerable group of SLE patients, with appropriate risk stratification towards optimised vaccination strategies.Figure 1.Survival analysis across patients with SLE, AIRDs, or nrAIDs, and HCs. SLE: systemic lupus erythematosus;AIRD: autoimmune rheumatic disease;nrAID: non-rheumatic autoimmune disease;HC: healthy control.[Figure omitted. See PDF]AcknowledgementsThe authors thank all survey respondents, as well as patient associations and all members of the COVAD study group for their invaluable role in the data collection.Disclosure of InterestsEmelie Kihlgren Olsson: None declared, Naveen Ravichandran: None declared, Elena Nikiphorou Speakers bureau: EN has received speaker honoraria/participated in advisory boards for Celltrion, Pfizer, Sanofi, Gilead, Galapagos, AbbVie, and Lilly., Consultant of: EN has received speaker honoraria/participated in advisory boards for Celltrion, Pfizer, Sanofi, Gilead, Galapagos, AbbVie, and Lilly., Grant/research support from: EN holds research grants from Pfizer and Lilly., Julius Lindblom: None declared, Sreoshy Saha: None declared, Syahrul Sazliyana Shaharir: None declared, Wanruchada Katchamart: None declared, Phonpen Akarawatcharangura Goo: None declared, Lisa Traboco: None declared, Yi-Ming Chen: None declared, Kshitij Jagtap: None declared, James B. Lilleker Speakers bureau:
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Background/Aims Post COVID-19 syndrome (PCS) is an emerging cause of morbidity and poor quality of life in COVID-19 survivors. We aimed to assess the prevalence, risk factors, outcomes, and association with disease flares of PCS in patients with autoimmune rheumatic diseases (AIRDs) and non-rheumatic autoimmune diseases (nrAIDs), both vulnerable groups understudied in the current literature using data from the 2nd COVID-19 Vaccination in Autoimmune Diseases (COVAD) global multicentre patient self-reported e-survey. Methods The survey was circulated from February to July 2022 by the international COVAD Study Group (157 collaborators from 106 countries), and demographics, comorbidities, AIRD/nrAID status, COVID-19 history, vaccination details, and PROMIS physical and mental function were recorded. PCS was defined as symptom resolution time >90 days following acute COVID-19. Predictors of PCS were analysed using regression models for the different groups. Results 7666 total respondents completed the survey. Of these, 2650 respondents with complete responses had positive COVID-19 infection, and 1677 (45.0% AIRDs, 12.5% nrAIDs, 42.5% HCs) completed the survey >90 days post acute COVID-19. Of these, 136 (8.1%) had PCS. Prevalence of PCS was higher in AIRDs (10.8%) than healthy controls HCs (5.3%) (OR: 2.1;95%CI: 1.4-3.1, p=0.002). Across the entire cohort, a higher risk of PCS was seen in women (OR: 2.9;95%CI: 1.1-7.7, p=0.037), patients with long duration of AIRDs/ nrAIDs (OR 1.01;95%CI: 1.0-1.02, p=0.016), those with comorbidities (OR: 2.8;95%CI: 1.4-5.7, p=0.005), and patients requiring oxygen supplementation for severe acute COVID-19 (OR: 3.8;95%CI: 1.1- 13.6, p=0.039). Among patients with AIRDs, comorbidities (OR 2.0;95%CI: 1.08-3.6, p=0.026), and advanced treatment (OR: 1.9;95%CI: 1.08-3.3, p=0.024), or intensive care (OR: 3.8;95%CI: 1.01-14.4, p=0.047) for severe COVID-19 were risk factors for PCS. Notably, patients who developed PCS had poorer PROMIS global physical [15 (12-17) vs 12 (9-15)] and mental health [14 (11-16) vs 11 (8-14)] scores than those without PCS. Conclusion Individuals with AIRDs have a greater risk of PCS than HCs. Associated comorbid conditions, and advanced treatment or intensive care unit admission for severe COVID-19 confer a higher risk of PCS. It is imperative to identify risk factors for PCS for immediate multidisciplinary management in anticipation of poor physical and mental health.
