| 1. |
- Brahe, C. H., et al.
(författare)
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Retention and response rates in 14 261 PsA patients starting TNF inhibitor treatment-results from 12 countries in EuroSpA
- 2020
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Ingår i: Rheumatology. - : Oxford University Press (OUP). - 1462-0324 .- 1462-0332. ; 59:7, s. 1640-1650
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Tidskriftsartikel (refereegranskat)abstract
- Objective. To investigate TNF inhibitor (TNFi) retention and response rates in European biologic-naive patients with PsA. Methods. Prospectively collected data on PsA patients in routine care from 12 European registries were pooled. Heterogeneity in baseline characteristics between registries were explored (analysis of variance and pairwise comparison). Retention rates (Kaplan-Meier), clinical remission [28-joint count DAS (DAS28) <2.6; 28 joint Disease Activity index for Psoriatic Arthritis 4] and ACR criteria for 20% improvement (ACR20)/ACR50/ACR70 were calculated, including LUNDEX adjustment. Results. Overall, 14 261 patients with PsA initiated a first TNFi. Considerable heterogeneity of baseline characteristics between registries was observed. The median 12-month retention rate (95% CI) was 77% (76, 78%), ranging from 68 to 90% across registries. Overall, DAS28/28 joint Disease Activity index for Psoriatic Arthritis remission rates at 6 months were 56%/27% (LUNDEX: 45%/22%). Six-month ACR20/50/70 responses were 53%/38%/22%, respectively. In patients initiating a first TNFi after 2009 with registered fulfilment of ClASsification for Psoriatic ARthritis (CASPAR) criteria (n = 1980) or registered one or more swollen joint at baseline (n = 5803), the retention rates and response rates were similar to those found overall. Conclusion. Approximately half of >14 000 patients with PsA who initiated first TNFi treatment in routine care were in DAS28 remission after 6 months, and three-quarters were still on the drug after 1 year. Considerable heterogeneity in baseline characteristics and outcomes across registries was observed. The feasibility of creating a large European database of PsA patients treated in routine care was demonstrated, offering unique opportunities for research with real-world data.
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| 2. |
- Chatzidionysiou, K, et al.
(författare)
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Rituximab Retreatment in Rheumatoid Arthritis in a Real-life Cohort: Data from the CERERRA Collaboration
- 2017
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Ingår i: The Journal of rheumatology. - : The Journal of Rheumatology. - 0315-162X .- 1499-2752. ; 44:2, s. 162-169
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Tidskriftsartikel (refereegranskat)abstract
- Several aspects of rituximab (RTX) retreatment in rheumatoid arthritis (RA) need to be further elucidated. The aim of this study was to describe the effect of repeated courses of RTX on disease activity and to compare 2 retreatment strategies, fixed-interval versus on-flare retreatment, in a large international, observational, collaborative study.Methods.In the first analysis, patients with RA who received at least 4 cycles with RTX were included. In the second analysis, patients who received at least 1 RTX retreatment and for whom information about the strategy for retreatment was available were identified. Two retreatment strategies (fixed-interval vs on-flare) were compared by fitting-adjusted, mixed-effects models of 28-joint Disease Activity Score (DAS28) over time for first and second retreatment.Results.A total of 1530 patients met the eligibility criteria for the first analysis. Significant reductions of mean DAS28 between the starts of subsequent treatment cycles were observed (at start of first treatment cycle: 5.5; second: 4.3; third: 3.8; and fourth: 3.5), suggesting improved response after each additional cycle (p < 0.0001 for all pairwise comparisons). A total of 800 patients qualified for the second analysis: 616 were retreated on flare and 184 at fixed interval. For the first retreatment, the fixed-interval retreatment group yielded significantly better results than the on-flare group (estimated marginal mean DAS28 = 3.8, 95% CI 3.6–4.1 vs 4.6, 95% CI 4.5–4.7, p < 0.0001). Similar results were found for the second retreatment.Conclusion.Repeated treatment with RTX leads to further clinical improvement after the first course of RTX. A fixed-interval retreatment strategy seems to be more effective than on-flare retreatment.
