Defining the care delivery value chain and mapping the patient journey in rheumatoid arthritis.

Rheumatoid Arthritis (RA) is a chronic disease that impacts patients' quality of life. Sophisticated organization of care delivery drives quality improvement. Therefore, the study objective was establishing a validated process map of the care cycle for RA patients. Hence, increasing transparency and optimizing care delivery and identifying areas of improvement. To map the RA care cycle, the care delivery value chain (CDVC) approach was used as framework to document activities and resources systematically. A mixed method study was conducted where quantitative data on activities were collected from health records and unstructured interviews with medical staff were held. Consequently, the process map was separately validated in a consensus meeting with a delegation of the medical staff and patient advisory board. At the start of the care cycle, the focus is predominantly on defining the treat-to-target strategy and examining disease activity. Towards the monitoring phase, tapering medication and managing the disease through patient-reported outcome measures are becoming increasingly important. Although patient's functioning, quality of care and patient's evaluation of received care are monitored, reflection of CDVC and engaging patients in the evaluation process resulted in improvement actions on outcome and process level. Mapping the RA care cycle following a systematic approach, provides insight and transparency in delivered activities, involved resources and the engagement of patients and caregivers at multiple levels, contributing to a system facilitating value-based care delivery. The CDVC framework and applied methodology is recommended in other conditions. Future research will focus at assigning outcomes and costs to activities and evaluating interventions to explore patient value.

Determining the Lowest Optimally Effective Methotrexate Dose for Individual RA Patients Using Their Dose Response Relation in a Tight Control Treatment Approach.

OBJECTIVE: To determine the optimal methotrexate dose in individual patients and to explore whether this optimal dose and the level of disease activity at that dose could be predicted. METHODS: Data from CAMERA II trial comparing MTX and MTX with 10 mg of prednisone both in a tight control treatment strategy in early RA was used. For each patient a curve for disease activity over time was fitted and the MTX dose after which further step-up did not result in relevant improvement in disease activity anymore was determined the 'lowest optimally effective MTX dose (LOED)'. The association of demographic and clinical characteristics at baseline with this LOED and with the level of disease activity reached at LOED was studied. RESULTS: In 204 (100 MTX and 104 MTX with prednisone) out of 236 patients LOED could be defined. 10 mg/wk was the most prevalent LOED in patients treated with MTX and prednisone and 10 mg/wk, 20 mg/wk and 30 mg/wk in the MTX strategy. Although the specific LOED could not reliably be predicted, higher baseline disease activity, height and lower weight were associated with higher LOEDs (i.e at least 15 mg/wk). A score was presented to decide on a starting dose of 10 mg/wk or (at least) 15 mg/wk. The level of disease activity at LOED could not be reliably predicted. CONCLUSION: A starting dose of 10 mg/wk might be a good choice for most patients and is frequently already the optimal dose. However, a subgroup of patient can be determined who would require higher MTX doses.

Does disease activity add to functional disability in estimation of utility for rheumatoid arthritis patients on biologic treatment?

OBJECTIVE: Treatment in general is mostly directly aimed at disease activity, and measures such as the DAS28 might therefore present important additional information. Our aim was to develop and validate a model that uses a combination of disease activity (DAS28) and HAQs to estimate EuroQoL 5-dimension scale (EQ5D) utilities. METHODS: Longitudinal data from a cohort study in RA patients from the Utrecht Rheumatoid Arthritis Cohort study Group (Stichting Reumaonderzoek Utrecht) who started treatment with a biologic drug were used for mapping and validation. All 702 observations, including DAS28, HAQ and EQ5D assessed at the same time points, were used. The observations were randomly divided into a subset for development of the model (n = 428 observations) and a subset for validation (n = 274). A stepwise multivariable regression analysis was used to test the association of DAS28 (components) and HAQ (domains) with EQ5D. Model performance was assessed using the explained variance (R(2)) and root mean square errors. Observed and predicted utility scores were compared to check for under- or overestimation of the scores. Finally, the performance of the model was compared with published mapping models. RESULTS: Lower DAS28 score and HAQ items dressing and grooming, arising, eating, walking and activities were associated with higher EQ5D scores. The final model had an explained variance of 0.35 and a lower root mean square error as compared with other models tested. The agreement between predicted and observed scores was fair. CONCLUSION: HAQ components estimate EQ5D better than total HAQ. Adding DAS28 to HAQ components does not result in better utility estimations.

Personalized biological treatment for rheumatoid arthritis: a systematic review with a focus on clinical applicability.