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Background/Aims Flares following COVID-19 vaccination are an emerging concern among patients with rare rheumatic disease like idiopathic inflammatory myositis (IIMs), whereas data and understanding of this is rather limited. We aimed to study the prevalence, characteristics and determinants of IIM flares following COVID-19 vaccination. Methods CoVAD (COVID-19 Vaccination In Autoimmune Diseases) surveys are global patient self-reported e-surveys from 109 countries conducted in 2021 and 2022. Flares of IIM were defined by 4 definitions;a. patient self-reported, b. physician and immunosuppression (IS) denoted, c. sign directed (new erythematous rash, or worsening myositis or arthritis), d. MCID worsening of PROMISPF10a score between the patients who had taken both surveys. Descriptive statistics and multivariate regression were used to describe the predictors of flare. Cox-regression analysis was used to differentiate flares by IIM subtypes. Results Among the 1,278 IIM patients, aged 63 (50-71) years, 276 (21.5%) were dermatomyositis, 237 (18.5%) IBM, 899 (70.3%) were female and most were Caucasian (80.8%). Flares of IIM were seen in 123/1278 (9.6%), 163/1278 (12.7%), 112/1278 (8.7%), and 16/96 (19.6%) by definitions a-d respectively with median time to flare being 71.5 (10.7- 235) days. Muscle weakness (69.1%), and fatigue (56.9%) were the most common symptoms of flare. The predictors of self-reported flare were: inactive/disease in remission prior to first dose of vaccine (OR=4.3, 95%CI=2.4-7.6), and anxiety disorder (OR=2.2, 95%CI=1.1-4.7). Rituximab use (OR=0.3, 95%CI=0.1-0.7) and IBM (OR=0.3, 95%CI=0.1-0.7) were protective. Physician defined flares were seen more often in females, mixed ethnicity, and those with asthma, ILD, and anxiety disorder (OR ranging 1.6-7.0, all p<0.05). Notably, overlap myositis (OM) had higher HR for flare compared to polymyositis (HR=2.3, 95%CI=1.2-4.4, p=0.010). Conclusion Nearly one in ten individuals with IIM develop flares after vaccination, more so among women, those with overlap myositis, and inactive disease prior to vaccination. Formal definition of flares in IIM is needed.
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Background: Patients with comorbidities and active rheumatic disease have increased morbidity and hospitalization following SARS-CoV- 2 infection. While vaccination has decreased this, many unknown factors still influence COVID-19 vaccine hesitancy. The data on predictors of vaccine hesitancy is regional and scarce. We aimed to analyze the factors influencing vaccine hesitancy in 2022 and compare them with those in 2021 through multicentre international e-surveys (The COVID-19 Vaccination in Autoimmune Diseases Studies -COVAD study 1 and 2). Method(s): COVAD 1 and 2 are multi-centre international e-survey with 152 collaborators in 106 countries including patients with idiopathic inflammatory myopathies (IIM), autoimmune rheumatic diseases (AIRDs), other autoimmune diseases (AIDs), and healthy controls (HCs) conducted in March-December 2021 and February-June 2022 (ongoing), respectively. Descriptive and multivariable regression adjusting for age, gender, ethnicity, and stratified by country of residence was performed. Result(s): Among the 18 882 (2021) and 7666 complete responses (2022), and 3109 (16.5%) and 387 (5.1%) did not receive any COVID-19 vaccine, respectively. The prevalence of vaccine hesitancy has decreased [OR 0.26 (0.24-0.3), P < 0.001]. Among the 387 vaccine non-recipients in 2022, numbers were as follows: IIM 69 (17%), AIRDs 179 (46%), other AIDs 80 (20.6%), and HC 59 (15%). The reasons for vaccine hesitancy in 2022 included: doctor advising against it 47 (12%), do not believe in the science behind the vaccine 79 (21%), long-term safety concerns 152 (39%), awaiting more safety data 105 (27%), and not recommended due to recent infection 30 (7%). Compared to AIRDs and HCs, IIM patients were more disbelievers of the science behind the vaccine [OR 1.8 (1.08-3.2), P = 0.023 AIRDs, OR 4 (1.9-8.1), P < 0.001 HC], had more long-term safety concerns [OR 1.9 (1.2-2.9), P = 0.001 AIRDs, OR 5.4 (3-9.6), P < 0.001 HC] and