Involving patients as research partners in research in rheumatology: a literature review in 2023

OBJECTIVE: The inclusion of patient research partners (PRPs) in research projects is increasingly recognised and recommended in rheumatology. The level of involvement of PRPs in translational research in rheumatology remains unknown, while in randomised clinical trials (RCTs), it has been reported to be 2% in 2020. Therefore, we aimed to assess the involvement of PRPs in recent translational studies and RCTs in rheumatology. METHODS: We conducted a scoping literature review of the 80 most recent articles (40 translational studies and 40 RCTs) from four target diseases: rheumatoid arthritis, psoriatic arthritis, systemic lupus erythematosus and lower extremity osteoarthritis. We selected 20 papers from each disease, published up until 1 March 2023, in rheumatology and general scientific journals. In each paper, the extent of PRP involvement was assessed. Analyses were descriptive. RESULTS: Of 40 translational studies, none reported PRP involvement. Of 40 RCTs, eight studies (20%) reported PRP involvement. These trials were mainly from Europe (75%) and North America (25%). Most of them (75%) were non-industry funded. The type of PRP involvement was reported in six of eight studies: six studies reported PRP participation in the study design or design of the intervention and two of them in the interpretation of the results. All the trials reporting the number of PRPs (75%), involved at least two PRPs. CONCLUSION: Despite a worldwide movement advocating for increased patient involvement in research, PRPs in translational research and RCTs in rheumatology are significantly under-represented. This limited involvement of PRPs in research highlights a persistent gap between the existing recommendations and actual practice

Patient global assessment in measuring disease activity in rheumatoid arthritis:A review of the literature

International audiencePatient-reported outcomes (PROs) reflect the patient’s perspective and are used in rheumatoid arthritis (RA) routine clinical practice. Patient global assessment (PGA) is one of the most widely used PROs in RA practice and research and is included in several composite scores such as the 28-joint Disease Activity Score (DAS28). PGA is often assessed by a single question with a 0–10 or 0–100 response. The content can vary and relates either to global health (e.g., how is your health overall) or to disease activity (e.g., how active is your arthritis). The wordings used as anchors, i.e., for the score of 0, 10, or 100 according to the scale used, and the timing (i.e., this day or this week) also vary. The different possible ways of measuring PGA translate into variations in its interpretation and reporting and may impact on measures of disease activity and consequently achievement of treat-to-target goals. Furthermore, although PGA is associated with objective measures of disease activity, it is also associated with other aspects of health, such as psychological distress or comorbidities, which leads to situations of discordance between objective RA assessments and PGA. Focusing on the role of PGA, its use and interpretation in RA, this review explores its validity and correlations with other disease measures and its overall value for research and routine clinical practice

Improving domain definition and outcome instrument selection: Lessons learned for OMERACT from imaging

Objectives: Imaging is one of the most rapidly evolving fields in medicine. Unfortunately, many imaging technologies have been applied as measurement instruments without rigorous evaluation of the evidence supporting their truth, discriminatory capability and feasibility for that context of use. The Outcome Measures in Rheumatology (OMERACT) Filter 2.1 Instrument Selection Algorithm (OFISA) is used to evaluate such evidence for use of an instrument in a research setting. The objectives of this work are to: [1] define and describe the key conceptual aspects that are essential for the evaluation of imaging as an outcome measurement instrument and [2] describe how these aspects can be assessed through OFISA. Methods: Experts in imaging and/or methodology met to formalize concepts and define key steps. These concepts were discussed with a team of patient research partners with interest in imaging to refine technical and methodological aspects into comprehensible information. A workshop was held at OMERACT2020 and feedback was incorporated into existing OMERACT process for domain and instrument selection. Results: Three key lessons were identified: (1) a clear definition of the domain we want to measure is a necessary prerequisite to the selection of a good instrument, (2) the sources of variability that can directly influence the instrument should be clearly identified, (3) incorporating these first two lessons into OFISA improves the quality of every instrument selection process. Conclusions: The incorporation of these lessons in the updated OMERACT Filter (now 2.2) will improve the quality of the selection process for all types of outcome measurement instruments

Improving domain definition and outcome instrument selection: Lessons learned for OMERACT from imaging

Objectives: Imaging is one of the most rapidly evolving fields in medicine. Unfortunately, many imaging technologies have been applied as measurement instruments without rigorous evaluation of the evidence supporting their truth, discriminatory capability and feasibility for that context of use. The Outcome Measures in Rheumatology (OMERACT) Filter 2.1 Instrument Selection Algorithm (OFISA) is used to evaluate such evidence for use of an instrument in a research setting. The objectives of this work are to: [1] define and describe the key conceptual aspects that are essential for the evaluation of imaging as an outcome measurement instrument and [2] describe how these aspects can be assessed through OFISA. Methods: Experts in imaging and/or methodology met to formalize concepts and define key steps. These concepts were discussed with a team of patient research partners with interest in imaging to refine technical and methodological aspects into comprehensible information. A workshop was held at OMERACT2020 and feedback was incorporated into existing OMERACT process for domain and instrument selection. Results: Three key lessons were identified: (1) a clear definition of the domain we want to measure is a necessary prerequisite to the selection of a good instrument, (2) the sources of variability that can directly influence the instrument should be clearly identified, (3) incorporating these first two lessons into OFISA improves the quality of every instrument selection process. Conclusions: The incorporation of these lessons in the updated OMERACT Filter (now 2.2) will improve the quality of the selection process for all types of outcome measurement instruments