Depression is a common comorbidity in rheumatoid arthritis (RA), yet it may not be adequately recognized during routine clinical care. RA symptoms may confer a risk for depression, and vice versa; depression may affect RA disease activity and response to treatment. The study aims were to compare patient- and physician-reported depression measures, evaluate the temporal bi-directional association between RA disease activity and depressive symptomology, and assess depression as a moderator of RA treatment. Patients were identified using a national RA registry sample (Consortium of Rheumatology Researchers of North America; CORRONA). Depression prevalence and incidence rates were estimated, and concordance and disagreement using measures reported separately by patients and physicians, as well as baseline cross-sectional associations between RA disease and a history of depression. A survival analysis was conducted to temporally predict the incident onset of self-reported depressive symptoms using the different metrics of RA disease activity. Also, mixed effects models were used to assess prospective changes in RA disease activity by prevalent and incident depressive symptom status. Lastly, logistic regression models compared the likelihood of clinical response to RA treatment during follow-up in those with and without depression when starting biologic disease modifying anti-rheumatic drug (DMARD) therapy. Patient-reported depression rates were much higher and significantly different from physician based comorbidity estimates. Patient and physician RA disease activity measures were associated with an increased risk for depression onset, but not laboratory-reported serum biomarkers. Similarly, depression was temporally associated with significantly slower rates of decline regarding every patient-reported disease activity measure, some physician-reported metrics, but not acute phase reactants. Moreover, there was a significantly lower probability of achieving clinical remission among those with depression on a biologic DMARD after 6 months and an analogous effect at 12-months that was slightly lower in magnitude, which did not reach statistical significance. Rheumatologists under-reported the occurrence of prevalent and incident depressive symptoms, and thus are likely unaware of its presence in their RA patients. Further, the results suggest the bi-directional effects between these conditions are related to the cognitive and behavioral aspects of depression and their interactions with disease activity, rather than shared immunological mechanisms in the context of cell-mediated immunity. When also considering the impact on clinical response to biologic DMARDS, the findings collectively imply that rheumatologists must address any challenges due to depression to provide the best care to their patients.

Rheumatoid Arthritis is an inflammatory joint disease that is one of the most common autoimmune diseases in the world. The treatment usually starts with a first-line treatment called Methotrexate, but it is often insufficient. One of the most common second-line treatments is Tumor Necrosis Factor inhibitors (TNFi). Although some patients respond to TNFi, it has a risk of side effects, including infections. Hence, ability to predict patient responses to TNFi becomes important to choose the correct treatment. This work presents a new approach to predict if the patients were still on TNFi, 1 year after they started, by using a generative neural network architecture called Variational Autoencoder (VAE). We combined a VAE and a classifier neural network to create a supervised learning model called Supervised VAE (SVAE), trained on two versions of a tabular dataset containing Swedish register data. The datasets consist of 7341 patient records, and our SVAE achieved an AUROC score of 0.615 on validation data. Nevertheless, compared to machine learning models previously used for the same prediction task, SVAE achieved higher scores than decision trees and elastic net but lower scores than random forest and gradient-boosted decision tree. Despite the regularization effect that VAEs provide during classification training, the scores achieved by the SVAEs tested during this thesis were lower than the acceptable discrimination level. / Reumatoid artrit är en inflammatorisk ledsjukdom och är en av de vanligaste autoimmuna sjukdomarna i världen. Medicinsk behandling börjar ofta med Metotrexat. Vid brist på respons så fortsätter behandlingen ofta med Tumor Necrosis Inhibitors (TNFi). På grund av biverkningar av TNFi, såsom ökad risk för infektioner, är det viktigt att kunna prediktera patienters respons på behandlingen. Här presenteras ett nytt sätt att prediktera om patienter fortfarande stod på TNFi ett år efter initiering. Vi kombinerade Variational Autoencoder (VAE), ett generativt neuralt nätverk, med ett klassificeringsnätverk för att skapa en övervakad inlärningsmodell kallad Supervised VAE (SVAE). Denna tränades på två versioner av svenska registerdata, vilka innehöll information om 7341 patienter i tabellform. Vår SVAE-modell uppnådde 0,615 AUROC på valideringsdata. I jämförelse med maskininlärningsmodeller som tidigare använts för samma prediktionsuppgift uppnådde SVAE högre poäng än Decision Tree och Elastic Net men lägre poäng än Random Forest och Gradient-Boosted Decision Tree. Trots regulariseringseffekten som VAE ger under träning så var poängen som de testade SVAEmodellerna uppnår lägre än den acceptabla diskrimineringsnivån.