had more doctors recommending against the vaccine [OR 12.9 (2.8-59), P < 0.001 HC]. Vaccine non-recipients had higher pain visual analog score (VAS) (P < 0.001), lower fatigue VAS (P = 0.003), lower PROMIS10a physical health (P < 0.001), and mental health scores (P = 0.015). The factors predicting vaccine hesitancy in regression were lower PROMIS10a global physical health score [OR 0.9 (0.8-0.97), P = 0.014] and Caucasian ethnicity [OR 4.2 (1.7-10.3), P = 0.001]. Compared to 2021, doctor's advising against vaccination [OR 2.5 (1.8-3.6), P < 0.001] and long-term safety concerns [OR 3.6 (2.9-4.6), P < 0.001] were more frequent causes of vaccine hesitancy overall whereas vaccine non-availability [OR 0.05 (0.02-0.11), P < 0.001] and have scheduled the vaccination but not received [OR 0.1 (0.06-0.3), P < 0.001] were less frequent causes in 2022. Conclusion(s): Overall, the prevalence of COVID-19 vaccine hesitancy has decreased. Long-term safety concerns and the need for more safety data are now the major reasons for vaccine hesitancy. Caucasian ethnicity and lower physical health scores are predictors of vaccine hesitancy. The increase in physicians recommending against vaccination calls for more physician awareness to mitigate vaccine hesitancy.
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Responding quickly to unknown pathogens is crucial to stop uncontrolled spread of diseases that lead to epidemics, such as the novel coronavirus, and to keep protective measures at a level that causes as little social and economic harm as possible. This can be achieved through computational approaches that significantly speed up drug discovery. A powerful approach is to restrict the search to existing drugs through drug repurposing, which can vastly accelerate the usually long approval process. In this Review, we examine a representative set of currently used computational approaches to identify repurposable drugs for COVID-19, as well as their underlying data resources. Furthermore, we compare drug candidates predicted by computational methods to drugs being assessed by clinical trials. Finally, we discuss lessons learned from the reviewed research efforts, including how to successfully connect computational approaches with experimental studies, and propose a unified drug repurposing strategy for better preparedness in the case of future outbreaks.
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Background: Giant Cell Arteritis (GCA) is a systemic vasculitis involving large and medium-sized blood vessels. Treatment is with high dose glucocorticoids. Steroid-sparing agents and Tocilizumab (TCZ) are used for refractory or relapsing cases. NHS England requires all GCA patients to be discussed in a regional multidisciplinary team meeting (MDT) prior to commencing TCZ. TCZ has only been permitted for a maximum of one year;this time limitation was extended during the Covid-19 pandemic (1). The monthly virtual Bristol and Bath regional MDT started in November 2018. Objectives: We aimed to review: 1) Baseline data on all patients referred to the Bristol and Bath TCZ for GCA MDT, including demographics, clinical presentation and previous steroid-sparing agents used and 2) 12 month follow up data including number of completions, adverse effects, and fares on treatment. Methods: The TCZ MDT referral proforma, adapted from the NHS England Blueteq approval form, was reviewed for all patients referred. 12 month follow up data was obtained from clinic letters. Results: Baseline data Thirty-eight cases were referred between November 2018 and September 2021. Of these, 31 were approved for TCZ usage;100% fulflled the criteria for either refractory (n=11) or relapsing (n=20) disease. Mean age was 74 years and 74.2% were female. Average disease duration was 161.5 days for the refractory and 827.3 days for the relapsing group. 77.4% had cranial GCA, 48.4% had large vessel involvement, 45.2% had visual symptoms and 25.8% had ischaemic visual loss. The positive investigations were PET-CT (48.4%), temporal artery ultrasound (41.9%) and temporal artery biopsy (32.3%). 