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| 2. |
- 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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| 3. |
- 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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| 4. |
- 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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| 5. |
- 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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| 6. |
- 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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