In this paper, a rheumatoid arthritis (RA) medicine clinical dataset with an ordinal response is selected to study this new medicine. In the dataset, there are four features, sex, age,treatment, and preliminary. Sex is a binary categorical variable with 1 indicates male, and 0 indicates female. Age is the numerical age of the patients. And treatment is a binary categorical variable with 1 indicates has RA, and 0 indicates does not have RA. And preliminary is a five class categorical variable indicates the patient’s RA severity status before taking the medication. The response Y is 5 class ordinal variable shows the severity of patient’s RA severity after taking the medication. The primary aim of this study is to determine what factors play a significant role in determine the response after taking the medicine. First, cumulative logistic regression is applied to the dataset to examine the effect of various factors on ordinal response. Secondly, the ordinal response is categorized into two classes. Then logistic regression is conducted to the RA dataset to see if the variable selection would be different. Moreover, the shrinkage methods, elastic net and lasso are used to make a variable selection on the RA dataset of two-class response for the purpose of adding penalization to increase the model’s robustness.The four model results were compared at the end of the paper. From the comparison result, logistic regression has a better performance on variable selection than the other three approaches based on P-value.

No description available.

The effect of synovial membrane products and mechanical pressure upon the metabolism of articular cartilage proteoglycans has been studied in vitro. The degradation of cartilage proteoglycans was studied in an organ culture system and measured as the release of [35S ] sulphate from prelabelled cartilage. The effect of synovial membrane products upon the synthesis of proteoglycans was studied in a chondrocyte monolayer system and the effect of mechanical pressure upon the synthesis of proteoglycans in an organ culture system. In both types of experiments [35S] sulphate was used as precursor. The findings may be summarized as follows 1 Conditioned synovial medium (control-SM) enhanced the degradation and reduced the synthesis of cartilage proteoglycans. In addition the degradation was further enhanced when the synovial tissue had been cultured in the presence of dextran sulphate. 2 Conditioned medium from synovial tissue cultured in the presence of indo-methacin (indo-SM), significantly reduced the synthesis of cartilage proteoglycans in chondrocyte cultures and reduced, although non-significantly, the degradation of proteoglycans in whole cartilage cultures. 3 Addition o f the prostaglandins E1 or E2 (PGE1 or PGE2 ) together with indo-SM to the cartilage cultures greatly enhanced cartilage degradation whereas the addition of PGE1 or PGE2 together with control-SM had no effect compared with that of control-SM alone. 4 Conditioned medium from synovial tissue cultured in the presence of low doses of glucocorticoids reduced cartilage degradation compared with control-SM. However, addition of control-SM together w ith low concentrations of glucocorticoids to the cartilage cultures significantly enhanced cartilage degradation. 5 Conditioned medium from synovial tissue cultured with actinomycin D or cycloheximide did not enhance cartilage degradation compared with cartilage cultured alone. 6 A continuous pressure of approximately 30 kgfcm-2 on cultures of cartilage reduced both the synthesis and the degradation o f cartilage proteoglycans. Although it is difficult to extrapolate from the in vitro to the in vivo situation, it is proposed that some factor(s) from the synovial membrane have the capacity to enhance the degradation and reduce the synthesis o f articular cartilage proteoglycans. From these experiments it cannot be completely excluded that treatm ent of arthritic joints with non-steroidal or streroidal anti-inflammatory drugs may result under certain conditions in enhanced joint damage. It is also suggested that under certain conditions the metabolism o f cartilage proteoglycans could be directly affected by mechanical stress. / <p>Diss. Umeå, Umeå universitet, 1982, härtill 6 uppsatser</p> / digitalisering@umu