64.5% had trialled a steroid-sparing agent at time of referral (61.3 % metho-trexate, 9.7% azathioprine, 6.5% lefunomide), 35.5% had received intravenous methylprednisolone and 58% were receiving greater than 40mg prednisolone at the time of referral. Glucocorticoid adverse effects of osteoporosis, weight gain, cataracts and hypertension were each seen in 19.4%;whilst diabetes, neuropsychiatric symptoms and sleep disturbance were each reported in 16.1%. Those with ocular involvement tended to be referred earlier than those without (478.2 days vs 648.1 days), were referred on higher doses of glucocorticoids (71.4% vs 47.1% on ≥ 40mg) and had less steroid-sparing agents prior to referral. Follow up data In December 2021, a follow-up audit revealed 14/31 patients had completed at least 12 months of tocilizumab;5 of these had had an extension under Covid-19 exceptional guidance (mean duration of 5.2 months). Of the remaining 17: 3 patients had stopped early (1 death, 1 moved away, 1 due to adverse effects of headache and gastro-intestinal side effects), 4 had not started tocilizumab and 10 had not completed 12 months of treatment at that point. Adverse events in the 14 patients at 12 months included: liver abnormalities (2/14;14.3%), neutropenia (2/14;14.3%), thrombocytopaenia (1/14;7.1%), soft tissue infections (3/14;21.4%), urinary tract infection (1/14;7.1%) and lipid derangement (4/14 28.6%). One case of GCA relapse occurred on TCZ (mild headache and raised infammatory markers settled on small increase in prednisolone). After 12 months, mean prednisolone dose was 3mg (range 0-15mg). Conclusion: All patients approved for Tocilizumab in the GCA MDT fulflled NHS England criteria for either relapsing or refractory disease. The majority of cases had cranial disease, but almost half had either ocular or large vessel involvement, refecting a severe spectrum of disease. Cases showed a high burden of glucocorticoid toxicity. Follow up data suggests that TCZ was effective in allowing glucocorticoid weaning and disease control, but with some adverse effects. Future work to follow up patients after stopping Tocilizumab would be informative, as the twelve month limitation on treatment is likely to be re-instated.
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Background: A highly controversial question is whether or not corticosteroids should be prescribed for patients with early diffuse cutaneous systemic sclerosis (dcSSc). Although the painful and disabling features of early dcSSc (including tight itchy skin, contractures, fatigue) have an infammatory basis and are likely to respond to corticosteroids, corticosteroids are a risk factor for potentially life-threatening scleroderma renal crisis. Objectives: Our aim was to examine safety and efficacy of moderate dose prednisolone in patients with early dcSSc. Specific objectives were to evaluate whether moderate dose prednisolone reduced pain and disability, and improved skin score, and whether prednisolone was safe with particular reference to renal function Methods: PRedSS set out as a Phase II, multicentre, double-blind randomised controlled trial, converted to open-label because of the Covid-19 pandemic. Patients were randomised to receive either moderate dose prednisolone (approximately 0.3 mg/kg) or matching placebo (or no treatment during open-label) for 6 months. The co-primary endpoints were the Health Assessment Questionnaire Disability Index (HAQ-DI) and modifed Rodnan skin core (mRSS) at 3 months. Over 20 secondary endpoints included patient reported outcome measures refecting pain, itch, anxiety and depression, fatigue and helplessness. 72 participants randomised 1:1 were planned and anticipated to yield 60 evaluable, giving over 80% power for each co-primary outcome in ANCOVA analyses [assumptions;HAQ-DI (a = 0.025, ô =-0.6, o = 0.9, p = 0.6), mRSS (a = 0.025, ô =-5.5, a = 8.2, p = 0.6)]. Mixed Models for Repeated Measures (week 6, month 3, month 6) were ftted with covariates trial arm, baseline score, anti-Scl-70 and their interactions with time point. An unstructured covariance matrix was assumed with the primary focus being the trial arm effect at 3 months. Results: The study terminated early due to the Covid-19 pandemic and consequently did not meet the recruitment target