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| 5. |
- Christiansen, SN, et al.
(författare)
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SECULAR TRENDS IN BASELINE CHARACTERISTICS, TREATMENT RETENTION AND RESPONSE RATES IN 17453 BIONAIVE PSORIATIC ARTHRITIS PATIENTS INITIATING TNFI - RESULTS FROM THE EUROSPA COLLABORATION
- 2021
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Ingår i: ANNALS OF THE RHEUMATIC DISEASES. - : BMJ. - 0003-4967 .- 1468-2060. ; 80, s. 131-132
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Knowledge of changes over time in baseline characteristics and tumor necrosis factor inhibitor (TNFi) response in bionaïve psoriatic arthritis (PsA) patients treated in routine care is limited.Objectives:To investigate secular trends in baseline characteristics and retention, remission and response rates in PsA patients initiating a first TNFi.Methods:Prospectively collected data on bionaïve PsA patients starting TNFi in routine care from 15 European countries were pooled. According to year of TNFi initiation, three groups were defined a priori based on bDMARD availability: Group A (1999–2008), Group B (2009–2014) and Group C (2015–2018).Retention rates (Kaplan-Meier), crude and LUNDEX adjusted1 remission (Disease Activity Score (DAS28) <2.6, 28-joint Disease Activity index for PsA (DAPSA28) ≤4, Clinical Disease Activity Index (CDAI) ≤2.8) and ACR50 response rates were assessed at 6, 12 and 24 months. No statistical comparisons were made.Results:A total of 17453 PsA patients were included (4069, 7551 and 5833 in groups A, B and C).Patients in group A were older and had longer disease duration compared to B and C. Retention rates at 6, 12 and 24 months were highest in group A (88%/77%/64%) but differed little between B (83%/69%/55%) and C (84%/70%/56%).Baseline disease activity was higher in group A than in B and C (DAS28: 4.6/4.3/4.0, DAPSA28: 29.9/25.7/24.0, CDAI: 21.8/20.0/18.6), and this persisted at 6 and 12 months. Crude and LUNDEX adjusted remission rates at 6 and 12 months tended to be lowest in group A, although crude/LUNDEX adjusted ACR50 response rates at all time points were highest in group A. At 24 months, disease activity and remission rates were similar in the three groups (Table).Table 1.Secular trends in baseline characteristics, treatment retention, remission and response rates in European PsA patients initiating a 1st TNFiBaseline characteristicsGroup A(1999–2008)Group B(2009–2014)Group C(2015–2018)Age, median (IQR)62 (54–72)58 (49–67)54 (45–62)Male, %514847Years since diagnosis, median (IQR)5 (2–10)3 (1–9)3 (1–8)Smokers, %161717DAS28, median (IQR)4.6 (3.7–5.3)4.3 (3.4–5.1)4.0 (3.2–4.8)DAPSA28, median (IQR)29.9 (19.3–41.8)25.7 (17.2–38.1)24.0 (16.1–35.5)CDAI, median (IQR)21.8 (14.0–31.1)20.0 (13.0–29.0)18.6 (12.7–26.1)TNFi drug, % (Adalimumab / Etanercept / Infliximab / Certolizumab / Golimumab)27 / 43 / 30 / 0 / 036 / 31 / 14 / 5 / 1421 / 40 / 21 / 8 / 10Follow up6 months12 months24 monthsGr AGr BGr CGr AGr BGr CGr AGr BGr CRetention rates, % (95% CI)88 (87–89)83 (82–84)84 (83–85)79 (78–80)72 (71–73)72 (71–73)68 (67–69)60 (59–61)60 (59–62)DAS28, median (IQR)2.7 (1.9–3.6)2.4 (1.7–3.4)2.3 (1.7–3.2)2.5 (1.8–3.4)2.2 (1.6–3.1)2.1 (1.6–2.9)2.1 (1.6–3.1)2.0 (1.6–2.9)1.9 (1.5–2.6)DAPSA28, median (IQR)10.6 (4.8–20.0)9.5 (3.9–18.3)8.7 (3.6–15.9)9.1 (4.1–17.8)7.7 (3.1–15.4)7.6 (2.9–14.4)6.7 (2.7–13.7)6.6 (2.7–13.5)5.9 (2.4–11.8)CDAI, median (IQR)7.8 (3.0–15.2)8.0 (3.0–15.0)6.4 (2.6–12.2)6.4 (2.5–13.0)6.2 (2.5–12.1)5.8 (2.2–11.4)5.0 (2.0–11.0)5.5 (2.0–11.2)5.0 (2.0–9.0)DAS28 remission, %, c/L47 / 4255 / 4661 / 5153 / 4362 / 4566 / 4864 / 4268 / 3775 / 41DAPSA28 remission, %, c/L22 / 1926 / 2228 / 2325 / 2031 / 2232 / 2336 / 2334 / 1938 / 21CDAI remission, %, c/L23 / 2123 / 1926 / 2227 / 2127 / 2029 / 2134 / 2231 / 1735 / 19ACR50 response, %, c/L26 / 2322 / 1824 / 2027 / 2223 / 1721 / 1523 / 1518 / 1014 / 8Gr, Group; c/L, crude/LUNDEX.Conclusion:Over the past 20 years, patient age, disease duration and disease activity level at the start of the first TNFi in PsA patients have decreased. Furthermore, TNFi retention rates have decreased while remission rates have increased, especially remission rates within the first year of treatment. These findings may reflect a greater awareness of early diagnosis in PsA patients, a lowered threshold for initiating TNFi and the possibility for earlier switching in patients with inadequate treatment response.References:[1]Arthritis Rheum 2006; 54: 600-6.Acknowledgements:Novartis Pharma AG and IQVIA for supporting the EuroSpA Research Collaboration Network.Disclosure of Interests:Sara Nysom Christiansen Speakers bureau: BMS and GE, Grant/research support from: Novartis, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis, Simon Horskjær Rasmussen: None declared, Anne Gitte Loft Speakers bureau: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, UCB, Consultant of: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, UCB, Grant/research support from: Novartis, Johan K Wallman Consultant of: Celgene, Eli Lilly, Novartis, Florenzo Iannone Speakers bureau: Abbvie, MSD, Novartis, Pfizer and BMS, Brigitte Michelsen Consultant of: Novartis, Grant/research support from: Novartis, Michael J. Nissen Speakers bureau: Novartis, Eli Lilly, Celgene, and Pfizer, Consultant of: Novartis, Eli Lilly, Celgene, and Pfizer, Jakub Zavada: None declared, Maria Jose Santos Speakers bureau: AbbVie, Novartis, Pfizer, Manuel Pombo-Suarez: None declared, Kari Eklund: None declared, Matija Tomsic Speakers bureau: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Consultant of: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Björn Gudbjornsson Speakers bureau: Amgen and Novartis, İsmail Sari: None declared, Catalin Codreanu Speakers bureau: AbbVie, Amgen, Egis, Novartis, Pfizer, UCB, Grant/research support from: AbbVie, Amgen, Egis, Novartis, Pfizer, UCB, Daniela Di Giuseppe: None declared, Bente Glintborg Grant/research support from: Pfizer, Biogen, AbbVie, Marco Sebastiani: None declared, Karen Minde Fagerli: None declared, Burkhard Moeller: None declared, Karel Pavelka Speakers bureau: AbbVie, Roche, MSD, UCB, Pfizer, Novartis, Egis, Gilead, Eli Lilly, Consultant of: AbbVie, Roche, MSD, UCB, Pfizer, Novartis, Egis, Gilead, Eli Lilly, Anabela Barcelos: None declared, Carlos Sánchez-Piedra: None declared, Heikki Relas: None declared, Ziga Rotar Speakers bureau: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Consultant of: Abbvie, Amgen, Biogen, Medis, MSD, Novartis, Pfizer, Thorvardur Love: None declared, Servet Akar: None declared, Ruxandra Ionescu Speakers bureau: Abbvie, Amgen, Boehringer-Ingelheim Eli-Lilly,Novartis, Pfizer, Sandoz, UCB, Gary Macfarlane Grant/research support from: GlaxoSmithKline, Marleen G.H. van de Sande: None declared, Merete L. Hetland Speakers bureau: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis., Mikkel Østergaard Speakers bureau: AbbVie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Centocor, GSK, Hospira, Janssen, Merck, Mundipharma, Novartis, Novo, Orion, Pfizer, Regeneron, Schering-Plough, Roche, Takeda, UCB and Wyeth, Consultant of: AbbVie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Centocor, GSK, Hospira, Janssen, Merck, Mundipharma, Novartis, Novo, Orion, Pfizer, Regeneron, Schering-Plough, Roche, Takeda, UCB and Wyeth
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| 6. |
- 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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| 7. |
- 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. |
- Georgiadis, S, et al.
