RESUMO
BACKGROUND: The Patient-Determined Disease Steps (PDDS) scale is a patient-reported measure of disability used by at least 3 North American multiple sclerosis (MS) registries. We conducted a systematic review of the psychometric properties of the PDDS scale as part of a harmonization effort related to disability measures used in MS registries. METHODS: We searched the EMBASE, Ovid Medline, Scopus, Cochrane Database of Systematic Reviews, CENTRAL, CINAHL Plus, and ClinicalTrials.gov databases from database inception through July 28, 2020. Two reviewers independently screened abstracts and full-text reports for study inclusion and data extraction and assessed study quality and risk of bias. We included studies that assessed the validity or reliability of the PDDS scale. We conducted a meta-analysis to quantitatively summarize the findings. RESULTS: From the 2476 abstracts screened, 234 articles underwent full-text review, of which 5 met the inclusion criteria. These studies assessed criterion validity, construct validity, and test-retest reliability. In all studies, criterion validity was assessed by correlating the PDDS scale score with the Expanded Disability Status Scale score (pooled r = 0.73; 95% CI, 0.66-0.79). Test-retest reliability was high (pooled intraclass correlation coefficient = 0.96; 95% CI, 0.92-0.99). CONCLUSIONS: In this systematic review, the PDDS scale demonstrated criterion and construct validity for assessing disability in individuals with MS who have mild to moderate disabilities. This review also supports the test-retest reliability of the PDDS scale, although further studies with larger samples are needed.
RESUMO
Objectives: The development of autoantibody directed towards citrullinated proteins (ACPA) are predictive of RA in at-risk individuals. The biological events that underpin loss of immune tolerance and progression into inflammatory arthritis are not known. We sought to identify serum proteomic alterations that drive autoantibody formation, persistence and progression into inflammatory arthritis in a cohort of first-degree relatives (FDR) of RA patients. Methods: We studied baseline serum samples from a cohort of Indigenous FDR (n = 147) and quantified serum proteins using a 48-plex platform. Longitudinal outcomes were defined on the basis of ACPA status and progression into inflammatory arthritis (IA). K-means clustering, differential expression, and principal components analyze group differences. A co-expression module analysis was used to identify enriched networks. Random forest was used to classify ACPA positive samples, while network analysis was used to understand underlying biological processes based on protein expression. Results: We defined 6 proteomic clusters, with enrichment of ACPA positive samples in one of the clusters. 23 of 24 differentially expressed proteins in ACPA positive samples were upregulated. A co-expression network was enriched in ACPA positive sera and individuals who progressed into IA. Random Forest achieved an area under the curve of 0.767 to classify ACPA positive sera in a test dataset. Network analysis revealed upregulation of JAK-STAT signalling as being activated in those at highest risk to develop future IA. Conclusions: The serum proteome provides a rich dataset to understand biological processes in ACPA seropositive individuals. A combination of serum biomarkers, including ACPA, may predict future arthritis onset in at-risk individuals.
