BackgroundPreviously a study in the QUEST-RA database, based on rheumatoid arthritis (RA) patients included between January 2005 and June 2006, has shown that the ratio between biological disease modifying antirheumatic drug (bDMARD) use and glucocorticoid (GC) use strongly differs between countries. Considering the difference in affordability between bDMARDs and GCs, it may be hypothesized, that when less bMDARDs are used, glucocorticoid use increases.ObjectivesTo investigate globally, in more recent data, the ratio between bDMARD and GC use, and to assess whether this relates to a country’s socioeconomic status (SES).MethodsData on bDMARD and GC use between 1-1-2007 and 28-12-2020 were extracted from the METEOR registry: an international database capturing daily clinical practice data from patients with a clinical diagnosis of RA. The ratio between the proportion of patients who had ever used a bDMARD and the proportion of patients who had ever used a GC, with no concomitant bDMARD use, during a total follow up duration of two years (bDMARD/GC ratio) was calculated per country. Univariable linear regression was used to analyze the bDMARD/GC ratios according to publicly available country-level indicators of SES (Worldbank, OECD).ResultsData from 10,856 patients covering eight countries showed varying proportions of bDMARD use. The number of patients included ranged from 64 (Spain) to 8484 (India). Baseline characteristics varied per country (Table 1) The percentage of patients who used a bDMARD (with or without a GC) during two years follow up ranged from 1% (South Africa, India) to 26% (United States, state of Massachusetts) and for those who used a GC at some time during two years follow up ranged from 19% (Great Britain) to 94% (South Africa). Higher country-level wealth measured in GDP per capita, health expenditure and household net adjusted disposable income were related to a higher bDMARD/GC ratio. For every 10,000 IntI$ increase in GDP per capita, household net adjusted disposable income and health expenditure per capita, the bDMARD/GC ratio (range 0 to 1) was observed to increase by a value of β 0.1 (Figure 1A, 95% CI 0.05;0.1, p<0.05), β 0.2 (Figure 1B, 95% CI 0.08;0.3, p<0.05) and β 0.6 (Figure 1C, 95% CI 0.4;0.8, p<0.05), respectively.ConclusionIn this analysis based on a worldwide cohort capturing 8 countries, we show that the bDMARD/GC ratio differs across countries. These differences are significantly related to general country-level indicators of level of wealth, where greater wealth went with a higher proportion of patients using bDMARDs and/or a smaller proportion of patients using GCs.Table 1.Baseline characteristics and proportions of bDMARD and GC use per countryUSNLPortugalSouth AfricaSpainUKIndiaMexicoN Included patients215369334754644668484170Female, %7468738286648584Rheumatoid factor +, %4449619383668248ACPA +, %3946517581625128BMI, median (IQR)29 (25;33)25 (22;28)27 (23;29)28 (24;33)25 (22;7.2)27 (24;32)25 (22;29)28 (24;31)Current or ever smoker,%472724243655214Age at diagnosis, mean (SD)53 (15)57 (16)55 (15)50 (13)52 (15)58 (15)46 (12)48 (14)Symptom duration at baseline (years), mean (SD)2.0 (3.8)1.3 (3.5)1.7(3.1)3.6 (4.6)0.7 (0.8)1.1 (2.3)5.5 (6.1)1.4 (3.3)DAS28, mean (Sd)5.1(1.4)4.5 (1.5)5.1(1.5)5.5 (1.4)4.8 (1.5)5.1 (1.3)6.3 (1.3)5.1(1.6)GC use only,% Within 1 year4930719375196077 2 years4729709470196477bDMARD and GC use, % Within 1 year123315001 2 years144616002bDMARD use only, % Within 1 year96205111 2 years1911409211REFERENCES:NIL.Acknowledgements:NIL.Disclosure of InterestsIsabell Nevins: None declared, Cornelia Allaart: None declared, David Vega-Morales: None declared, Lai-Ling Winchow: None declared, Arvind Chopra: None declared, Ana Maria Rodrigues: None declared, Thomas Huizinga: None declared, Maarten Boers: None declared, Sytske Anne Bergstra Grant/research support from: Received APIRE grant from Pfizer.

