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| 2. |
- Askling, J., et al.
(författare)
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How comparable are rates of malignancies in patients with rheumatoid arthritis across the world? A comparison of cancer rates, and means to optimise their comparability, in five RA registries
- 2016
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Ingår i: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 75:10, s. 1789-1796
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Tidskriftsartikel (refereegranskat)abstract
- Background The overall incidence of cancer in patients with rheumatoid arthritis (RA) is modestly elevated. The extent to which cancer rates in RA vary across clinical cohorts and patient subsets, as defined by disease activity or treatment is less known but critical for understanding the safety of existing and new antirheumatic therapies. We investigated comparability of, and means to harmonise, malignancy rates in five RA registries from four continents. Methods Participating RA registries were Consortium of Rheumatology Researchers of North America (CORRONA) (USA), Swedish Rheumatology Quality of Care Register (SRR) (Sweden), Norfolk Arthritis Register (NOAR) (UK), CORRONA International (several countries) and Institute of Rheumatology, Rheumatoid Arthritis (IORRA) (Japan). Within each registry, we analysed a main cohort of all patients with RA from January 2000 to last available data, and sensitivity analyses of sub-cohorts defined by disease activity, treatment change, prior comorbidities and restricted by calendar time or follow-up, respectively. Malignancy rates with 95% CIs were estimated, and standardised for age and sex, based on the distributions from a typical RA clinical trial programme population (fostamatinib). Results There was a high consistency in rates for overall malignancy excluding non-melanoma skin cancer (NMSC), for malignant lymphomas, but not for all skin cancers, across registries, in particular following age/sex standardisation. Standardised rates of overall malignancy excluding NMSC varied from 0.56 to 0.87 per 100 person-years. Within each registry, rates were generally consistent across sensitivity analyses, which differed little from the main analysis. Conclusion In real-world RA populations, rates of both overall malignancy and of lymphomas are consistent.
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| 3. |
- Barbulescu, A, et al.
(författare)
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COMPARATIVE EFFECTIVENESS OF JAKI VERSUS BDMARDS; A NATIONWIDE STUDY IN RA
- 2021
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Ingår i: ANNALS OF THE RHEUMATIC DISEASES. - : BMJ. - 0003-4967 .- 1468-2060. ; 80, s. 68-68
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The Janus kinase inhibitors (JAKi) have been increasingly used for the treatment of rheumatoid arthritis (RA) in Sweden, with baricitinib representing ~80% of prescriptions. Evidence regarding the comparative effectiveness of JAKis versus biologics (bDMARDs), and in particular non- tumour-necrosis-factor inhibitor (TNFi) bDMARDs, in real-life is limited.Objectives:To compare RA patients treated with bDMARDs and JAKi in Sweden, in terms of: (1) patient characteristics at treatment start; (2) proportions of patients remaining on therapy, and response rates, at 12 months.Methods:RA patients starting treatment in 2017 and 2018 with either a TNFi, rituximab, abatacept, interleukin 6 inhibitors (IL6i) or a JAKi as different lines of treatment were identified in the Swedish Rheumatology Quality Register. One patient could contribute with more than one treatment episode.Treatment response at 12 months was measured as EULAR good response, HAQ improvement >0.2 units, DAS28 and CDAI remission, and as 0 tender and swollen joint counts (28JC). Patients were classified as