(författare)
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CAN SINGLE IMPUTATION TECHNIQUES FOR BASDAI COMPONENTS RELIABLY CALCULATE THE COMPOSITE SCORE IN AXIAL SPONDYLOARTHRITIS PATIENTS?
- 2022
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Ingår i: ANNALS OF THE RHEUMATIC DISEASES. - : BMJ. - 0003-4967 .- 1468-2060. ; 81, s. 212-213
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In axial spondyloarthritis (axSpA), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) is a key patient-reported outcome. However, one or more of its components may be missing when recorded in clinical practice.ObjectivesTo determine whether an individual patient’s BASDAI at a given timepoint can be reliably calculated with different single imputation techniques and to explore the impact of the number of missing components and/or differences between missingness of individual components.MethodsReal-life data from axSpA patients receiving tumour necrosis factor inhibitors (TNFi) from 13 countries in the European Spondyloarthritis (EuroSpA) Research Collaboration Network were utilized [1]. We studied missingness in BASDAI components based on simulations in a complete dataset, where we applied and expanded the approach of Ramiro et al. [2]. After introducing one or more missing components completely at random, BASDAI was calculated from the available components and with three different single imputation techniques: possible middle value (i.e. 50) of the component and mean and median of the available components. Differences between the observed (original) and calculated scores were assessed and correct classification of patients as having BASDAI<40 mm was additionally evaluated. For the setting with one missing component, differences arising between missing one of components 1-4 versus 5-6 were explored. Finally, the performance of imputations in relation to the values of the original score was investigated.ResultsA total of 19,894 axSpA patients with at least one complete BASDAI registration at any timepoint were included. 59,126 complete BASDAI registrations were utilized for the analyses with a mean BASDAI of 38.5 (standard deviation 25.9). Calculating BASDAI from the available components and imputing with mean or median showed similar levels of agreement (Table 1). When allowing one missing component, >90% had a difference of ≤6.9 mm between the original and calculated scores and >95% were correctly classified as BASDAI<40 (Table 1). However, separate analyses of components 1-4 and 5-6 as a function of the BASDAI score suggested that imputing any one of the first four BASDAI components resulted in a level of agreement <90% for specific BASDAI values while imputing one of the stiffness components 5-6 always reached a level of agreement >90% (Figure 1, upper panels). As expected, it was observed that regardless of the BASDAI component set to missing and the imputation technique used, correct classification of patients as BASDAI<40 was less than 95% for values around the cutoff (Figure 1, lower panels).Table 1.Level of agreement between the original and calculated BASDAI and correct classification for BASDAI<40 mmLevel of agreement with Dif≤6.9 mm* (%)Correct classification for BASDAI<40 mm** (%)1 missing componentAvailable93.996.9Value 5073.996.3Mean94.296.8Median93.196.82 missing componentsAvailable83.794.8Value 5040.792.8Mean83.594.8Median82.894.73 missing componentsAvailable71.992.6Value 5028.187.3Mean72.292.6Median69.792.2* The levels of agreement with a difference (Dif) of ≤6.9 mm between the original and calculated scores were based on the half of the smallest detectable change. Agreement of >90% was considered as acceptable. ** Correct classification of >95% was considered as acceptable.Figure 1.Level of agreement between the original and calculated BASDAI and correct classification for BASDAI<40 mm as a function of the original scoreConclusionBASDAI calculation with available components gave similar results to single imputation of missing components with mean or median. Only when missing one of BASDAI components 5 or 6, single imputation techniques can reliably calculate individual BASDAI scores. However, missing any single component value results in misclassification of patients with original BASDAI scores close to 40.References[1]Ørnbjerg et al. (2019). Ann Rheum Dis, 78(11), 1536-1544.