OBJECTIVES: To review studies that address prediction of response to biologic treatment in RA and to explore the clinical utility of the studied (bio)markers. METHODS: A search for relevant articles was performed in PubMed, Embase and Cochrane databases. Studies that presented predictive values or in which these could be calculated were selected. The added value was determined by the added value on prior probability for each (bio)marker. Only an increase/decrease in chance of response ⩾15% was considered clinically relevant, whereas in oncology values >25% are common. RESULTS: Of the 57 eligible studies, 14 (bio)markers were studied in more than one cohort and an overview of the added predictive value of each marker is presented. Of the replicated predictors, none consistently showed an increase/decrease in probability of response ⩾15%. However, positivity of RF and ACPA in case of rituximab and the presence of the TNF-α promoter 308 GG genotype for TNF inhibitor therapy were consistently predictive, yet low in added predictive value. Besides these, 65 (bio)markers studied once showed remarkably high (but not validated) predictive values. CONCLUSION: We were unable to address clinically useful baseline (bio)markers for use in individually tailored treatment. Some predictors are consistently predictive, yet low in added predictive value, while several others are promising but await replication. The challenge now is to design studies to validate all explored and promising findings individually and in combination to make these (bio)markers relevant to clinical practice.

Generalization and extrapolation of treatment effects from clinical studies in rheumatoid arthritis.

OBJECTIVE: Pragmatic clinical trials have been proposed as a solution for nongeneralizability of randomized clinical trial (RCT) results. We investigated whether treatment effects of pragmatic clinical trials are indeed generalizable to clinical practice and how efficacy estimates from published RCTs can be translated to daily practice populations. METHODS: Data from pragmatic clinical trials of the Utrecht Rheumatoid Arthritis Cohort and the observational Nijmegen Early Rheumatoid Arthritis inception cohort were used. The treatment effects of methotrexate and hydroxychloroquine as opposed to the pyramid approach were compared between the trials and observational study using a modified comprehensive cohort design analysis. The changes from baseline in disease activity (Disease Activity Score in 28 joints [DAS28]) and functional disability (Health Assessment Questionnaire [HAQ]) and European League Against Rheumatism (EULAR) response at 6 months were studied. The influence of population and treatment characteristics on the American College of Rheumatology 50% improvement criteria response compared with control therapy also at 6 months from RCTs was assessed using the relative risk (RR) and risk difference (RD). RESULTS: The DAS28 and HAQ generally improved more in patients in the pragmatic trials than in daily practice. However, using EULAR response as outcome, the treatment effect was not found to be different. In published RCT data, higher glucocorticoid use, disease duration, and cotreatment with disease-modifying antirheumatic drugs increased the RR. Use of glucocorticoids increased the RD, and higher values of baseline DAS28 and HAQ decreased the RR and RD. CONCLUSION: Pragmatic clinical trials might be directly generalizable only regarding relative treatment response. In extrapolating published RCT results to daily practice, population characteristics associated with disease severity, disease duration, and treatment history or cotreatment need to be taken into account.

Do radiographic joint damage and disease activity influence functional disability through different mechanisms? Direct and indirect effects of disease activity in established rheumatoid arthritis.

OBJECTIVE: To explore the relationship between rheumatoid arthritis (RA) disease activity and functional disability over time, considering indirect (predictive) and direct (concurrent) associations as well as the influence of radiographic joint damage and treatment strategy. METHODS: Functional disability [Health Assessment Questionnaire (HAQ)], disease activity [28-joint Disease Activity Score (DAS28)], and radiographic joint damage [Sharp/van der Heijde score (SHS)] were measured in 4 consecutive randomized controlled trials with increasingly intensive (tight control) treatment strategies. Average followup time for the 3 cohorts was 97, 53, and 50 months, respectively. Next to current DAS28, the previous DAS28 was used to study the predictive effect of a change in DAS28 on progression of functional disability (HAQ). Finally, it was investigated whether SHS mediated the predictive effect of DAS28. RESULTS: In patients treated with intensive treatment strategies, the progression of HAQ over time was statistically significantly less (p < 0.0001). The predictive influence of DAS28 on HAQ progression increased over the duration of the disease. SHS was not found to influence HAQ progression and did not mediate the predictive effect of DAS28. In the less intensively treated patients, the direct effect of disease activity decreased with disease duration, and contrarily, SHS did influence HAQ progression, but was not found to (fully) mediate the predictive effect of DAS28. CONCLUSION: In patients with RA treated with modern treatment strategies, there is less functional decline over time. Further, disease activity does predict functional decline but joint damage does not. This might indicate that factors associated with cumulative disease activity but not visible on radiographs can influence functional decline in patients with RA. This further underlines the importance of disease activity as a treatment target in early RA and in established RA.