non-responders if they stopped treatment before evaluation due to safety or inefficacy. Responses for patients who stopped treatment due to pregnancy or death and patients on treatment but with missing response were imputed using multiple imputation.Proportions of responders and differences in proportions between treatment groups, adjusted using inverse probability of treatment weighting, were estimated using linear regression with robust standard errors.Results:JAKi were often used after bDMARDs, and less frequently prescribed in combination with methotrexate. Measured comorbidities were less frequent among JAKi initiators than among non-TNFi biologic initiators, but RA activity was similar (Table).Table 1.Patient characteristics at treatment initiationCharacteristicMedian (IQR) or N (%)AbataceptIL6iRituximabTNFiJAKiTreatment Starts6945346923497905Age63 (53-71)59 (48-70)65 (54-73)59 (47-68)60 (51-70)Female543 (78)441 (83)519 (75)2739 (78)759 (84)RA duration (years)13 (5-21)10 (5-18)12 (6-22)9 (3-17)13 (7-22)Rheum. factor535 (79)385 (73)588 (87)2405 (70)686 (77)DAS284.8 (3.9-5.6)4.9 (4.0-5.7)4.7 (3.8-5.5)4.4 (3.4-5.3)4.7 (3.9-5.7)HAQ1.3 (0.8-1.6)1.3 (0.8-1.8)1.3 (0.8-1.8)1.0 (0.5-1.4)1.3 (0.8-1.8)Tender joints5 (2-9)6 (3-10)5 (2-9)4 (2-8)6 (2-10)Swollen joints4 (2-6)4 (2-7)4 (2-7)3 (1-6)4 (2-7)ts/bDMARD line3 (2-4)3 (2-4)2 (1-4)1 (1-2)4 (2-6)At least one prev. TNFi539 (78)442 (83)457 (66)1448 (41)770 (85)At least one prev. non-TNFi271 (39)220 (41)243 (35)441 (13)584 (65)Methotrexate co-treatment264 (50)172 (40)286 (53)1708 (62)296 (40)Glucocorticoids co-treatment247 (47)186 (43)275 (51)1126 (41)389 (53)Cancer*90 (2.8)64 (2.3)363 (7.7)410 (1.8)20 (2.2)Cardio-vascular dis.*245 (7.5)123 (4.4)322 (6.8)749 (3.4)41 (4.4)Chronic respiratory dis.*303 (9.3)140 (5.0)473 (10.0)721 (3.2)50 (5.4)Diabetes*324 (9.9)216 (7.7)456 (9.7)1479 (6.7)69 (7.5)* any diagnosis within 5 years before start Adjusted differences in proportion with each response outcomeIn a crude comparison, 65% (61%-68%) of JAKi, 62% (59%-66%) of abatacept, 58% (53%-62%) of IL6i, 80% (77%-83%) of rituximab and 68% (67%-70%) of TNFi initiators remained on treatment at 12 months after start. Also, JAKi showed lower overall responder proportions than TNFi, rituximab and IL6i.After adjustment for demographic and socio-economic factors, RA disease activity, previous use of ts/bDMARDs, co-medication with glucocorticoids and methotrexate and comorbidities at baseline, no significant differences in responder proportions between JAKi and bDMARDs remained (Figure). Furthermore, the adjusted proportions of patients on treatment were higher for JAKi and rituximab than for the other bDMARDs.Conclusion:This preliminary analysis of patients treated in clinical practice found no statistically significant difference in effectiveness between JAKi and bDMARDs.Disclosure of Interests:Andrei Barbulescu: None declared, Johan Askling Grant/research support from: Abbvie, Astra-Zeneca, BMS, Eli Lilly, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB. These entities have entered into agreements with Karolinska Institutet with JA as principal investigator, mainly in the context of safety monitoring of biologics via the ARTIS national safety monitoring system, Katerina Chatzidionysiou Speakers bureau: Eli Lilly, Abbvie and Pfizer, Consultant of: Eli Lilly, Abbvie and Pfizer, Helena Forsblad-d’Elia: None declared, Alf Kastbom Employee of: Sanofi, Ulf Lindström: None declared, Carl Turesson Speakers bureau: Abbvie, Bristol-Myers Squibb, Medac, Pfizer, Roche, Consultant of: Roche, Grant/research support from: Bristol-Myers Squibb, Thomas Frisell: None declared
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| 4. |
- Bower, H, et al.
(författare)
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Influenza outcomes in patients with inflammatory joint diseases and DMARDs: how do they compare to those of COVID-19?