[2]Ramiro et al. (2014). Rheumatology, 53(2), 374-376.AcknowledgementsNovartis Pharma AG and IQVIA for supporting the EuroSpA collaboration.Disclosure of InterestsStylianos Georgiadis Grant/research support from: Novartis, Myriam Riek Grant/research support from: Novartis, Christos Polysopoulos Grant/research support from: Novartis, Almut Scherer Grant/research support from: Novartis, Daniela Di Giuseppe: None declared, Gareth T. Jones Speakers bureau: Janssen, Grant/research support from: AbbVie, Pfizer, UCB, Amgen, GSK, Merete Lund Hetland Grant/research support from: Abbvie, Biogen, BMS, Celltrion, Eli Lilly, Janssen Biologics B.V, Lundbeck Fonden, MSD, Medac, Pfizer, Roche, Samsung Biopies, Sandoz, Novartis, Mikkel Østergaard Speakers bureau: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, UCB, Consultant of: Abbvie, BMS, Boehringer-Ingelheim, Celgene, Eli-Lilly, Hospira, Janssen, Merck, Novartis, Novo, Orion, Pfizer, Regeneron, Roche, Sandoz, Sanofi, UCB, Grant/research support from: Abbvie, BMS, Merck, Celgene, Novartis, Simon Horskjær Rasmussen Grant/research support from: Novartis, Johan K Wallman Consultant of: AbbVie, Amgen, Celgene, Eli Lilly, Novartis, Bente Glintborg Grant/research support from: Pfizer, Abbvie, BMS, Anne Gitte Loft Speakers bureau: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Consultant of: AbbVie, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Karel Pavelka Speakers bureau: Pfizer, MSD, BMS, UCB, Amgen, Egis, Roche, AbbVie, Consultant of: Pfizer, MSD, BMS, UCB, Amgen, Egis, Roche, AbbVie, Jakub Zavada Speakers bureau: Abbvie, Elli-Lilly, Sandoz, Novartis, Egis, UCB, Consultant of: Abbvie, Elli-Lilly, Sandoz, Novartis, Egis, UCB, Merih Birlik: None declared, Ayten Yazici Grant/research support from: Roche, Brigitte Michelsen Grant/research support from: Novartis, Eirik kristianslund: None declared, Adrian Ciurea Speakers bureau: AbbVie, Eli Lilly, Merck Sharp & Dohme, Novartis, Pfizer, Consultant of: AbbVie, Eli Lilly, Merck Sharp & Dohme, Novartis, Pfizer, Michael J. Nissen Speakers bureau: AbbVie, Eli Lilly, Janssens, Novartis, Pfizer, Consultant of: AbbVie, Eli Lilly, Janssens, Novartis, Pfizer, Ana Maria Rodrigues Speakers bureau: Abbvie, Amgen, Consultant of: Abbvie, Amgen, Grant/research support from: Novartis, Pfizer, Amgen, Maria Jose Santos Speakers bureau: Abbvie, AstraZeneca, Lilly, Novartis, Pfizer, Gary Macfarlane Grant/research support from: GSK, Anna-Mari Hokkanen Grant/research support from: MSD, Heikki Relas Speakers bureau: Abbvie, Celgene, Pfizer, UCB, Viatris, Consultant of: Abbvie, Celgene, Pfizer, UCB, Viatris, Catalin Codreanu Speakers bureau: AbbVie, Amgen, Boehringer Ingelheim, Ewopharma, Lilly, Novartis, Pfizer, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Ewopharma, Lilly, Novartis, Pfizer, Corina Mogosan: None declared, Ziga Rotar Speakers bureau: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek, Janssen, Consultant of: Abbvie, Novartis, MSD, Medis, Biogen, Eli Lilly, Pfizer, Sanofi, Lek, Janssen, Matija Tomsic Speakers bureau: Abbvie, Amgen, Biogen, Eli Lilly, Janssen, Medis, MSD, Novartis, Pfizer, Sanofi, Sandoz-Lek, Consultant of: Abbvie, Amgen, Biogen, Eli Lilly, Janssen, Medis, MSD, Novartis, Pfizer, Sanofi, Sandoz-Lek, Björn Gudbjornsson Speakers bureau: Amgen, Novartis, Consultant of: Amgen, Novartis, Arni Jon Geirsson: None declared, Pasoon Hellamand Grant/research support from: Novartis, Marleen G.H. van de Sande Speakers bureau: Eli Lilly, Novartis, UCB, Janssen, Abbvie, Consultant of: Eli Lilly, Novartis, UCB, Janssen, Abbvie, Grant/research support from: Eli Lilly, Novartis, UCB, Janssen, Abbvie, Isabel Castrejon: None declared, Manuel Pombo-Suarez Consultant of: Abbvie, MSD, Roche, Bruno Frediani: None declared, Florenzo Iannone Speakers bureau: Abbvie, Amgen, AstraZeneca, BMS, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Consultant of: Abbvie, Amgen, AstraZeneca, BMS, Galapagos, Janssen, Lilly, MSD, Novartis, Pfizer, Roche, UCB, Lykke Midtbøll Ørnbjerg Grant/research support from: Novartis
