The correlation between 4 adherence measurements methods in patients with rheumatoid arthritis using methotrexate.

AIMS: Methotrexate (MTX) is the cornerstone in the treatment of rheumatoid arthritis (RA) patients. However, adherence to MTX therapy is not optimal, and instruments to assess medication nonadherence are warranted. To date there is no consensus on the best method to determine adherence to MTX. The aim of this study was to assess the correlation between adherence assessed with a Medication Event Monitoring System (MEMS) vs. pill count, MTX-polyglutamate (PG) concentration and Compliance Questionnaire-Rheumatology (CQR) in patients with established RA. Second, the correlations between these methods and the Disease Activity Scores of 28 joints (DAS28) were examined. METHODS: Adult RA patients currently treated with MTX were included. Multivariable linear and logistic regression were used, with adherence assessed with MEMS as dependent variable vs. pill count, MTX-PG concentrations, CQR as independent variables and DAS28 vs. each of the 4 adherence measurements. Covariates were included, such as comedication, age and use of corticosteroids. RESULTS: In total, 190 consecutive RA patients were included. Pill count was correlated with adherence assessed with MEMS (linear regression, ß = 0.588, 95% confidence interval = 0.255-0.921, P < .001), whereas CQR and MTX-PGs were not. Logistic regression confirmed the correlation between dichotomized adherence and pill count only (ß = 4.47, 95% confidence interval = 1.31-7.64, P =  .006). No other correlations were found, either for all adherence outcomes or DAS28. CONCLUSION: Measuring adherence with MEMS is correlated with pill count, whereas other methods were not correlated with MEMS or with DAS28. Pill count can be used to estimate adherence to MTX therapy, in case MEMS is not achievable.

Electronic Monitoring Feedback for Improving Medication Adherence and Clinical Outcomes in Early Rheumatoid Arthritis: A Randomized Clinical Trial.

BACKGROUND: Non-adherence to medication (range 30-107%) is a major issue in patients with rheumatoid arthritis (RA). Previous research has shown that electronic monitoring feedback (EMF) might be an effective strategy to improve medication adherence in chronic conditions. Therefore, this study investigated the effectiveness of electronic monitoring feedback in patients with early RA to improve medication adherence and clinical outcomes compared to usual care. METHODS: An open-label randomized clinical trial was performed to compare EMF with standard care during a 12-month follow-up period on two sites of the Sint Maartenskliniek (Nijmegen and Boxmeer) in the Netherlands. Patients were eligible if they: (1) had a (working) diagnosis of early RA, (2) were currently using methotrexate, (3) were aged ≥18 years, and (4) had a life expectancy of ≥12 months. Primary outcome was the difference in proportion of non-adherent patients measured with the Compliance Questionnaire on Rheumatology after 12 months. Secondary outcomes were beliefs about medicines, medication adherence measured with the MMAS-8®, patients' health status, prescription of biologic DMARDs, and disease activity after 12 months. RESULTS: Of the 367 initially-invited patients, 93 patients with early RA agreed to participate in this study. No significant difference was found in the proportion of non-adherent patients between the intervention arm and the usual care arm after 12 months follow-up (60.0% and 61.3%, p=0.93, respectively). Patients in the intervention arm tended to discontinue methotrexate earlier than patients in the usual care arm (median time in weeks: 15.7 (9.1-33.6) and 21.9 (19-28.4), respectively, p=0.31), whereas patients in the usual care arm tended to initiate biologic DMARDs earlier than those in the intervention arm (median time in weeks: 11.9 (5.7-22) and 17 (9.9-40.9), respectively, p=0.55). CONCLUSION: This study illustrates the challenge of targeting non-adherence with EMF in patients with early RA and shares important lessons learned about designing adherence intervention trials with respect to study attrition, accounting for drug survival, intervention fidelity, intervention uptake, and technical aspects.

Are Health Care Professionals' Implicit and Explicit Attitudes Toward Conventional Disease-Modifying Antirheumatic Drugs Associated With Those of Their Patients?