Background: Inflammation is the natural reaction of the body to an antigen. In some conditions, this reaction continues even after the elimination of the antigen, entering a chronic stage; it targets normal cells of the body and causes extensive damage. Rheumatoid arthritis (RA) is such a condition. It associates with significant metabolic alterations that lead to changes in body composition and especially body fat (BF) increases. In the general population, increased body fat (i.e. obesity) associates with a number of health disorders such as systemic low grade inflammation and a significantly increased risk for cardiovascular disease (CVD). Both effects of obesity could have detrimental effects in RA. Increased inflammation could worsen disease activity while obesity could further increase the already high CVD risk in RA. However, obesity in RA has attracted minimal scientific attention. Aims: The present project aimed to: 1) assess whether the existing measures of adiposity are able to identify the changes in body composition of RA patients, 2) if necessary develop RA-specific measures of adiposity, 3) investigate the association of obesity with disease characteristics and CVD profile of the patients, 4) and identify factors that might affect body weight and composition in these patients. Methods: A total of 1167 volunteers were assessed. Of them 43 suffered from osteoarthritis and 82 were healthy controls. These, together with 516 RA patients were used in the first study. Their body mass index (BMI), BF, and disease characteristics were assessed. In the second, third, fourth and fifth studies a separate set of 400 RA patients was assessed. In addition to the above assessments, their cardiovascular profile and more detailed disease characteristics were obtained. For the final study, 126 RA patients were assessed for all the above and also data on their physical activity levels and their diet were collected. Results: Assessments of adiposity for the general population are not valid for RA patients. Thus, we proposed RA-specific measures of adiposity. These are able to better identify RA patients with increased BF. We were also able to find associations between obesity and disease activity. Both underweight and obese RA patients had more active disease compared to normal-weight patients. Obese patients had significantly worse CVD profile compared to normal-weight. The newly devised measures of adiposity were able to identify those at increased risk. However, not all obese individuals were unhealthy and not all normal-weight healthy. Among our patients we were able to identify subtypes of obesity with distinct phenotypic characteristics that warrant special attention. Finally, we were able to identify factors that influence body weight and composition. Cigarette smoking protected against obesity while its cessation associated with increased adiposity. Physical activity was also found to be protective against obesity while diet or inflammation of the disease failed to produce any significant results. Conclusions: Obesity is a significant threat to the health of RA patients. The measures of adiposity developed herein should be used to identify obese RA patients. Physical activity seems like the sole mode for effective weight management in this population. Health and exercise professionals should actively encourage their patients to exercise as much as they can. This study has created more questions than it answered; further research in the association of obesity and inflammation, as well as in ways to treat it, is essential.

published_or_final_version / Social Work / Master / Master of Social Work

Rheumatoid arthritis (RA) is a progressive autoimmune disorder of joints that is associated with high health care costs and yet lacks guidance on how early to initiate biologic disease-modifying antirheumatic drugs (DMARDs), a class of medications that is the major cost driver in RA management. The main purpose of this study was to examine patient socio-demographics, medication use patterns, and clinical characteristics associated with initiation of biologic DMARDs. This was a retrospective study using Texas Medicaid prescription and medical claims database during the study period of July 1, 2003 – December 31, 2010. Patients (18 – 63 years) with an RA diagnosis (ICD-9-CM code 714.xx), no non-biologic DMARD or biologic DMARD use during the pre-index period, and a minimum of 2 prescription claims for the same non-biologic DMARD during the post-index period were included in the study. The primary study outcomes were time to initiation of biologic DMARDs and likelihood of initiating biologic DMARDs. There was a total of 2,714 subjects included in the study. The majority had claims for pain medications (92.4%), glucocorticoids (64.9%), and non-biologic DMARD monotherapy (86.4%); while 24.3% initiated on biologic DMARDs and 58.9% had a Charlson Comorbidity Index (CCI) score=1. Compared to time to initiation (days) of biologic DMARDs for methotrexate (539.7±276.9) users, it was longer for sulfasalazine (670.2±167.8) and hydroxychloroquine (680.2±158.7) users and similar to leflunomide users (541.6±286.5; p<0.0001). There were no significant differences in time to initiation between non-biologic DMARD mono vs. dual therapy. Younger age, glucocorticoid use, methotrexate user (vs. sulfasalazine, hydroxychloroquine users), and non-biologic DMARD monotherapy user (vs. dual therapy user) were significantly associated with higher likelihood to initiate biologic DMARDs. In conclusion, age, glucocorticoid use, non-biologic DMARD type and therapy were significant factors associated with initiation of biologic DMARDs. Healthcare providers and Texas Medicaid should recognize these potential driving factors and take efforts to achieve optimal therapy for RA patients through thorough RA medication evaluation, well-structured RA monitoring programs, and patient education. / text