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| 14. |
- Lauper, K, et al.
(författare)
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A SYSTEMATIC REVIEW TO INFORM THE EULAR 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. 123-124
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Comparative effectiveness studies using observational data are increasingly used. Despite their high potential for bias, there are no detailed recommendations on how these studies should best be analysed and reported in rheumatology.Objectives:To conduct a systematic literature review of comparative effectiveness research in rheumatology to inform the EULAR task force developing points to consider when analysing and reporting comparative effectiveness research with observational data.Methods:All original articles comparing drug effectiveness in longitudinal observational studies of ≥100 patients published in key rheumatology journals (Scientific Citation Index > 2) between 1.01.2008 and 25.03.2019 available in Ovid MEDLINE® were included. Titles and abstracts were screened by two reviewers for the first 1000 abstracts and independently checked to ensure sufficient agreement has been reached. The main information extracted included the types of outcomes used to assess effectiveness, and the types of analyses performed, focusing particularly on confounding and attrition.Results:9969 abstracts were screened, with 218 articles proceeding to full-text extraction (Figure 1), representing a number of rheumatic and musculoskeletal diseases. Agreement between the two reviewers for the first 1000 abstracts was 92.7% with a kappa of 0.6. The majority of the studies used several outcomes to evaluate effectiveness (Figure 2A). Most of the studies did not explain how they addressed missing data on the covariates (70%) (Figure 2B). When addressed (30%), 44% used complete case analysis and 10% last observation carried forward (LOCF). 25% of studies did not adjust for confounding factors and there was no clear correlation between the number of factors used to adjust and the number of participants in the studies. An important number of studies selected covariates using bivariate screening and/or stepwise selection. 86% of the studies did not acknowledge attrition (Figure 2C). When trying to correct for attrition (14%), 38% used non-responder (NR) imputation, 24% used LUNDEX1, a form of NR imputation, and 21% LOCF.Conclusion:Most of studies used multiple outcomes. However, the vast majority did not acknowledge missing data and attrition, and a quarter did not adjust for any confounding factors. Moreover, when attempting to account for attrition, several studies used methods which potentially increase bias (LOCF, complete case analysis, bivariate screening…). This systematic review confirms the need for the development of recommendations for the assessment and reporting of comparative drug effectiveness in observational data in rheumatology.References:[1]Kristensen et al. A&R. 2006 Feb;54(2):600-6.Acknowledgments:Support of the Standing Committee on Epidemiology and Health Services ResearchDisclosure of Interests:Kim Lauper: None declared, Joanna KEDRA: 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, 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, Sytske Anne Bergstra: None declared, Delphine Courvoisier: None declared
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| 15. |
- Lauper, K, et al.
