| 1. |
- Emamikia, S., et al.
(författare)
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CAN WE ENHANCE ADHERENCE TO MEDICATIONS IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS? RESULTS FROM A QUALITATIVE STUDY
- 2022
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Ingår i: Annals of the Rheumatic Diseases. - : HighWire Press. - 0003-4967 .- 1468-2060. ; 81:Suppl. 1, s. 439-439
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Medication non-adherence is common among patients with systemic lupus erythematosus (SLE) [1] and may lead to poor clinical outcomes [2,3].ObjectivesOur aim was to identify influenceable contributors to medication non-adherence to suggest interventions that could increase adherence.MethodsPatients with SLE from two Swedish tertiary referral centres (N=205) participated in a survey assessing self-reported adherence to medications. Medication adherence was self-reported and measured using the generic instrument Medication Adherence Self-Report Inventory (MASRI) and the rheumatic disease-specific instrument Compliance Questionnaire Rheumatology (CQR). Responses were used to select patients for qualitative interviews (N=15). Verbatim interview transcripts were analysed by two researchers using content analysis methodology.ResultsThe mean age of the interviewees was 39 years, 87% were women, and their mean SLE duration was 11.6 years. Patients’ medications and adherence levels are detailed in Table 1. We categorised reasons for non-adherence thematically into (i) patient-related e.g., unintentional non-adherence due to forgetfulness or intentional non-adherence due to disbelief in medications, (ii) healthcare-related e.g., untrustworthy relationship with the treating physician, authority fear, and poor information about the prescribed medications or the disease, (iii) medication-related e.g., fear of side-effects, and (iv) disease-related reasons e.g., lacking acceptance of a chronic illness or perceived disease quiescence. Interventions identified that healthcare could implement to improve patients’ adherence to medications included (i) increased communication between healthcare professionals and patients, (ii) patient education, (iii) accessible healthcare, preferably with the same personnel, (iv) smooth transition from paediatric to adult care, (v) regularity in addressing adherence to medications, (vi) psychological support, and (vii) involvement of family members or people who are close to the patient.Table 1.Characteristics of the fifteen interviewees.PatientPrescribed medicationsOverall medication adherence according to:Intentional non-adherence (Y/N)MASRI (0–100%)CQR (0–100%)Direct question (Y/N) *1PRED9661NYHCQ96AZA962PRED10077YNAHCQ100MTX (pills)1003PRED10081YNA4HCQ9058NY5HCQ10054NY6PRED7065NNHCQ70AZA697PRED6747NYHCQ50AZA208HCQ8872NN9PRED9574NYHCQ96MMF RTX (iv)9910PRED10066NNHCQ100AZA BEL (sc)8011PRED9654NNHCQ100MMF RTX9812PRED8958NNHCQ9213PRED10084YNACYS10014HCQ10074YNAMTX (pills)10015PRED9067NNHCQ90MMF801 MASRI: Medications Adherence Self Report Inventory; CQR: Compliance Questionnaire Rheumatology; F/M: female/male; Y/N: yes/no; NA: not applicable; iv: intravenous; sc: subcutaneous; PRED: prednisolone; HCQ: hydroxychloroquine; AZA: azathioprine; MTX: methotrexate; MMF: mycophenolate mofetil; RTX: rituximab; BEL: belimumab; CYS: cyclosporine; * Y= Adherence assent to direct question; N= Non-adherence assent to direct question.ConclusionThe reasons for medication non-adherence are complex and multifaceted. From the patients’ perspective, multiple different strategies could be implemented in healthcare with the goal of improving adherence, including increased communication, patient education and psychological support.References[1]Mehat, P et al. Arthritis Care & Research 2017, 69, 1706-1713.[2]Feldman, C.H. et al. Arthritis Care & Research 2015, 67, 1712-1721.[3]Julian, L.J. et al. Arthritis and rheumatism 2009, 61, 240-246.AcknowledgementsAll authors would like to express our gratitude to the individuals who participated in the interviews and shared their thoughts, views, and opinions.Disclosure of InterestsSharzad Emamikia: None declared, Cidem Gentline: None declared, Yvonne Enman: None declared, Ioannis Parodis Grant/research support from: Amgen, AstraZeneca, Aurinia Pharmaceuticals, Elli Lilly and Company, Gilead Sciences, GlaxoSmithKline, Janssen Pharmaceuticals, Novartis and F. Hoffmann-La Roche AG.
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| 3. |
- Gomez, A, et al.
