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- 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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- Herrera-Rivero, Marisol, et al.
(författare)
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Exploring the genetics of lithium response in bipolar disorders.
- 2023
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Ingår i: Research square.
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N=2,064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II.We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism.Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II.
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- 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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- Seidler, Y, et al.
(författare)
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KNOWING WHAT TO DO WITH THE DATA - A QUALITATIVE STUDY ON CHALLENGES OF USING SMARTPHONE-BASED EPROS IN RHEUMATOID ARTHRITIS
- 2022
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Ingår i: ANNALS OF THE RHEUMATIC DISEASES. - : BMJ. - 0003-4967 .- 1468-2060. ; 81, s. 1081-1081
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Using patient-reported outcomes (PROs) has a long tradition in rheumatology, and PRO measurement is included in many composite indices evaluating disease progression and treatment response [1]. However, little is known about patients´ and health professionals´ (HPs) perceptions of using digitally collected PROs, the so-called ePROs, with a personal smartphone app.ObjectivesTo identify main challenges in utilising ePROs for management and treatment of rheumatoid arthritis from patients’ and HPs’ perspectives.MethodsWe interviewed 25 people with rheumatoid arthritis (RA) and 17 HPs (nurses, rheumatologists, and physiotherapists) from Austria and Denmark. We used the RheumaBuddy app as a practical example to illustrate the digital data collection and the feedback that patients would get from entering their self-reported outcomes. Interviews were recorded and transcribed. We applied a qualitative thematic analysis to identify major themes using a procedure of rigorous coding. Analysis was done by two researchers, and conflicts were solved by consensus. Ethical approval was obtained in both countries.ResultsThree main themes emerged: 1) Being simple yet comprehensive; 2) Resources to interpret, use and act upon the collected data; and 3) Being reminded of the disease. Within the first theme, many valued the intuitiveness and simplicity of ePROs, especially when used as a monitoring tool in between clinical visits. HPs were concerned about not to overwhelm the patients with too many questions. On the other hand, the short ePROs asked in the app were not comprehensive enough to capture psychosocial and lifestyle aspects of the disease which were considered important both by patients and HPs. Within the second theme, patients and HPs expressed that ePROs could be the basis for shared decision making. Nevertheless, some patients had clearer ideas on making use of the feedback they could get from their self-reported data than the others. Participants from Denmark, who experienced a higher level of digital health maturity in official institutions, expressed more proactive use of the data than participants from Austria who were on average younger than their Danish counterparts. One patient in Austria even asserted having no idea what to do with the collected data but believed that the “doctor will make good use of it”. HPs in both countries, however, indicated that they needed more resources, skills, and time to make sense of the ePRO data and act accordingly. Under the third theme, patients considered the collection of ePROs to be very important when pain and disease activity were high. HPs, on the other hand, were more concerned that the regular collection of ePROs might constantly remind patients that they are living with the disease.ConclusionThe potential adoption of ePROs in practice depends on both patients and HPs’ motivations and ideas to use the feedback they would get from the collected data. This might be influenced by the level of digital health maturity of a country, as well as available resources. In addition, ePROs need to be intuitive and simple, but at the same time comprehensive and reliable enough so that they can be used for shared decision making. Challenges remain for the ePROs to be used as supporting and empowering tools, and not as reminders of the disease and pain.Table 1.Demographic data of the participants (N=42)DemographicAustriaDenmarkTotalDataPatientHPPatientHPPatientHPN14101172517Women (%)10(71)6(60)7(64)5(71)17(68)11(65)Men (%)4(29)4(40)4(36)2(29)8(32)6(35)AgeMean (Range)54(30-76)41(29-63)65(37-77)47(31-59)60(30-77)44(29-63)References[1]T Stamm, I Parodis, and P Studenic. Patient-reported outcomes with anifrolumab in patients with systemic lupus erythematosus, Lancet Rheumatol, (2022), in Press.AcknowledgementsWe would like to express our particular thank you to all those who have taken part in the interview study and for their valuable inputs.Disclosure of InterestsYuki Seidler: None declared, Tanja Schjødt Jørgensen Speakers bureau: AbbVie, Pfizer, Roche, Novartis, UCB, Biogen and Eli Lilly., Consultant of: AbbVie, Pfizer, Roche, Novartis, UCB, Biogen and Eli Lilly, Paul Studenic: None declared, Helga Radner Speakers bureau: Gilead, Merck Sharp, Pfizer, Abbvie, Consultant of: Gilead, Merck Sharp, Pfizer, Abbvie, Thomas Nygaard: None declared, Nadine Weibrecht: None declared, Nikolas Popper Speakers bureau: Roche, Consultant of: dwh GmbH (as CSO), Lars Erik Kristensen Speakers bureau: Pfizer, AbbVie, Amgen, UCB, Gilead, Biogen, BMS, MSD, Novartis, Eli Lilly, and Janssen pharmaceuticals, Consultant of: Pfizer, AbbVie, Amgen, UCB, Gilead, Biogen, BMS, MSD, Novartis, Eli Lilly, and Janssen pharmaceuticals, Grant/research support from: IIT research grants from Novo, UCB, Eli Lilly; Novartis and Abbvie, Tanita-Christina Wilhelmer: None declared, James Rickmann: None declared, Erika Mosor: None declared, Valentin Ritschl: None declared, Tanja Stamm Speakers bureau: AbbVie, Novartis, Roche, Sanofi, and Takeda., Consultant of: AbbVie and Sanofi Genzyme., Grant/research support from: AbbVie and Roche.
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- Herrera-Rivero, Marisol, et al.
(författare)
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Immunogenetics of lithium response and psychiatric phenotypes in patients with bipolar disorder.
- 2023
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Ingår i: Research square.
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- The link between bipolar disorder (BP) and immune dysfunction remains controversial. While epidemiological studies have long suggested an association, recent research has found only limited evidence of such a relationship. To clarify this, we investigated the contributions of immune-relevant genetic factors to the response to lithium (Li) treatment and the clinical presentation of BP. First, we assessed the association of a large collection of immune-related genes (4,925) with Li response, defined by the Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale), and clinical characteristics in patients with BP from the International Consortium on Lithium Genetics (ConLi+Gen, N = 2,374). Second, we calculated here previously published polygenic scores (PGSs) for immune-related traits and evaluated their associations with Li response and clinical features. We found several genes associated with Li response at p < 1×10- 4 values, including HAS3, CNTNAP5 and NFIB. Network and functional enrichment analyses uncovered an overrepresentation of pathways involved in cell adhesion and intercellular communication, which appear to converge on the well-known Li-induced inhibition of GSK-3β. We also found various genes associated with BP's age-at-onset, number of mood episodes, and presence of psychosis, substance abuse and/or suicidal ideation at the exploratory threshold. These included RTN4, XKR4, NRXN1, NRG1/3 and GRK5. Additionally, PGS analyses suggested serum FAS, ECP, TRANCE and cytokine ligands, amongst others, might represent potential circulating biomarkers of Li response and clinical presentation. Taken together, our results support the notion of a relatively weak association between immunity and clinically relevant features of BP at the genetic level.
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