An Overview on Causes of Nonadherence in the Treatment of Rheumatoid Arthritis: Its Effect on Mortality and Ways to Improve Adherence

Chowdhury, Tutul; Dutta, Jui; Noel, Pharlin; Islam, Ratul; Gonzalez-Peltier, Gael; Azad, Samzorna; Shankar, Malavika; Rayapureddy, Aditya Keerthi; Roy, Padmaja Deb; Gousy, Nicole; Hassan, Khondokar N

doi:10.7759/cureus.24520

Cited by 5 publications

(3 citation statements)

References 39 publications

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“…RA leads to irreversible damage of the synovial lining of joints and significantly affects the life quality [ 18 ]. Over the past few decades, despite advances in therapeutic strategies, the prevalence of RA has increased [ 19 ].…”

Section: Discussionmentioning

confidence: 99%

Identification and validation of metabolism-related genes signature and immune infiltration landscape of rheumatoid arthritis based on machine learning

Guo

Wang

et al. 2023

Aging

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Rheumatoid arthritis (RA) causes irreversible joint damage, but the pathogenesis is unknown. Therefore, it is crucial to identify diagnostic biomarkers of RA metabolism-related genes (MRGs). This study obtained transcriptome data from healthy individuals (HC) and RA patients from the GEO database. Weighted gene correlation network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO), and random forest (RF) algorithms were adopted to identify the diagnostic feature biomarker for RA. In addition, biomarkers were verified by qRT-PCR and Western blot analysis. We established a mouse model of collagen-induced arthritis (CIA), which was confirmed by HE staining and bone structure micro-CT analysis, and then further verified the biomarkers by immunofluorescence. In vitro NMR analysis was used to analyze and identify possible metabolites. The correlation of diagnostic feature biomarkers and immune cells was performed using the Spearman-rank correlation algorithm. In this study, a total of 434 DE-MRGs were identified. GO and KEGG enrichment analysis indicated that the DE-MRGs were significantly enriched in small molecules, catabolic process, purine metabolism, carbon metabolism, and inositol phosphate metabolism. AKR1C3, MCEE, POLE4, and PFKM were identified through WGCNA, LASSO, and RF algorithms. The nomogram result should have a significant diagnostic capacity of four biomarkers in RA. Immune infiltration landscape analysis revealed a significant difference in immune cells between HC and RA groups. Our findings suggest that AKR1C3, MCEE, POLE4, and PFKM were identified as potential diagnostic feature biomarkers associated with RA’s immune cell infiltrations, providing a new perspective for future research and clinical management of RA.

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Section: Discussionmentioning

confidence: 99%

Identification and validation of metabolism-related genes signature and immune infiltration landscape of rheumatoid arthritis based on machine learning

Guo

Wang

et al. 2023

Aging

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“…It has been reported that over half (54.8%) of patients with AS experience sleep disturbance [ 20 , 21 ], while the prevalence of sleep disturbance in patients with RA has been estimated at 60–80% compared with 10–30% in the general population [ 22 ]. While management of the underlying disease, specifically pain, has the potential to improve sleep outcomes for some patients, pain may not always be considered or well-treated in RA and axSpA for a variety of reasons, including misdiagnosis and delayed diagnosis, and therapy-related, physician-related, and patient-related factors [ 2 , 47 , 48 ]. Furthermore, several studies have shown that pain persists in many people with RA, despite commencing new treatments for their disease including tumor necrosis factor-α inhibitors [ 13 ].…”

Section: Discussionmentioning

confidence: 99%

A concept elicitation study to understand the relationship between sleep and pain in rheumatoid arthritis and axial spondyloarthritis