(författare)
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Adverse Health-Related Quality of Life Outcome Despite Adequate Clinical Response to Treatment in Systemic Lupus Erythematosus
- 2021
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Ingår i: Frontiers in medicine. - : Frontiers Media SA. - 2296-858X. ; 8, s. 651249-
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To determine the prevalence of adverse health-related quality of life (HRQoL) outcomes in patients with SLE who achieved an adequate clinical response after a 52-week long standard therapy plus belimumab or placebo, and identify contributing factors.Methods: We included patients who met the primary endpoint of the BLISS-52 (NCT00424476) and BLISS-76 (NCT00410384) trials, i.e., SLE Responder Index 4 (total population: N = 760/1,684; placebo: N = 217/562; belimumab 1 mg/kg: N = 258/559; belimumab 10 mg/kg: N = 285/563). Adverse HRQoL outcomes were defined as SF-36 scale scores ≤ the 5th percentile derived from age- and sex-matched population-based norms, and FACIT-Fatigue scores <30. We investigated factors associated with adverse HRQoL outcomes using logistic regression analysis.Results: We found clinically important diminutions of HRQoL in SLE patients compared with matched norms and high frequencies of adverse HRQoL outcomes, the highest in SF-36 general health (29.1%), followed by FACIT-Fatigue (25.8%) and SF-36 physical functioning (25.4%). Overall, frequencies were higher with increasing age. Black/African American and White/Caucasian patients reported higher frequencies than Asians and Indigenous Americans, while Hispanics experienced adverse HRQoL outcome less frequently than non-Hispanics. Established organ damage was associated with adverse physical but not mental HRQoL outcomes; particularly, damage in the cardiovascular (OR: 2.12; 95% CI: 1.07–4.21; P = 0.032) and musculoskeletal (OR: 1.41; 95% CI: 1.01–1.96; P = 0.041) domains was associated with adverse SF-36 physical component summary. Disease activity showed no impact on HRQoL outcomes. In multivariable logistic regression analysis, addition of belimumab to standard therapy was associated with lower frequencies of adverse SF-36 physical functioning (OR: 0.59; 95% CI: 0.39–0.91; P = 0.016) and FACIT-F (OR: 0.53; 95% CI: 0.34–0.81; P = 0.004).Conclusions: Despite adequate clinical response to standard therapy plus belimumab or placebo, a substantial proportion of SLE patients still reported adverse HRQoL outcomes. While no impact was documented for disease activity, established organ damage contributed to adverse outcome within physical HRQoL aspects and add-on belimumab was shown to be protective against adverse physical functioning and severe fatigue.
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| 4. |
- Gomez, A, et al.
(författare)
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ASSOCIATION OF OVERWEIGHT/OBESITY WITH IMPAIRED HEALTH-RELATED QUALITY OF LIFE IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS
- 2020
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Ingår i: ANNALS OF THE RHEUMATIC DISEASES. - : BMJ. - 0003-4967 .- 1468-2060. ; 79, s. 664-665
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Patients with systemic lupus erythematosus (SLE) experience a considerably impaired health-related quality of life (HRQoL) compared with the general population. Previous literature has implied an association between high body mass index (BMI) and HRQoL diminutions. However, data are scarce and further exploration in large study populations and, importantly, with regard to the clinical significance of this association is needed.Objectives:The aim of this study was to determine whether overweight and/or obesity were associated with impaired physical and/or mental HRQoL aspects in the SLE population of two large clinical trials.Methods:We utilised pooled baseline data from the BLISS-52 (NCT00424476) and BLISS-76 (NCT00410384) clinical trials of belimumab (N=1684). Access to data was granted by GlaxoSmithKline. The patients were stratified into four groups based on their body mass index (BMI), according to WHO guidelines. We conducted comparisons between non-overweight versus overweight, and non-obese versus obese SLE patients. HRQoL was self-reported using the Medical Outcomes Study (MOS) short form 36 (SF-36) health survey, the functional assessment of chronic illness therapy (FACIT)-Fatigue scale and the three-level EuroQol- 5 Dimension (EQ-5D) questionnaire. We explored whether the differences in scores were clinically meaningful using previously determined thresholds for minimal clinically important differences (MCIDs). The non-parametric Mann-Whitney U test was used for comparisons between different BMI groups. Linear regression analysis was next applied to test