A comparative analysis of Patient-Reported Expanded Disability Status Scale tools

Author:

Collins Christian DE1,Ivry Ben1,Bowen James D2,Cheng Eric M3,Dobson Ruth4,Goodin Douglas S5,Lechner-Scott Jeannette6,Kappos Ludwig7,Galea Ian8

Affiliation:

1. Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton, UK

2. Multiple Sclerosis Center, Swedish Neuroscience Institute, Seattle, WA, USA

3. Department of Neurology, David Geffen School of Medicine, VA Greater Los Angeles Healthcare System, University of California, Los Angeles (UCLA), Los Angeles, CA, USA

4. Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK

5. Department of Neurology, University of California, San Francisco (UCSF), San Francisco, CA, USA

6. Hunter Medical Research Institute, The University of Newcastle, Australia and Department of Neurology, John Hunter Hospital, Newcastle, NSW, Australia

7. Departments of Medicine, Clinical Research, Biomedicine and Biomedical Engineering, University Hospital Basel, Basel, Switzerland

8. Clinical Neurosciences, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton, UK/Wessex Neurosciences Centre, University Hospital Southampton NHS Foundation Trust, Southampton, UK

Abstract

Background: Patient-Reported Expanded Disability Status Scale (PREDSS) tools are an attractive alternative to the Expanded Disability Status Scale (EDSS) during long term or geographically challenging studies, or in pressured clinical service environments. Objectives: Because the studies reporting these tools have used different metrics to compare the PREDSS and EDSS, we undertook an individual patient data level analysis of all available tools. Methods: Spearman’s rho and the Bland–Altman method were used to assess correlation and agreement respectively. Results: A systematic search for validated PREDSS tools covering the full EDSS range identified eight such tools. Individual patient data were available for five PREDSS tools. Excellent correlation was observed between EDSS and PREDSS with all tools. A higher level of agreement was observed with increasing levels of disability. In all tools, the 95% limits of agreement were greater than the minimum EDSS difference considered to be clinically significant. However, the intra-class coefficient was greater than that reported for EDSS raters of mixed seniority. The visual functional system was identified as the most significant predictor of the PREDSS–EDSS difference. Conclusion: This analysis will (1) enable researchers and service providers to make an informed choice of PREDSS tool, depending on their individual requirements, and (2) facilitate improvement of current PREDSS tools.

Publisher

SAGE Publications

Subject

Clinical Neurology,Neurology

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