BackgroundThe development of biologic and targeted synthetic (b/ts)DMARDs contributed to improved treatment outcomes in rheumatoid arthritis (RA). However, high medications costs may limit their use. Previously we showed that in countries with a lower socioeconomic status (SES), b/tsDMARDs were prescribed to fewer patients than in countries with higher SES. In this study we take a more detailed look at b/tsDMARD prescription behavior between countries.ObjectivesTo explore cross-country relationships between Gross Domestic Product (GDP) per capita, specific indicators of b/tsDMARDs use and disease outcomes in patients with RA.MethodsThis multinational, observational study included countries that had contributed ≥100 patients using b/tsDMARDs, with available follow up, to one of 2 registries: METEOR, an international registry capturing daily clinical practice data of patients with a clinical diagnosis of RA, and JAK-POT, an investigator-initiated collaboration between national registries aiming to evaluate clinical aspects of b/tsDMARDs in RA. On a per-country basis, mean DAS28 was calculated from the last available follow-up visit per patient. b/tsDMARD usage was determined as mean time to start b/tsDMARD therapy since date of diagnosis, mean number of b/tsDMARDs tried per patient and mean duration of b/tsDMARD therapy. To calculate the time to start a first b/tsDMARD per country included from the JAK-POT registry, only bionaïve patients were included. Possible associations between GDP per capita and country-level indicators of b/tsDMARD use and DAS28 were tested in univariable linear regression models. Regression coefficients (β) are interpreted as the numerical increase in the outcome per 1 point increase in the predictor.ResultsData from 25,832 patients living in 17 different countries showed varying b/tsDMARD prescription behavior. GDP per capita ranged from 6505 (India) to 93350 Intl$ (Ireland). Time to start b/tsDMARD therapy ranged from 0.5 (Austria) to 11.1 (Finland) years. Mean number of b/tsDMARDs tried per patient ranged from 1.0 (Turkey) to 2.4 (Switzerland). Duration of b/tsDMARD therapy ranged from 0.9 (India) to 5.5 (Portugal) years (Figure 1). Baseline DAS28 ranged between 3.7 and 6.1, but was not related to any of the indicators of b/tsDMARD use: time to start a b/tsDMARD β 0.08 (95% CI -0.7; 0.9), number of prescribed b/tsDMARDs β 0.06 (95% CI -0.03; 0.2), duration of b/tsDMARD treatment β 0.1 (95% CI -0.3; 0.5). No statistically significant associations were observed between GDP per capita and time to start b/tsDMARD therapy (Figure 1A, β 0.09 CI 95% -0.7; 0.9), the number of b/tsDMARDs tried per patient (fig 1B, β 0.07 CI 95% -0.02; 0.2) or the duration of b/tsDMARD treatment (fig 1C, β 0.1 CI 95% -0.3; 0.5). None of the indicators of b/tsDMARD prescription were significantly related to DAS28 at the end of follow up: time to start a b/tsDMARD β 0.02 (95% CI -0.05; 0.1), duration of b/tsDMARD therapy β -0.03 (95% CI -0.2; 0.1) and number of b/tsDMARDs β -0.03 (95% CI -0.6; 0.6).ConclusionThis study showed varying b/tsDMARD prescription behavior and disease activity across 17 countries worldwide. Overall, differences in b/tsDMARD prescription behaviour did not appear to be related to socioeconomic welfare and, no significant association was observed between b/tsDMARD prescription behavior and disease activity at a country level. This seems to indicate that once patients start a b/tsDMARD, socioeconomic welfare has less impact on b/tsDMARD use.REFERENCES:NIL.Acknowledgements:NIL.Disclosure of InterestsIsabell Nevins: None declared, Delphine Courvoisier: None declared, Axel Finckh Speakers bureau: AbbVie, BMS, Pfizer, Eli-Lilly, Sandroz, Consultant of: AbbVie, Novartis, Pfizer, MSD, Lilly, Grant/research support from: AbbVie, BMS, Galapagos, Lilly, Pfizer, Ruth Fritsch-Stork: None declared, Dan Nordström: None declared, Ana Maria Rodrigues: None declared, ȘTEFAN CRISTIAN DINESCU: None declared, Álvaro García Martos: None declared, Mert Oztas: None declared, Ziga Rotar: None declared, Karen Solomon-Escoto: None declared, Arvind Chopra: None declared, David Vega-Morales: None declared, Petronella DM de Buck: None declared, Denis Choquette: None declared, Richard Conway Speakers bureau: Janssen, Roche, Sanofi, AbbVie, Galapagos, Fresenius Kabi, Viatris, Grant/research support from: Janssen, Celltrion, Nordic Pharma, Abbvie, Florenzo Iannone: None declared, Cornelia Allaart: None declared, Thomas Huizinga: None declared, Kim Lauper: None declared, Sytske Anne Bergstra Grant/research support from: ASPIRE grant from Pfizer.

