Currently recommended skin scores correlate highly in the assessment of patients with Juvenile Dermatomyositis (JDM)
Autor: | Alexander Gebreamlak, Katherine M. Sawicka, Rose Garrett, Y. Ingrid Goh, Kayla M. Baker, Brian M. Feldman |
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Jazyk: | angličtina |
Rok vydání: | 2023 |
Předmět: |
Juvenile dermatomyositis (JDM)
Disease activity score skin subscale (skinDAS) Cutaneous assessment tool (CAT) Cutaneous dermatomyositis disease area and severity index (CDASI) Physician’s global assessment skin visual analog scale (Skin VAS) Patient outcomes Pediatrics RJ1-570 Diseases of the musculoskeletal system RC925-935 |
Zdroj: | Pediatric Rheumatology Online Journal, Vol 21, Iss 1, Pp 1-8 (2023) |
Druh dokumentu: | article |
ISSN: | 1546-0096 |
DOI: | 10.1186/s12969-023-00844-5 |
Popis: | Abstract Background Juvenile Dermatomyositis (JDM) is a rare, chronic, and life-threatening childhood autoimmune disease. Currently, there are recommended, reliable and validated measurement tools for assessment of skin disease activity in JDM including the Disease Activity Score (skinDAS), Cutaneous Assessment Tool (CAT), and the Cutaneous Dermatomyositis Disease Area and Severity Index (CDASI). The Physician’s global assessment skin visual analog scale (Skin VAS) is also widely used for skin activity in JDM. For the purpose of comparative international studies, we wanted to compare these tools to the Physician’s skin VAS (as a standard) to identify which performs better. Objectives We sought to compare the correlations of these scoring tools, and separately assess the responsiveness each tool demonstrates following patient treatment, in order to see if one tool may be preferred. This was determined by assessing how well these tools correlate with each other, and the Physician’s skin VAS over time, as well as the responsiveness of each tool after patient treatment. Methods Skin scores were recorded at a baseline (first visit after June 1st, 2018) and all follow-up office visits at the Juvenile Dermatomyositis Clinic. Following baseline visits, patients were followed up as clinically indicated. A subset of newly diagnosed patients (inception cohort) was identified. Correlations were assessed at the baseline visit and over time for the whole cohort. The correlations over time were derived using Generalized Estimating Equations (GEEs). Standardized response means with 95% confidence intervals were calculated to test score responsiveness for the nested inception cohort. Results The skinDAS, CAT and CDASI all correlated highly with each other and with the Physician’s skin VAS. The three scoring tools accurately reflected Physician’s skin VAS scores over time. In addition, all tools showed moderate to high responsiveness following treatment. Conclusion All studied skin score tools performed well in our study and appear to be useful. Since no tool far outperforms the others, arbitrary consensus will be needed to select a single standard measurement tool for the purposes of efficiency and global comparability. |
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