Objectives
To evaluate the prevalence of self-perceived depression and anxiety in patients with systemic lupus erythematosus (SLE) and to explore associated factors.
Methods
Cross-sectional study of ...unselected patients with SLE (ACR-97 criteria) and controls with chronic inflammatory rheumatic diseases. Both completed the Hospital Anxiety and Depression Scale (HADS). Demographic and clinical characteristics, comorbidity, and treatments were collected, and a multivariate analysis was performed to explore factors associated with depression and anxiety in SLE.
Results
The study population comprised 172 patients and 215 controls. Women accounted for 93% of the patients with SLE. Fibromyalgia was recorded in 12.8% and a history of depression in 17%. According to HADS, 37.2% fulfilled the diagnostic criteria for depression and 58.7% those for anxiety; prevalence was similar in the controls (32.6% and 55.1%, respectively). Up to a third of patients with self-perceived depression were not receiving antidepressants. There was no concordance between a previous history of depression and current depression. In the multivariate model, current depression was associated with single marital status (OR 2.69; 95% CI: 1.17–6.42; p = .022), fibromyalgia (7.69; 2.35–30.72; p = .001), smoking (3.12; 1.24–8.07; p = .016), severity of SLE (0.76; 0.6–0.94; p = .016), and organ damage (1.27; 1.01–1.61; p = .042). Current anxiety was only associated with fibromyalgia (3.97; 1.21–17.98; p = .036).
Conclusions
Depression and anxiety are most likely underdiagnosed in SLE. Prevalence appears to be similar to that of other chronic inflammatory rheumatic diseases. Anxiety is associated with fibromyalgia, while depression is also associated with single marital status, smoking, organ damage, and severity of SLE.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, OILJ, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Aim
To assess the golimumab retention rate during up to 8 years of follow up, and any associated factors.
Methods
Retrospective analysis of the BIOBADASER (Spanish registry of biological drugs) ...database, assessing all adults who had ever started golimumab >6 months before the analysis for an approved indication (rheumatoid arthritis RA, axial spondyloarthritis SpA or psoriatic arthritis PsA).
Results
Among 885 patients (RA 267, axial SpA 370, PsA 248) receiving 944 cycles of golimumab, the retention rate of golimumab was 71.1% (95% confidence interval: 68.0–73.9) at year 1% and 37.7% (95% CI: 33.3–42.1) at year 7 and at year 8. Retention was higher when golimumab was used as the first biological drug (81.7% at year 1, 49.9% at year 7, p < 0.001). In Cox regression analysis, factors associated with golimumab retention included use as first‐line therapy (hazard ratio HR for discontinuation 1.52 for second‐ and 1.79 for third/later‐line vs. first‐line), use in axial SpA or PsA rather than RA (HR for axial SpA vs. RA 0.59, for PsA vs. Rheumatoid arthritis 0.67), and treatment with concomitant methotrexate (HR 0.67). Factors associated with golimumab discontinuation were corticosteroid use (HR 1.46) and disease activity above median (HR 1.29) at golimumab initiation.
Conclusion
Based on this retrospective analysis of the BIOBADASER registry, nearly two‐fifths (37.7%) of adult rheumatology patients initiating golimumab will remain on treatment for 8 years, with a higher probability of retention in axial SpA or PsA indications and when golimumab is used as first biologic.
The better understanding of the safety of biologic DMARDs (bDMARDs), as well as the emergence of new bDMARDs against different therapeutic targets and biosimilars have likely influenced the use ...patterns of these compounds over time. The aim of this study is to assess changes in demographic characteristics, disease activity and treatment patterns in patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), or ankylosing spondylitis (AS) who started a first- or second-line biologic between 2007 and mid-2020. Patients diagnosed with RA, PsA or AS included in the BIOBADASER registry from January 2007 to July 2020 were included. According to the start date of a first- or second-line biologic therapy, patients were stratified into four time periods: 2007-2009; 2010-2013; 2014-2017; 2018-2020 and analyzed cross-sectionally in each period. Demographic and clinical variables, as well as the type of biologic used, were assessed. Generalized linear models were applied to study the evolution of the variables of interest over time periods, the diagnosis, and the interactions between them. A total of 4543 patients initiated a first biologic during the entire time frame of the study. Over the four time periods, disease evolution at the time of biologic initiation (p < 0.001), disease activity (p < 0.001), retention rate (p < 0.001) and the use of tumor necrosis factor inhibitors as a first-line treatment (p < 0.001) showed a significant tendency to decrease. Conversely, comorbidities, as assessed by the Charlson index (p < 0.001), and the percentage of patients using bDMARDs in monotherapy (p < 0.001), and corticosteroids (p < 0.001) tended to increase over time. Over the entire period of the study's analysis, 3289 patients started a second biologic. The following trends were observed: decreased DAS28 at switching (p < 0.001), lower retention rates (p = 0.004), and incremental changes to the therapeutic target between the first and second biologic (p < 0.001). From 2007 until now rheumatic patients who started a biologic were older, exhibited less clinical activity, presented more comorbidities, and switched to a different biologic more frequently and earlier.
Prognostic scales may help to optimize the use of hospital resources, which may be of prime interest in the context of a fast spreading pandemics. Nonetheless, such tools are underdeveloped in the ...context of COVID-19. In the present article we asked whether accurate prognostic scales could be developed to optimize the use of hospital resources. We retrospectively studied 467 files of hospitalized patients after COVID-19. The odds ratios for 16 different biomarkers were calculated, those that were significantly associated were screened by a Pearson's correlation, and such index was used to establish the mathematical function for each marker. The scales to predict the need for hospitalization, intensive-care requirement and mortality had enhanced sensitivities (0.91 CI 0.87-0.94; 0.96 CI 0.94-0.98; 0.96 CI 0.94-0.98; all with p < 0.0001) and specificities (0.74 CI 0.62-0.83; 0.92 CI 0.87-0.96 and 0.91 CI 0.86-0.94; all with p < 0.0001). Interestingly, when a different population was assayed, these parameters did not change considerably. These results show a novel approach to establish the mathematical function of a marker in the development of highly sensitive prognostic tools, which in this case, may aid in the optimization of hospital resources. An online version of the three algorithms can be found at: http://benepachuca.no-ip.org/covid/index.php.
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