(författare)
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Analysing and reporting of observational data: a systematic review informing the EULAR points to consider when analysing and reporting comparative effectiveness research with observational data in rheumatology
- 2021
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Ingår i: RMD open. - : BMJ. - 2056-5933. ; 7:3
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Tidskriftsartikel (refereegranskat)abstract
- To evaluate the analysis and reporting of comparative effectiveness research with observational data in rheumatology, informing European Alliance of Associations for Rheumatology points to consider.MethodsWe performed a systematic literature review searching Ovid MEDLINE for original articles comparing drug effectiveness in longitudinal observational studies, published in key rheumatology journals between 2008 and 2019. The extracted information focused on reporting and types of analyses. We evaluated if year of publication impacted results.ResultsFrom 9969 abstracts reviewed, 211 articles fulfilled the inclusion criteria. Ten per cent of studies did not adjust for confounding factors. Some studies did not explain how they chose covariates for adjustment (9%), used bivariate screening (21%) and/or stepwise selection procedures (18%). Only 33% studies reported the number of patients lost to follow-up and 25% acknowledged attrition (drop-out or treatment cessation). To account for attrition, studies used non-responder imputation, followed by last observation carried forward (LOCF) and complete case (CC) analyses. Most studies did not report the number of missing data on covariates (83%), and when addressed, 49% used CC and 11% LOCF. Date of publication did not influence the results.ConclusionMost studies did not acknowledge missing data and attrition, and a tenth did not adjust for any confounding factors. When attempting to account for them, several studies used methods which potentially increase bias (LOCF, CC analysis, bivariate screening…). This study shows that there is no improvement over the last decade, highlighting the need for recommendations for the assessment and reporting of comparative drug effectiveness in observational data in rheumatology.
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- Linde, L., et al.
(författare)
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Predictors of DAPSA28 remission in patients with psoriatic arthritis initiating a first TNF inhibitor: results from 13 European registries
- 2024
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Ingår i: Rheumatology. - 1462-0324. ; 63:3, s. 751-764
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Tidskriftsartikel (refereegranskat)abstract
- Objectives In bio-naive patients with PsA initiating a TNF inhibitor (TNFi), we aimed to identify baseline predictors of Disease Activity index for PsA in 28 joints (DAPSA28) remission (primary objective) and DAPSA28 moderate response at 6 months, as well as drug retention at 12 months across 13 European registries. Methods Baseline demographic and clinical characteristics were retrieved and the three outcomes investigated per registry and in pooled data, using logistic regression analyses on multiply imputed data. In the pooled cohort, selected predictors that were either consistently positive or negative across all three outcomes were defined as common predictors. Results In the pooled cohort (n = 13 369), 6-month proportions of remission, moderate response and 12-month drug retention were 25%, 34% and 63% in patients with available data (n = 6954, n = 5275 and n = 13 369, respectively). Five common baseline predictors of remission, moderate response and 12-month drug retention were identified across all three outcomes. The odds ratios (95% CIs) for DAPSA28 remission were: age, per year: 0.97 (0.96-0.98); disease duration, years (<2 years as reference): 2-3 years: 1.20 (0.89-1.60), 4-9 years: 1.42 (1.09-1.84), & GE;10 years: 1.66 (1.26-2.20); men vs women: 1.85 (1.54-2.23); CRP of >10 vs & LE;10 mg/l: 1.52 (1.22-1.89) and 1 mm increase in patient fatigue score: 0.99 (0.98-0.99). Conclusion Baseline predictors of remission, response and adherence to TNFi therapy were identified, of which five were common for all three outcomes, indicating that the predictors emerging from our pooled cohort may be considered generalizable from country level to disease level.
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- Michelsen, B., et al.
