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Background: Although patients have different treatment preferences, these individual preferences could often be grouped in subgroups with shared preferences. Knowledge of these subgroups as well as factors associated with subgroup membership supports health care professionals in the understanding of what matters to patients in clinical decision-making. Objectives: To identify subgroups of patients with rheumatoid arthritis (RA) based on their shared preferences toward disease-modifying antirheumatic drugs (DMARDs), and to identify factors associated with subgroup membership. Methods: A discrete choice experiment to determine DMARD preferences of adult patients with RA was designed based on a literature review, expert recommendations, and focus groups. In this multicenter study, patients were asked to state their preferred choice between two different hypothetical treatment options, described by seven DMARD characteristics with three levels within each characteristic. Latent class analyses and multinomial logistic regressions were used to identify subgroups and the characteristics (patient characteristics, disease-related variables, and beliefs about medicines) associated with subgroup membership. Results: Among 325 participating patients with RA, three subgroups were identified: an administration-driven subgroup (45.6%), a benefit-driven subgroup (29.7%), and a balanced subgroup (24.7%). Patients who were currently using biologic DMARDs were significantly more likely to belong to the balanced subgroup than the administration-driven subgroup (relative risk ratio (RRR): 0.50, 95% CI: 0.28–0.89). Highly educated patients were significantly more likely to belong to the benefit-driven subgroup than the balanced subgroup (RRR: 11.4, 95% CI: 0.97–133.6). Patients' medication-related concerns did not contribute significantly to subgroup membership, whereas a near-significant association was found between patients' beliefs about medication necessity and their membership of the benefit-driven subgroup (RRR: 1.12, 95% CI: 1.00–1.23). Conclusion: Three subgroups with shared preferences were identified. Only biologic DMARD use and educational level were associated with subgroup membership. Integrating patient's medication preferences in pharmacotherapy decisions may improve the quality of decisions and possibly medication adherence. [ABSTRACT FROM AUTHOR]

Introduction: Non-adherence to disease-modifying antirheumatic drugs (DMARDs) is suspected to relate to health care costs. In this study we investigated this relation in the first year of treatment. Methods: In a multi-center cohort study with a one year follow up, non-adherence was continuously measured using electronic monitored medication jars. Non-adherence was defined as the number of days with a negative difference between expected and observed opening of the container. Cost measurement focused on hospital costs in the first year: consultations, emergency room visits, hospitalization, medical procedures, imaging modalities, medication costs, and laboratory tests. Cost volumes were registered from patient medical files. We applied multivariate regression analyses for the association between non-adherence and costs, and other variables (age, sex, center, baseline disease activity, diagnosis, socioeconomic status, anxiety and depression) and costs. Results: Of the 275 invited patients, 206 were willing to participate. 74.2% had rheumatoid arthritis, 20.9% had psoriatic arthritis and 4.9% undifferentiated arthritis. 23.7% of the patients were more than 20% non-adherent over the follow-up period. Mean costs are € 2117.25 (SD € 3020.32). Non-adherence was positively related to costs in addition to baseline anxiety. Conclusion: Non-adherence is associated with health care costs in the first year of treatment for arthritis. This suggests that improving adherence is not only associated with better outcome, but also with savings. [ABSTRACT FROM AUTHOR]

Objectives: To induce disease remission, early arthritis patients should adhere to their disease-modifying antirheumatic drugs (DMARD) in the first months after diagnosis. It remains unknown why some patients are non-adherent. We aimed to identify patients at risk for non-adherence in the first 3 months of treatment.Methods: Adult DMARD-naive early arthritis patients starting synthetic DMARDs filled out items on potential adherence predictors at baseline. Adherence was measured continuously. Non-adherence was defined as not opening the electronically monitored pill bottle when it should have been. Items were reduced and clustered using principal component analysis. The most discriminating items were identified with latent trait models. We used a multivariable logistic regression model to find non-adherence predictors.Results: 301 patients agreed to participate. Adherence was high and declined over time. Principal component analysis led to 7 dimensions, while subsequent latent trait models analyses led to 15 dimensions. Two dimensions were associated with adherence, one dimension was associated with non-adherence.Conclusions: Information seeking behavior and positive expectations about the course of the disease are associated with adherence. Patients who become passive because of pain are at risk for non-adherence.Practice Implications: Rheumatologists have cues to identify non-adherence, and may intervene on non-adherence through implementing shared decision making techniques. [ABSTRACT FROM AUTHOR]

Abstract: Objectives: To identify factors associated with adherence to medication for rheumatoid arthritis or undifferentiated inflammatory arthritis using a systematic literature search. Methods: PubMed, PsycINFO, EMbase and CINAHL databases were systematically searched from inception to February 2011. Articles were included if they addressed medication adherence, used a reproducible definition, determinants and its statistical relationship. Methodological quality was assessed using a quality assessment list for observational studies derived from recommendations from Sanderson et al. (2007) [12]. Resulting factors were interpreted using the Health Belief Model (HBM). Results: 18 out of 1479 identified studies fulfilled the inclusion criteria. 64 factors were identified and grouped according to the HBM into demographic and psychosocial characteristics, cues to action and perceived benefits versus perceived barriers. The belief that the medication is necessary and DMARD use prior to the use of anti-TNF had strong evidence for a positive association with adherence. There is limited evidence for positive associations between adherence and race other than White, general cognition, satisfactory contact with the healthcare provider and the provision of adequate information from the healthcare provider. There is limited evidence for negative associations between adherence and having HMO insurance, weekly costs of TNF-I, having a busy lifestyle, receiving contradictory information or delivery of information in an insensitive manner by the rheumatologist. 18 factors were unrelated to adherence. Conclusions: The strongest relation with adherence is found to be prior use of DMARDs before using anti-TNF and beliefs about the necessity of the medication. Because the last one is modifiable, this provides hope to improve adherence. [Copyright &y& Elsevier]