ArticleClinical rheumatology2022
Functional capacity vs side effects: treatment attributes to consider when individualising treatment for patients with rheumatoid arthritis.
Article in Clinical rheumatology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Patient research partner involvement in rheumatology research: a systematic literature review informing the 2023 updated EULAR recommendations for the involvement of patient research partners.Annals of the rheumatic diseases · 2024Pooled it
- Relative Importance of Disease-Modifying Antirheumatic Drug Attributes for Patients with Rheumatoid Arthritis.Patient preference and adherence · 2025Article
- Physical function and severe side effects matter most to patients with RA (< 5 years): a discrete choice experiment assessing preferences for personalized RA treatment.BMC rheumatology · 2023Article
- Rheumatoid arthritis study of the Egyptian College of Rheumatology (ECR): nationwide presentation and worldwide stance.Rheumatology international · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
introductionIndividualisation of rheumatoid arthritis (RA) treatment needs to take account of individual patients' preferences to increase patient-centeredness in treatment decisions. The aim of this study was to identify patient-relevant treatment attributes to consider when individualising treatment for patients with RA.
methodPatients with RA in Sweden were invited to rank the most important treatment attributes in an online survey (April to May 2020). Semi-structured interviews were conducted (October to November 2020) to further identify and frame potential attributes for shared decision-making. The interviews were audio-recorded, transcribed and analysed using thematic framework analysis. Patient research partners and rheumatologists supported the selection and framing of the treatment attributes across the assessment.
resultsThe highest ranked attributes (N = 184) were improved functional capacity, reduced inflammation, reduced pain and fatigue and the risk of getting a severe side effect. The framework analysis revealed two overarching themes for further exploration: treatment goals and side effects. 'Treatment goals' emerged from functional capacity, revealing two dimensions: physical functional capacity and psychosocial functional capacity. 'Side effects' revealed that mild and severe side effects were the most important to discuss in shared decision-making.
conclusionsFunctional capacity (physical and psychosocial) and potential side effects (mild and severe) are important treatment attributes to consider when individualising RA treatment. Future research should assess how patients with RA weigh benefits and risks against each other, in order to increase patient-centeredness early on the treatment trajectory.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.