Multicriteria decision analysis methods with 1000Minds for developing systemic sclerosis classification criteria

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.