Raymond,

Chen,

Bracher

et al. 2023

Qual Life Res

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Purpose This qualitative study (GSK study: 213635) was designed to better understand sleep disturbance as experienced by individuals with rheumatoid arthritis (RA) or axial spondyloarthritis (axSpA), and the relationship between sleep disturbance and pain and other aspects of the disease and disease activity. Methods Sixty-minute, one-on-one, concept elicitation interviews were conducted with 30 participants (15 with RA and 15 with axSpA) from the US. Interviews were audio-recorded and transcribed verbatim. Interview transcripts were coded and analyzed to explore themes related to pain and sleep disturbance, and relationships among those themes. Results Pain was a prominent driver of sleep disturbance; 12 participants with RA (80%) and 14 with axSpA (93%) reported that pain impacted their ability to fall asleep, while all 15 with RA (100%) and 14 with axSpA (93%) reported that pain impacted their ability to stay asleep. Two-thirds of participants with RA (67%) or axSpA (60%) described a bi-directional relationship, whereby pain worsened sleep disturbance and sleep disturbance further aggravated pain. Factors other than pain, such as fatigue and emotional health, were also reported as important contributors to sleep disturbance (RA: n = 12/15, 80%; axSpA: n = 14/15, 93%). Participants with RA or axSpA described complex interconnections between fatigue, emotional health, pain, and sleep, often labeling these relationships as “vicious cycles”. Notably, half of all participants reported sleep disturbance occurring without pain or other understood causes. Conclusion These perspectives collected from people with RA or axSpA suggest that reducing sleep disruption directly may offer clinically relevant benefits.

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“…Forgetfulness can arise from various factors such as managing multiple commitments and the responsibility of taking several medications. Handling numerous medication schedules can amplify the complexity of personal healthcare management, potentially leading to oversight or missed doses [ 17 ]. Therefore, CPAMS was designed to inform the patient 1 week prior to the next injection.…”

Section: Discussionmentioning

confidence: 99%

Improvement of proportion of days covered for denosumab under implementation of clinical pharmacist adherence management system: normal and COVID-19 period

Yang,

He,

Yuan

2023

Osteoporos Int

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Summary We established a clinical pharmacist adherence management system (CPAMS) led by clinical pharmacists to examine whether denosumab adherence could be improved. The results showed that CPAMS could effectively improve adherence to denosumab and the treatment of osteoporosis. However, this effect weakened during the spread of infectious diseases such as COVID-19. Purpose Denosumab is currently one of the drugs that can effectively reduce the risk of clinical fracture. However, as a drug requiring long-term subcutaneous injection, patient adherence to denosumab is the most important factor affecting its therapeutic efficacy. Therefore, we established a clinical pharmacist adherence management system (CPAMS) led by clinical pharmacists and examined whether denosumab adherence could be improved. Methods Data were collected from patients receiving denosumab in our hospital between March 2021 and May 2022. The patients who participated in the CPAMS were in the intervention group, and the rest were in the control group. We analysed the proportion of days covered (PDC) value of denosumab, distribution of subsequent visits, and proportion of patients who continued participating during the normal and coronavirus (COVID-19) periods. Results Eighty-five patients were enrolled in this retrospective study: 32 in the intervention group and 53 in the control group. The PDC values were significantly higher in the intervention group (0.9875, 0.9025–1) than in the control group (0.5, 0.5–0.5) after 1 year. The subsequent visit rate in the intervention group was 93.80%. However, none of the patients in the control group returned. In the intervention group, the ratio of timely to delayed subsequent visits was 11:19. After the COVID-19 pandemic, the PDC value of the intervention group (0.957, 0.5–1) was lower than that before COVID-19, and the ratio of timely to delayed subsequent visits was 9:13. Conclusions Clinical pharmacist-led CPAMS could effectively improve adherence to denosumab and the treatment of osteoporosis. Supplementary Information The online version contains supplementary material available at 10.1007/s00198-023-06933-1.

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An Overview on Causes of Nonadherence in the Treatment of Rheumatoid Arthritis: Its Effect on Mortality and Ways to Improve Adherence

Cited by 5 publications

References 39 publications

Identification and validation of metabolism-related genes signature and immune infiltration landscape of rheumatoid arthritis based on machine learning

Identification and validation of metabolism-related genes signature and immune infiltration landscape of rheumatoid arthritis based on machine learning

A concept elicitation study to understand the relationship between sleep and pain in rheumatoid arthritis and axial spondyloarthritis

Improvement of proportion of days covered for denosumab under implementation of clinical pharmacist adherence management system: normal and COVID-19 period

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