of 72 patients. Thirty-five patients (Table 1) were randomised (17 to prednisolone and 18 to placebo/control, 25 during the double-blind phase), of whom 34 completed the 3 month assessment. The adjusted mean difference between treatment groups at 3 months in HAQ-DI score was-0.10 (97.5% CI-0.29 to 0.10), p=0.25, and in mRSS-3.90 (97.5% CI-8.83 to 1.03), p=0.070, both favouring prednisolone but not signifcantly. Patients in the prednisolone group experienced less pain, helplessness and anxiety than control patients at 3 months: mean difference in pain scores-0.49, 95%CI (-0.93 to-0.06), p=0.027, in Hospital Anxiety and Depression (HADS) anxiety scores-2.05, 95%CI (-3.73 to-0.37), p=0.018, and in helplessness scores-1.54, 95%CI (-3.01 to-0.07), p=0.040. There were no renal crises. Conclusion: PRedSS exemplifed the challenges of running a clinical trial of an investigational medicinal product potentially associated with increased infection risk during the Covid-19 pandemic. Because PRedSS was terminated prior to target recruitment, it was underpowered, and any conclusions have to be extremely cautious. Although PRedSS suggested some beneft from moderate dose predni-solone, the small sample indicates the need for a further randomised trial.
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Background: Immediately following the first wave of the COVID-19 pandemic, the number of giant cell arteritis (GCA) diagnoses noticeably increased at the Royal National Hospital for Rheumatic Diseases in Bath, UK. Furthermore, there was an increase in the proportion of patients with visual complications [1]. The finding supports the viral hypothesis of GCA aetiopathogenesis as previously described [2]. This not only has ramifications for understanding the underlying disease mechanisms in GCA but also has implications for the provision of local GCA services which may have already be affected by the pandemic. Objectives: The objective of the study was to estimate the incidence of giant cell arteritis during the COVID-19 pandemic years of 2020 -2021 and compare it to 2019 data. Given that there have now been two distinct peaks of COVID-19 as reflected by hospital admissions of COVID-19-positive patients this has allowed us to investigate if there is a temporal relationship between the prevalence of COVID-19 and the incidence of GCA. Methods: The incidence of GCA was calculated by assessing emailed referrals to the GCA service and the hospital electronic medical records to identity positive cases from 2019 to the current date. Local COVID-19 prevalence was estimated by measuring the number of hospital beds taken up by COVID-19 positive patients, available publicly in a UK Government COVID-19 dataset [3]. Results: There were 61 (95% Poisson distribution confidence interval [CI] 47 -78) probable or definite GCA diagnoses made in 2020 compared to 28 (CI 19 -40) in 2019 (Figure 1). This is an excess of 33 cases in 2020, or an increase in 118%. Given that 41% of the hospital's catchment population is over 50, this equates to an annual incidence rate of 13.7 per 100,000 in 2019 and 29.8 per 100,000 in 2020. This compares to a previously estimated regional incidence rate of 21.6 per 100,000 for the South West of the UK [4]. A peak in COVID-19-positive inpatients was seen on 10th April 2020 with a corresponding peak of GCA diagnoses on 29th May 2020, giving a lag period of approximately 6 weeks between these peaks (Figure 1). Conclusion: The incidence of GCA in Bath was significantly increased in 2020 compared to 2019. This may be the result of the widespread infection of the local population with the COVID-19 virus as a precipitating factor. Possible mechanisms include, but are not limited to, endothelial disruption by the virus, immune system priming towards T helper cell type 1 (Th1) cellular immunity and/or activation of the monocyte-macrophage system. More work is currently underway to assess the causal relationship between the two diseases. There was a lag period of 6 weeks between the peak during the first wave of the pandemic and the rise in GCA cases. We shall be closely monitoring the number of referrals that follow the current wave of the pandemic.