- 2022
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Ingår i: Annals of the rheumatic diseases. - : BMJ. - 1468-2060 .- 0003-4967. ; 81:3, s. 433-439
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Tidskriftsartikel (refereegranskat)abstract
- To estimate absolute and relative risks for seasonal influenza outcomes in patients with inflammatory joint diseases (IJDs) and disease-modifying antirheumatic drugs (DMARDs). To contextualise recent findings on corresponding COVID-19 risks.MethodsUsing Swedish nationwide registers for this cohort study, we followed 116 989 patients with IJD and matched population comparators across four influenza seasons (2015–2019). We quantified absolute risks of hospitalisation and death due to influenza, and compared IJD to comparators via Cox regression. We identified 71 556 patients with IJD on active treatment with conventional synthetic DMARDs and biological disease-modifying antirheumatic drugs (bDMARDs)/targeted synthetic disease-modifying antirheumatic drug (tsDMARDs) at the start of each influenza season, estimated risks for the same outcomes and compared these risks across DMARDs via Cox regression.ResultsPer season, average risks for hospitalisation listing influenza were 0.25% in IJD and 0.1% in the general population, corresponding to a crude HR of 2.38 (95% CI 2.21 to 2.56) that decreased to 1.44 (95% CI 1.33 to 1.56) following adjustments for comorbidities. For death listing influenza, the corresponding numbers were 0.015% and 0.006% (HR=2.63, 95% CI 1.93 to 3.58, and HR=1.46, 95% CI 1.07 to 2.01). Absolute risks for influenza outcomes were half (hospitalisation) and one-tenth (death) of those for COVID-19, but relative estimates comparing IJD to the general population were similar.ConclusionsIn absolute terms, COVID-19 in IJD outnumbers that of average seasonal influenza, but IJD entails a 50%–100% increase in risk for hospitalisation and death for both types of infections, which is largely dependent on associated comorbidities. Overall, bDMARDs/tsDMARDs do not seem to confer additional risk for hospitalisation or death related to seasonal influenza.
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| 7. |
- Courvoisier, DS, et al.
(författare)
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EULAR points to consider when analysing and reporting comparative effectiveness research using observational data in rheumatology
- 2022
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Ingår i: Annals of the rheumatic diseases. - : BMJ. - 1468-2060 .- 0003-4967. ; 81:6, s. 780-785
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Tidskriftsartikel (refereegranskat)abstract
- Comparing treatment effectiveness over time in observational settings is hampered by several major threats, among them confounding and attrition bias.ObjectivesTo develop European Alliance of Associations for Rheumatology (EULAR) points to consider (PtC) when analysing and reporting comparative effectiveness research using observational data in rheumatology.MethodsThe PtC were developed using a three-step process according to the EULAR Standard Operating Procedures. Based on a systematic review of methods currently used in comparative effectiveness studies, the PtC were formulated through two in-person meetings of a multidisciplinary task force and a two-round online Delphi, using expert opinion and a simulation study. Finally, feedback from a larger audience was used to refine the PtC. Mean levels of agreement among the task force were calculated.ResultsThree overarching principles and 10 PtC were formulated, addressing, in particular, potential biases relating to attrition or confounding by indication. Building on Strengthening the Reporting of Observational Studies in Epidemiology guidelines, these PtC insist on the definition of the baseline for analysis and treatment effectiveness. They also focus on the reasons for stopping treatment as an important consideration when assessing effectiveness. Finally, the PtC recommend providing key information on missingness patterns.ConclusionTo improve the reliability of an increasing number of real-world comparative effectiveness studies in rheumatology, special attention is required to reduce potential biases. Adherence to clear recommendations for the analysis and reporting of observational comparative effectiveness studies will improve the trustworthiness of their results.
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| 8. |
- Courvoisier, D, et al.
(författare)
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POINTS TO CONSIDER WHEN ANALYSING AND REPORTING COMPARATIVE EFFECTIVENESS RESEARCH WITH OBSERVATIONAL DATA IN RHEUMATOLOGY
- 2020
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Ingår i: ANNALS OF THE RHEUMATIC DISEASES. - : BMJ. - 0003-4967 .- 1468-2060. ; 79, s. 124-125