BackgroundGlucocorticoids (GC) are widely used for the initial treatment of rheumatoid arthritis (RA), to induce rapid suppression of inflammation and clinical symptoms and thereby limit radiographic damage progression. There are concerns that GC use in the long term is associated with a dose and duration dependent risk of serious side effects. Therefore, international guidelines have recommended to start GC when initiating a csDMARD, but to discontinue GC as rapidly as clinically feasible, preferably within 3 months (bridging therapy). In contrast, due to the concerns of GC side effects, the ACR guidelines published in 2021 conditionally recommend to start csDMARD monotherapy without GC bridging therapy.ObjectivesWe aim to evaluate the success rate of GC discontinuation after using temporary GC as part of initial therapy (‘bridging’) both in observational cohorts and clinical trials in newly diagnosed RA patients.MethodsSystematic literature searches were conducted to identify observational cohorts (scoping search) and clinical trials (in-depth search) that included RA patients who were treated with initial GC bridging therapy. GC bridging was defined as oral or intramuscular GC treatment that was discontinued within one year, alongside conventional DMARD therapy. Patient percentages still or again using GC were considered to represent the reverse of successful discontinuation. Random-effects meta-analyses were performed stratified by time point.ResultsThe literature search on observational cohort studies could not identify any study answering the research question, since it remained unclear which patients had received GC as part of the initial treatment. The literature search for clinical trials identified 7160 abstracts, resulting in 10 included studies, with varying type and dose of GC and varying tapering schedules (Table 1). Of these included studies, 4 reported sufficient data on GC discontinuation or GC use after the bridging phase. The pooled proportion of patients who were still using GC was 22% (95% Confidence Interval (CI) 8; 37, based on 4 trials) at 12 months and 10% at 24 months (95% CI -1; 22, based on 2 trials) (Figure 1). Thus, the vast majority had stopped GC. Heterogeneity was substantial (I2 ≥ 65%).Table 1.Overview of included clinical trials.Study (publication year)Tapering schedule (mg/day)COBRA (1997)In 7 weeks to 7.5. Stop after 28 weeks.*BeSt (2005)In 7 weeks to 7.5. Stop in 8 weeks after week 28 if DAS persistently ≤2.4IDEA (2014)N.A.COBRA-light (2015)arm 1: in 7 weeks to 7.5 arm 2: in 9 weeks to 7.5 Stop after 32 weeks if DAS<1.6.IMPROVED (2014)In 7 weeks to 7.5. Stop after 20 weeks if DAS <1.6 at 4 months.ARCTIC (2016)In 7 weeks to 0 if DAS <1.6 and no swollen joints present.tREACH (2013)In 10 weeks to 0.*CareRA (2017)- in 7 weeks to 7.5, further tapered from week 28, stop after 34 weeks.- Classic- in 6 weeks to 5, further tapered from week 28, stop after 34 weeks.- Slim- in 6 weeks to 5, further tapered from week 28, stop after 34 weeks.- Avant gardeAll if DAS28(CRP) ≤3.2.Hua et al. (2020)Tapering after 4 months to 5, stop after 6 months.*NORD-STAR (2020) - arm 1A (oral prednisolone)In 9 weeks to 5. Stop after 9 months.*DAS=disease activity score; mg=milligram; N.A.=not applicable.*GC tapered and stopped according to protocol, not depending on disease activity score.ConclusionThe success rate of GC discontinuation after bridging as part of initial treatment of RA has been described in a limited number of studies. Reports on observational cohorts did not answer the research question and in clinical trials reports, GC (dis)continuation data were also scarce. However, the available data show that GC can be discontinued successfully in a large majority of patients. The paucity of data also reveals that more efforts are needed to provide data towards identifying the optimal GC bridging and discontinuation strategy, combining Treatment to Target with Starting to Stop.AcknowledgementsWe would like to thank J.W. Schoones for his help and expertise in the systematic literature search.Disclosure of InterestsLotte van Ouwerkerk: None declared, Andriko Palmowski: None declared, Isabell Nevins: None declared, Frank Buttgereit Consultant of: Consultant of AstraZeneca, AbbVie, Grünenthal, Horizon Pharma, Pfizer, and Roche., Grant/research support from: Grant/research support from AbbVie, Horizon Pharma, Pfizer, and Roche., Patrick Verschueren Consultant of: Was consultant for ABBVIE, BMS, Celltrion, Eli Lilly, Galapagos, Gilead, Nordic Pharma, Pfizer and UCB., Employee of: Holds the Pfizer Chair Early Rheumatoid Arthritis Management at KU Leuven., Josef Smolen: None declared, Robert B.M. Landewé Shareholder of: Shareholder of: Director of Rheumatology Consultancy BV., Consultant of: Consultant of: Honoraria from AbbVie, AstraZeneca, BMS, Boehringer Ingelheim, Celgene, Galapagos, Gilead, Glaxo-Smith-Kline, Janssen, Eli-Lilly, Novartis, Pfizer, UCB Pharma., Hans Bijlsma Consultant of: Consultant for Galapagos, Lilly and Sun., Grant/research support from: Received study grants from AbbVie and Roche., Andreas Kerschbaumer: None declared, Rene Westhovens Consultant of: Was consultant for Celltrion, Galapagos and Gilead., Thomas Huizinga: None declared, Cornelia Allaart Grant/research support from: Received study grants for BeSt and IMPROVED from Centocor Inc. (now Janssen) and AbbVie, respectively., Sytske Anne Bergstra Grant/research support from: Received an ASPIRE grant from Pfizer.