independence in multivariable models, adjusting for age, sex, ethnicity, disease duration, disease activity, organ damage and standard of care treatment.Results:Forty-four per cent (44%) of the patients had a BMI score over the normal range, and 18% were obese. The overweight group performed worse than the non-overweight with regard to FACIT-Fatigue scores (mean ± standard deviation: 27.7 ± 12.1 vs 32.0 ± 11.3; P<0.001), EQ-5D score (0.70 ± 0.19 vs 0.76 ± 0.18; P<0.001) and all SF-36 subscales and component summaries. The differences were greater than the MCIDs for physical component summary (PCS) scores (36.9 ± 9.3 vs 40.8 ± 9.6; P<0.001), physical functioning (53.3 ± 25.1 vs 63.6 ± 25-1; P<0.001), role physical (48.0 ± 27.1 vs 55.6 ± 26.9; P<0.001), bodily pain (43.8 ± 22.4 vs 52.5 ± 25.1; P<0.001), vitality (39.6 ± 21.7 vs 46.6 ± 21.3; P<0.001), and social functioning scores (55.8 ± 25.2 vs 62.6 ± 25.2; P<0.001). Likewise, obese patients reported worse FACIT-Fatigue scores (25.7 ± 11.9 vs 31.1 ± 11.6; P<0.001), EQ-5D scores (0.68 ± 0.20 vs 0.75 ± 0.18; P<0.001) and clinically important diminutions of HRQoL in all SF-36 items, except for the mental component summary (MCS), role emotional and mental health.In multivariable linear regression analysis, the overweight and obese group showed worse PCS scores (standardised coefficient: β=-0.09; P<0.001 and β=-0.13; P<0.001, respectively) and FACIT-Fatigue scores (β=-0.11; P<0.001 and β=-0.10; P<0.001, respectively), and overweight patients had significantly impaired MCS scores (β=-0.05; P=0.039), irrespective of other factors. High disease activity and organ damage were associated with impaired HRQoL in all aspects, while Asian patients reported better PCS scores (and β=0.29; P=0.007) and FACIT-Fatigue scores (β=0.33; P=0.002).Conclusion:BMI above normal was highly associated with HRQoL impairment, especially in physical aspects. Further survey to examine causality is warranted to support structured weight control strategies as an intervention towards a more favourable HRQoL.Disclosure of Interests:None declared
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| 5. |
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| 6. |
- Gomez, A, et al.
(författare)
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Use of Antimalarial Agents is Associated with Favourable Physical Functioning in Patients with Systemic Lupus Erythematosus
- 2020
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Ingår i: Journal of clinical medicine. - : MDPI AG. - 2077-0383. ; 9:6
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Tidskriftsartikel (refereegranskat)abstract
- Impaired health-related quality of life (HRQoL) is a major problem in patients with systemic lupus erythematosus (SLE). Antimalarial agents (AMA) are the cornerstone of SLE therapy, but data on their impact on HRQoL are scarce. We investigated this impact using baseline data from the BLISS-52 (NCT00424476) and BLISS-76 (NCT00410384) trials (n = 1684). HRQoL was self-reported using the Medical Outcomes Study short-form 36 (SF-36), functional assessment of chronic illness therapy (FACIT)-Fatigue and 3-level EuroQoL 5-Dimension (EQ-5D) questionnaires. Patients on AMA (n = 1098/1684) performed better with regard to SF-36 physical component summary, physical functioning, role physical, bodily pain, FACIT-Fatigue, EQ-5D utility index and EQ-5D visual analogue scale scores. The difference in SF-36 physical functioning (mean ± standard deviation (SD): 61.1 ± 24.9 versus 55.0 ± 26.5; p < 0.001) exceeded the minimal clinically important difference (≥5.0). This association remained significant after adjustment for potential confounding factors in linear regression models (standardised coefficient, β = 0.07; p = 0.002). Greater proportions of AMA users than non-users reported no problems in the mobility, self-care, usual activities and anxiety/depression EQ-5D dimensions. AMA use was particularly associated with favourable HRQoL in physical aspects among patients with active mucocutaneous and musculoskeletal disease, and mental aspects among patients with active renal SLE. These results provide support in motivating adherence to AMA therapy. Exploration of causality in the relationship between AMA use and favourable HRQoL in SLE has merit.
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| 7. |
- Klareskog, Lars, et al.
(författare)
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Vad är reumatologi?
- 2017. - 3
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Ingår i: Reumatologi. - 9789144115108 ; , s. 21-24
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Bokkapitel (populärvet., debatt m.m.)
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| 9. |
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| 10. |
- Lindblom, J., et al.