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Comparing drug effectiveness in observational settings is hampered by several major threats, among them confounding and attrition bias bias (patients who stop treatment no longer contribute information, which may overestimate true drug effectiveness).Objectives:To present points to consider (PtC) when analysing and reporting comparative effectiveness with observational data in rheumatology (EULAR-funded taskforce).Methods:The task force comprises 18 experts: epidemiologists, statisticians, rheumatologists, patients, and health professionals.Results:A systematic literature review of methods currently used for comparative effectiveness research in rheumatology and a statistical simulation study were used to inform the PtC (table). Overarching principles focused on defining treatment effectiveness and promoting robust and transparent epidemiological and statistical methods increase the trustworthiness of the results.Points to considerReporting of comparative effectiveness observational studies must follow the STROBE guidelinesAuthors should prepare a statistical analysis plan in advanceTo provide a more complete picture of effectiveness, several outcomes across multiple health domains should be comparedLost to follow-up from the study sample must be reported by the exposure of interestThe proportion of patients who stop and/or change therapy over time, as well as the reasons for treatment discontinuation must be reportedCovariates should be chosen based on subject matter knowledge and model selection should be justifiedThe study baseline should be at treatment initiation and a description of how covariate measurements relate to baseline should be includedThe analysis should be based on all patients starting a treatment and not limited to patients remaining on treatment at a certain time pointWhen treatment discontinuation occurs before the time of outcome assessment, this attrition should be taken into account in the analysis.Sensitivity analyses should be undertaken to explore the influence of assumptions related to missingness, particularly in case of attritionConclusion:The increased use of real-world comparative effectiveness studies makes it imperative to reduce divergent or contradictory results due to biases. Having clear recommendations for the analysis and reporting of these studies should promote agreement of observational studies, and improve studies’ trustworthiness, which may also facilitate meta-analysis of observational data.Disclosure of Interests:Delphine Courvoisier: None declared, Kim Lauper: None declared, Sytske Anne Bergstra: None declared, Maarten de Wit Grant/research support from: Dr. de Wit reports personal fees from Ely Lilly, 2019, personal fees from Celgene, 2019, personal fees from Pfizer, 2019, personal fees from Janssen-Cilag, 2017, outside the submitted work., Consultant of: Dr. de Wit reports personal fees from Ely Lilly, 2019, personal fees from Celgene, 2019, personal fees from Pfizer, 2019, personal fees from Janssen-Cilag, 2017, outside the submitted work., Speakers bureau: Dr. de Wit reports personal fees from Ely Lilly, 2019, personal fees from Celgene, 2019, personal fees from Pfizer, 2019, personal fees from Janssen-Cilag, 2017, outside the submitted work., Bruno Fautrel Grant/research support from: AbbVie, Lilly, MSD, Pfizer, Consultant of: AbbVie, Biogen, BMS, Boehringer Ingelheim, Celgene, Lilly, Janssen, Medac MSD France, Nordic Pharma, Novartis, Pfizer, Roche, Sanofi Aventis, SOBI and UCB, Thomas Frisell: None declared, Kimme Hyrich Grant/research support from: Pfizer, UCB, BMS, Speakers bureau: Abbvie, Florenzo Iannone Consultant of: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Speakers bureau: Speaker and consulting fees from AbbVie, Eli Lilly, Novartis, Pfizer, Roche, Sanofi, UCB, MSD, Joanna KEDRA: None declared, Pedro M Machado Consultant of: PMM: Abbvie, Celgene, Janssen, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Speakers bureau: PMM: Abbvie, BMS, Lilly, MSD, Novartis, Pfizer, Roche and UCB, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Ziga Rotar Consultant of: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Speakers bureau: Speaker and consulting fees from Abbvie, Amgen, Biogen, Eli Lilly, Medis, MSD, Novartis, Pfizer, Roche, Sanofi., Maria Jose Santos Speakers bureau: Novartis and Pfizer, Tanja Stamm Grant/research support from: AbbVie, Roche, Consultant of: AbbVie, Sanofi Genzyme, Speakers bureau: AbbVie, Roche, Sanofi, Simon Stones Consultant of: I have been a paid consultant for Envision Pharma Group and Parexel. This does not relate to this abstract., Speakers bureau: I have been a paid speaker for Actelion and Janssen. These do not relate to this abstract., Anja Strangfeld Speakers bureau: AbbVie, BMS, Pfizer, Roche, Sanofi-Aventis, Robert B.M. Landewé Consultant of: AbbVie; AstraZeneca; Bristol-Myers Squibb; Eli Lilly & Co.; Galapagos NV; Novartis; Pfizer; UCB Pharma, Axel Finckh Grant/research support from: Pfizer: Unrestricted research grant, Eli-Lilly: Unrestricted research grant, Consultant of: Sanofi, AB2BIO, Abbvie, Pfizer, MSD, Speakers bureau: Sanofi, Pfizer, Roche, Thermo Fisher Scientific
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| 10. |
- Di Giuseppe, D, et al.