The purpose of this study was to advance knowledge and understanding related to the cognitive response evoked by symptoms in women with rheumatoid arthritis. The mechanisms to achieve this purpose were through: (1) psychometric evaluation of a newly developed instrument: Chronic Fatigue Index (CFI), (2) examining the relationship among the symptoms of RA and components of quality of life for women with RA, and (3) exploring the mechanism by which learned resourcefulness affects the relationship between symptoms and quality of life. The Chronic Fatigue Index (CFI) was evaluated and met minimal levels of reliability and validity. Cronbach alpha reliability estimate for the CFI was.87. Convergent validity was tested through factor analysis. The CFI was found to be a multi-dimensional scale with two distinct factors: chronicity and interference. The factor analytical strategies revealed 46% of the variance in chronic fatigue was supported by these two components. Moderate to strong relationships were found among the symptoms of chronic pain, chronic fatigue, disturbed sleep, and disease flare. To evaluate quality of life in this population a common factor was created through factor analysis. The results of factor analysis revealed three indicators explaining 69% of the variance in quality of life for this population. Chronic pain explained fourteen percent of the variance in learned resourcefulness. The other symptoms and multiplicative terms did not meet the entry criteria. Learned resourcefulness was a weak mediator between the disturbance of chronic pain and quality of life, but successfully moderated the adverse effect of disturbed sleep. Fifty eight percent of the variance in quality of life was explained by the direct path of chronic pain and disturbed sleep on quality of life and the interaction of disturbed sleep and learned resourcefulness. Model respecification suggested that the inclusion of additional variables in the model would increase the explanatory power of the model. The self-regulation framework for symptom appraisal was supported by the findings of this study. Nursing interventions should focus on assisting clients with enhancing their level of learned resourcefulness as it will buffer the adverse effects of the disease process.

A series of five individual studies explored: (1) Whether a treatment focus emphasizing active anger expression would alter the subject's awareness of and ability to express anger and (2) Whether such a treatment focus would alter the subject's experience of illness in the form of her report of pain and stiffness as "better", "the same", or "worse" than yesterday's experience. The treatment strategy utilized general Gestalt principles and was further focused on specific techniques of Anger Therapy as an agent of change. Evaluation of outcome in this time-lagged multiple baseline design viewed the overall process from the beginning of a baseline observation period through a maximum of one week following the conclusion of the last six weekly treatment sessions; daily measurement of the process of change during treatment; and clinical description of the subjects and of the treatment process itself. The overall process was formally assessed in pre and post treatment testing which included the Novaco Anger Inventory, Buss-Durkee Hostility Inventory, Marlowe-Crowne Social Desirability Scale, and FIRO-B. Daily telephone interview measured the frequency of anger awareness, anger expression; and ratings of anger intensity, overall daily mood, pain, and stiffness. Information from the treatment process was integrated with that obtained from other sources in discussing the outcome for each subject. It was concluded that intense anger expression appeared to effect temporary or transitory improvement in pain; that there was a relationship between each subject's perceived daily anger intensity and pain which appeared consistent for all subjects studied; and that issues of need for approval and control appeared related to anger awareness and expression as measured by the psychometrics utilized. These were recommended as potentially fruitful areas of future investigation. Background data revealed striking similarities in birth order and parenting practices which seemed worthy of further study as well.