(författare)
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TRANSCRIPTOME PROFILING AND AUTOIMMUNITY-RELATED SEROLOGICAL MARKERS IDENTIFY TP53 AND C3AR AS DRUG TARGETS IN NEUROPSYCHIATRIC SYSTEMIC LUPUS ERYTHEMATOSUS
- 2022
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Ingår i: Annals of the Rheumatic Diseases. - : HighWire Press. - 0003-4967 .- 1468-2060. ; 81:Suppl. 1, s. 326-326
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Involvement of the nervous system is a common but poorly understood manifestation of systemic lupus erythematosus (SLE), termed neuropsychiatric SLE (NPSLE). Although studies have reported varying prevalence estimates [1], NPSLE affects at least 20% of patients with SLE within the first years of the disease course [2]. The management of neuropsychiatric SLE (NPSLE) is poorly optimised and specific treatment is lacking.ObjectivesThe aim of this study was to investigate expression quantitative trait loci (eQTLs), the transcriptome, and autoimmunity-related cytokines and autoantibodies in patients with central nervous system (CNS) lupus to gain insights into underlying genetics and biologic mechanisms towards identification of novel drug targets.MethodsWe analysed differentially expressed genes (DEGs), pathways and their druggability via the Drug Gene Interaction database (DGIdb) [3] in active CNS lupus (n=26) versus healthy controls (HC; n=497), and eQTLs in active or past CNS lupus (n=53), based on validated (identified in two independent SLE populations) DEGs in SLE (n=350) versus HC (n=497), in whole blood collected within the frame of the European PRECISESADS consortium [4]. CNS lupus was defined according to SLE Disease Activity Index 2000 (SLEDAI-2K) [5] CNS items or by CNS manifestations such as chorea, acute confusional state, transverse myelitis, aseptic meningitis, and optic neuritis in the absence of predisposing conditions unrelated to SLE. Genome-wide RNA-sequencing and genotyping was previously performed by Illumina assays, and serum levels of 17 cytokines were analysed using a Luminex assay and ELISA [4].ResultsAmong 5631 significant and validated DEGs in active CNS patients compared with HC, 1922 unique DEGs were tagged to 21 and 176 significant KEGG [6] and Reactome [7] pathways, respectively. Pathways included “Interferon signalling”, “TNF signalling” and “Toll-like Receptor Cascades”. The pathways included 29 of 59 DEGs with a |fold change (FC)| > 1.5, 6 genes from 14 significant cis-eQTLs and 10 genes from 22 trans-eQTLs, and 2 genes from 8 cytokines that differed significantly between active CNS lupus and HC. These genes could be targeted by 496 different drugs, with the Bruton tyrosine kinase (BTK) inhibitor ibrutinib and the anti-CD20 B cell depleting monoclonal rituximab with ability to interfere with tumour protein P53 (TP53) activity, and a complement C3a Receptor (C3aR) antagonist being of particular interest.ConclusionIntegrated multilevel omics analysis revealed a set of enriched pathways of potential interest for future drug investigation in CNS lupus, including BTK and C3aR inhibition, and B cell depletion.References[1]Unterman A, Nolte JE, Boaz M, Abady M, Shoenfeld Y, Zandman-Goddard G. Neuropsychiatric syndromes in systemic lupus erythematosus: a meta-analysis. Semin Arthritis Rheum. 2011 Aug; 41(1):1-11[2]Hanly JG, Urowitz MB, Su L, Bae SC, Gordon C, Wallace DJ, et al. Prospective analysis of neuropsychiatric events in an international disease inception cohort of patients with systemic lupus erythematosus. Ann Rheum Dis. 2010 Mar; 69(3):529-535[3]Wagner AH, Coffman AC, Ainscough BJ, Spies NC, Skidmore ZL, Campbell KM, et al. DGIdb 2.0: mining clinically relevant drug-gene interactions. Nucleic Acids Res. 2016 Jan 4; 44(D1):D1036-1044[4]Barturen G, Babaei S, Català-Moll F, Martínez-Bueno M, Makowska Z, Martorell-Marugán J, et al. Integrative Analysis Reveals a Molecular Stratification of Systemic Autoimmune Diseases. Arthritis Rheumatol. 2021 Jun; 73(6):1073-1085[5]Gladman DD, Ibanez D, Urowitz MB. Systemic lupus erythematosus disease activity index 2000. J Rheumatol. 2002 Feb; 29(2):288-291[6]Kanehisa M, Furumichi M, Tanabe M, Sato Y, Morishima K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. 2017 Jan 4; 45(D1):D353-d361[7]Jassal B, Matthews L, Viteri G, Gong C, Lorente P, Fabregat A, et al. The reactome pathway knowledgebase. Nucleic Acids Res. 2020 Jan 8; 48(D1):D498-d503AcknowledgementsThe PRECISESADS clinical consortiumDisclosure of InterestsNone declared
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