Systematic Review and Metaanalysis of the Reproducibility of Patient Self-reported Joint Counts in Rheumatoid Arthritis

Remote patient-reported outcome measure triage score for monitoring disease activity and allocation of consultations in rheumatoid arthritis patients

OBJECTIVE

Currently, expedited by the coronavirus disease 2019 pandemic, there is high demand for allocating patients in a state of low disease activity to telehealth, ideally based on remote measurements. This cross-sectional study assesses the discriminative accuracy of the Rheumatoid Arthritis Impact of Disease (RAID) questionnaire regarding high and low disease activity. Furthermore, we aimed to optimize this classification, developing a remote triage score based on RAID and other patient-reported outcome measures (PROMs).

METHOD

Data were acquired from an outpatient clinic cohort of chronic rheumatoid arthritis patients at a large trainee hospital in the Netherlands. Patients were divided into high and low disease categories, based on 28-joint Disease Activity Score-C-reactive protein. Least absolute shrinkage and selection operator logistic regression were performed, including RAID item scores and other PROMs. Receiver operating characteristics curves and areas under the curve (AUCs) were obtained, and cut-off scores were based on predefined criteria of 90% and 95% sensitivity.

RESULTS

In total, 278 patients were analysed, of whom 77.2% were identified as having low disease activity. RAID results correlated with DAS28-CRP, showing good performance. The regression model included the RAID items pain and functional disability assessment, and the self-reported swollen joint count (SR-SJC). With an AUC of 0.88 (95% confidence interval 0.84-0.92), this model performed better than the RAID total score.

CONCLUSION

A remote triage score based on a composite score of pain, functional disability assessment, and SR-SJC can detect a sufficient proportion of patients with low disease activity who can be allocated to remote consultations.

Patient-reported swelling in arthralgia patients at risk for rheumatoid arthritis: is it of value?

OBJECTIVE

Patients with clinically suspect arthralgia (CSA) are at risk for developing rheumatoid arthritis (RA). These patients often report joint swelling while this is not objectified by physical examination. To explore the value of patient-reported swelling in CSA, we aimed to determine its association with subclinical joint inflammation on imaging and RA development.

METHODS

In two independent, similarly designed CSA cohorts from the Netherlands, symptomatic patients at risk for RA were studied. At baseline, patients indicated whether they had experienced swelling in hand joints. Subclinical joint inflammation was assessed with MRI or US. Patients were followed for inflammatory arthritis development.

RESULTS

In total, 534 CSA patients from two independent cohorts were studied, and patient-reported swelling was present in 57% in cohort 1 and in 43% in cohort 2. In both cohorts patient-reported swelling was associated with subclinical joint inflammation. Using MRI, it associated specifically with tenosynovitis (odds ratio [OR] 3.7 [95% CI: 2.0, 6.9]) and when using US with synovitis (OR 2.3 [95% CI: 1.04, 5.3]). CSA patients with self-reported swelling at baseline developed arthritis more often, with hazard ratios of 3.7 (95% CI: 2.0, 6.9) and 3.4 (95% CI: 1.4, 8.4) in cohort 1 and 2, respectively. This was independent of clinical predictors (e.g. morning stiffness), autoantibody positivity and US-detected subclinical joint inflammation. However, when corrected for MRI-detected subclinical joint inflammation, self-reported swelling was no longer an independent predictor.

CONCLUSION

Patient-reported joint swelling in CSA relates to subclinical joint inflammation and is an independent risk factor for RA development, but it is less predictive than the presence of MRI-detected subclinical joint inflammation.

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.

The Reproducibility of Patient Self-reported Joint Counts in Rheumatoid Arthritis: A Closer Look at the Results of a Review

In the management of rheumatoid arthritis (RA), the systematic evaluation of disease activity is of paramount importance. It is the cornerstone of the "treat-to-target" approach, aiming at disease remission and optimization of quality of life.¹ In times of increasing delivery of remote care, accelerated due to the coronavirus disease 2019 (COVID-19) pandemic, the role of patients in the monitoring of disease activity becomes more topical.