(författare)
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Drug retention, inactive disease and response rates in 1860 patients with axial spondyloarthritis initiating secukinumab treatment: routine care data from 13 registries in the EuroSpA collaboration
- 2020
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Ingår i: RMD open. - : BMJ. - 2056-5933. ; 6:3
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVES: To explore 6-month and 12-month secukinumab effectiveness in patients with axial spondyloarthritis (axSpA) overall, as well as across (1) number of previous biologic/targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs), (2) time since diagnosis and (3) different European registries. METHODS: Real-life data from 13 European registries participating in the European Spondyloarthritis Research Collaboration Network were pooled. Kaplan-Meier with log-rank test, Cox regression, χ² and logistic regression analyses were performed to assess 6-month and 12-month secukinumab retention, inactive disease/low-disease-activity states (Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) <2/<4, Ankylosing Spondylitis Disease Activity Score (ASDAS) <1.3/<2.1) and response rates (BASDAI50, Assessment of Spondyloarthritis International Society (ASAS) 20/40, ASDAS clinically important improvement (ASDAS-CII) and ASDAS major improvement (ASDAS-MI)). RESULTS: We included 1860 patients initiating secukinumab as part of routine care. Overall 6-month/12-month secukinumab retention rates were 82%/72%, with significant (p<0.001) differences between the registries (6-month: 70-93%, 12-month: 53-86%) and across number of previous b/tsDMARDs (b/tsDMARD-naïve: 90%/73%, 1 prior b/tsDMARD: 83%/73%, ≥2 prior b/tsDMARDs: 78%/66%). Overall 6-month/12-month BASDAI<4 were observed in 51%/51%, ASDAS<1.3 in 9%/11%, BASDAI50 in 53%/47%, ASAS40 in 28%/22%, ASDAS-CII in 49%/46% and ASDAS-MI in 25%/26% of the patients. All rates differed significantly across number of previous b/tsDMARDs, were numerically higher for b/tsDMARD-naïve patients and varied significantly across registries. Overall, time since diagnosis was not associated with secukinumab effectiveness. CONCLUSIONS: In this study of 1860 patients from 13 European countries, we present the first comprehensive real-life data on effectiveness of secukinumab in patients with axSpA. Overall, secukinumab retention rates after 6 and 12months of treatment were high. Secukinumab effectiveness was consistently better for bionaïve patients, independent of time since diagnosis and differed across the European countries. © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
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| 25. |
- Michelsen, B., et al.
(författare)
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Impact of discordance between patient's and evaluator's global assessment on treatment outcomes in 14 868 patients with spondyloarthritis
- 2020
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Ingår i: Rheumatology. - : Oxford University Press (OUP). - 1462-0324 .- 1462-0332. ; 59:9, s. 2455-2461
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Tidskriftsartikel (refereegranskat)abstract
- Objectives. To assess the impact of 'patient's minus evaluator's global assessment of disease activity' (Delta PEG) at treatment initiation on retention and remission rates of TNF inhibitors (TNFi) in psoriatic arthritis (PsA) and axial spondyloarthritis (axSpA) patients across Europe. Methods. Real-life data from PsA and axSpA patients starting their first TNFi from 11 countries in the European Spondyloarthritis Research Collaboration Network were pooled. Retention rates were compared by Kaplan-Meier analyses with log-rank test and by Cox regression, and remission rates by chi(2) test and by logistic regression across quartiles of baseline Delta PEG, separately in female and male PsA and axSpA patients. Results. We included 14 868 spondyloarthritis (5855 PsA, 9013 axSpA) patients. Baseline Delta PEG was negatively associated with 6/12/24-months' TNFi retention rates in female and male PsA and axSpA patients (P < 0.001), with 6/12/24-months' BASDAI < 2 (P <= 0.002) and ASDAS < 1.3 (P <= 0.005) in axSpA patients, and with DAS28CRP(4)<2.6 (P <= 0.04) and DAPSA28 <= 4 (P <= 0.01), but not DAS28CRP(3)<2.6 (P >= 0.13) in PsA patients, with few exceptions on remission rates. Retention and remission rates were overall lower in female than male patients. Conclusion. High baseline patient's compared with evaluator's global assessment was associated with lower 6/12/24-months' remission as well as retention rates of first TNFi in both PsA and axSpA patients. These results highlight the importance of discordance between patient's and evaluator's perspective on disease outcomes.
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