(författare)
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DIFFERENCES IN DRUG SURVIVAL BETWEEN ORIGINATOR AND BIOSIMILAR PRODUCTS AMONG FIRST USERS OF EACH MOLECULE
- 2021
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Ingår i: ANNALS OF THE RHEUMATIC DISEASES. - : BMJ. - 0003-4967 .- 1468-2060. ; 80, s. 535-535
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Biosimilar products of biological disease-modifying antirheumatic drugs (bDMARDs) entered the Swedish market in 2015, with regulatory approvals based on head to head trials of limited duration. Longer-term comparative drug survival, in clinical practice, remains less well documented.Objectives:To compare survival on drug between biosimilars and their originator products among first starters of etanercept, infliximab, adalimumab and rituximab.Methods:Data from the Swedish Rheumatology Quality register (SRQ) was used to identify and follow patients who started a first ever treatment with etanercept since April 2015 (originator=ETA,biosimilar= SB4), infliximab since March 2014 (originator=IFX,biosimilar= CT-P13), adalimumab since January 2018 (originator=ADA biosimilars=SB5, ABP501), or rituximab since January 2018 (originator=RIT,biosimilar= GP2013), through December 31st, 2019, date of first discontinuation of the drug, or death. Discontinuation was defined as lack of effectiveness or adverse events, while other reasons for interruption of the drug (including non-medical switch) were considered censoring events. Descriptive characteristics were collected from the SRQ and tabulated. Hazard ratios (HR) of discontinuation were estimated using Cox regression, with each drug analyzed separately, adjusted for age,sex,indication,line of treatment,disease duration,year of treatment start,region and concomitant use of csDMARD.Results:9274 patients started etanercept(49% SB4), 3609 started infliximab(64% CT-P13), 3117 started adalimumab(27% SB5, 14% ABP 501), and 763 started rituximab(39% GP2013), Table 1. Patients starting CT-P13 and GP2013 were less likely to be biologics-naïve compared to those starting the originator product. Initiators of SB5,ABP501 and GP2013 were more likely,and those starting CT-P13 were less likely,to be on concomitant csDMARDs compared to those starting the originator products. Patients characteristics of ETA and SB4 were similar.The introduction of a biosimilar was typically followed by a decrease in the uptake of the originator, but for ETA a change in pricing in 2018 later led to a reversal of this pattern (Figure 1).For IFX,ADA,and RIT, survival on drug was similar for the originator and its biosimilar(s). For ETA,risk of discontinuation was somewhat lower for the biosimilar than for the originator(adjusted HR:0.87,95% confidence interval:0.79-0.95), Table 1.Table 1.Hazard ratios of discontinuation and descriptive characteristics of biosimilar vs. originator among first starters of each molecule, until 31st December 2019.EtanerceptInfliximabAdalimumabRituximabOriginatorSB4OriginatorCT-P13OriginatorSB5ABP 501OriginatorGP2013N47214553130823011834852431465298Discontinuation12891236582878399139805726Adjusted hazard ratios*Ref0.87 (0.79-0.95)Ref1.14 (0.99-1.31)Ref1.02 (0.83-1.26)1.16 (0.88-1.52)Ref1.12 (0.68-1.85)Age, mean years (std)51 (16)51 (15)49 (16)49 (16)48 (15)52 (15)51 (15)59 (15)60 (15)Female, %67%65%61%64%62%64%65%75%76%RA, %46%48%39%35%33%42%43%61%76%Bionaïve, %72%72%76%69%45%52%43%53%38%Disease duration, mean years (std)11 (12)11 (11)11 (11)11 (11)12 (13)12 (11)14 (15)14 (19)15 (11)DAS28, mean4.0 (1.3)4.0 (1.4)4.1 (1.4)4.1 (1.4)3.7 (1.4)3.8 (1.3)4.0 (1.3)4.5 (1.4)4.7 (1.4)Concomitant csDMARDs, %45%47%57%48%37%49%42%36%43%Abbreviations: RA=rheumatoid arthritis. csDMARDs=conventional synthetic DMARD, std=standard deviation.Figure 1.Number of starts of biosimilars compared to the originator during the follow-up time, by moleculeConclusion:Despite their identical indications and therapeutic positioning, there are some differences in the baseline characteristics between patients who start ADA, IFX and RIT and their biosimilars. There are no differences in drug survival between originator and biosimilar with the possible exception of etanercept although the observed difference should be interpreted in light of possible unmeasured or residual channeling.Disclosure of Interests:Daniela Di Giuseppe: None declared, Hannah Bower: None declared, Bénédicte Delcoigne: None declared, Thomas Frisell: None declared, Katerina Chatzidionysiou Consultant of: Eli Lilly, AbbVie and Pfizer, Ulf Lindström: None declared, Christopher Sjowall: None declared, Elisabet Lindqvist: None declared, Johan Askling Grant/research support from: Abbvie, Astra-Zeneca, BMS, Eli Lilly, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi, and UCB,
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