OBJECTIVE: It is generally unknown how the attitudes and beliefs of health care professionals (HCPs) might affect the attitudes, beliefs, and medication-taking behavior of patients with rheumatoid arthritis (RA). This study aims 1) to examine the attitudes, health-related associations (both implicit and explicit), and beliefs of HCPs about conventional disease-modifying antirheumatic drugs, and 2) to assess whether these attitudes, health-related associations, and beliefs of HCPs are associated with those of their patients, with their patients' medication-taking behavior, and disease activity. METHODS: HCPs were recruited from 2 centers that specialized in rheumatology across The Netherlands, and patient recruitment followed. In this observational study, implicit outcomes were measured with single-category implicit association tests, whereas explicit outcomes were measured with a bipolar evaluative adjective scale and the Beliefs About Medicines Questionnaire-Specific. Spearman's rank correlations were used to describe correlations between implicit and explicit measures of the attitudes of HCPs. Multilevel, mixed-effects linear models were used to examine the association of HCP-related characteristics, including the implicit and explicit outcomes of HCPs, with those of their patients, their medication-taking behaviors, and disease activity. RESULTS: Of the 1,659 initially invited patients, 254 patients with RA (mean age 62.8 years, mean disease duration 11.8 years, and 68.1% of the patients were female) who were treated by 26 different HCPs agreed to participate in this study. The characteristics, attitudes, health-related associations, and beliefs about medicines of HCPs were not significantly associated with those of their patients, nor with their medication-taking behaviors or disease activity scores. CONCLUSION: This study demonstrated that the attitudes, health-related associations (as measured both implicitly and explicitly), and beliefs of HCPs were not significantly associated with the attitudes, beliefs, medication-taking behavior, and disease activity of patients with RA.

Preferences of patients with rheumatoid arthritis regarding disease-modifying antirheumatic drugs: a discrete choice experiment.

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.

A discrete choice experiment on preferences of patients with rheumatoid arthritis regarding disease-modifying antirheumatic drugs: the identification, refinement, and selection of attributes and levels.

OBJECTIVE: To comprehensively describe the identification, refinement, and selection of attributes and levels for a discrete choice experiment (DCE) on preferences of patients with rheumatoid arthritis (RA) regarding disease-modifying antirheumatic drugs (DMARDs). METHODS: A mixed-methods approach, consisting of three consecutive steps: a literature review, expert recommendations, and focus groups. Attributes and levels were identified by a scoping review and compiled into a list that was evaluated on its relevance by an expert panel. The list that resulted thereafter was used to inform three focus groups, including 23 patients with RA. New attributes and levels could be identified during the focus groups. Also, a ranking exercise was performed. The patients individually ranked the attributes (ie, the ones on the list and newly identified attributes) by relevance. The patients' individual rankings were summed to derive a ranking at group level and make an a priori selection of the most relevant attributes. The group discussions were transcribed for qualitative analysis. RESULTS: Nineteen attributes, each specified by two to seven levels, were identified by the scoping review. The expert recommendations resulted in the removal of one attribute. Furthermore, two new attributes and levels were identified and two attributes were split into two. One new attribute was identified during the focus groups. The results of the ranking exercise and qualitative analysis led to the refinement and selection of the following attributes: route of administration, frequency of administration, chance of efficacy, onset of action, risk of serious infections, risk of liver injury, and risk of cancer. Each attribute was specified by three levels. CONCLUSION: This study contributes to the limited literature on the development of attributes and levels. Future research should pay more attention to a comprehensive description of this process. It ensures transparency and thereby allows researchers to judge a DCE's quality and generalizability.

The effect of electronic monitoring feedback on medication adherence and clinical outcomes: A systematic review.

OBJECTIVE: This study aims to assess the efficacy of Electronic Monitoring Feedback (EMF) as an intervention to improve medication adherence (i.e. dose- or full adherence) and clinical outcomes in adult patients. METHODS: A systematic search was performed in Medline, EMBASE, PsycINFO and Web of Science and reported according to the PRISMA guidelines. Randomised controlled trials (RCTs) comparing EMF with usual care were identified to systematically summarise the evidence for use of EMF in improving medication adherence and clinical outcomes. The GRADE approach was used to assess the quality of the body of evidence. RESULTS: Of 9,993 initially-identified studies, ten studies (four of high-quality and six of low-quality) were included. The sample size of the studies included varied from 18 to 205 patients. Four of the six studies (66.7%) reported a significant positive effect of EMF on mean dose adherence levels, whereas a significant positive effect of EMF on mean full adherence levels was found in all of the included studies (100%, five out of five of the studies included). A significant positive effect of EMF on clinical outcomes was reported in one of the seven studies included. The overall effect of EMF on mean dose- and full adherence was positive and the overall effect of EMF on clinical outcomes was inconclusive. CONCLUSION: Considering the positive effect of EMF on medication adherence, EMF might be a promising intervention to enhance medication adherence. However, the effect of EMF on clinical outcomes was inconclusive. Prior to implementing EMF in clinical practice, future research with high-quality studies (e.g. adequate sample sizes, follow-up periods and no interfering co-interventions) is required to examine the (long-term) efficacy of EMF.