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Updated: May 1, 2026
The Multiple Sclerosis Performance Test MSPT: An iPad-Based Disability Assessment Tool
Published on: June 30, 2014
Multicriteria decision analysis methods with 1000Minds for developing systemic sclerosis classification criteria
Sindhu R Johnson1, Raymond P Naden2, Jaap Fransen3
1Division of Rheumatology, Department of Medicine, Toronto Western Hospital, University of Toronto, Ground Floor, East Wing, 399 Bathurst Street, Toronto, Ontario, Canada M5T 2S8; Division of Rheumatology, Department of Medicine, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.
Objectives:
Classification criteria for systemic sclerosis (SSc) are being developed. The objectives were to develop an instrument for collating case data and evaluate its sensibility; use forced-choice methods to reduce and weight criteria; and explore agreement among experts on the probability that cases were classified as SSc.
Study Design And Setting:
A standardized instrument was tested for sensibility. The instrument was applied to 20 cases covering a range of probabilities that each had SSc. Experts rank ordered cases from highest to lowest probability; reduced and weighted the criteria using forced-choice methods; and reranked the cases. Consistency in rankings was evaluated using intraclass correlation coefficients (ICCs).
Results:
Experts endorsed clarity (83%), comprehensibility (100%), face and content validity (100%). Criteria were weighted (points): finger skin thickening (14-22), fingertip lesions (9-21), friction rubs (21), finger flexion contractures (16), pulmonary fibrosis (14), SSc-related antibodies (15), Raynaud phenomenon (13), calcinosis (12), pulmonary hypertension (11), renal crisis (11), telangiectasia (10), abnormal nailfold capillaries (10), esophageal dilation (7), and puffy fingers (5). The ICC across experts was 0.73 [95% confidence interval (CI): 0.58, 0.86] and improved to 0.80 (95% CI: 0.68, 0.90).
Conclusions:
Using a sensible instrument and forced-choice methods, the number of criteria were reduced by 39% (range, 23-14) and weighted. Our methods reflect the rigors of measurement science and serve as a template for developing classification criteria.
