Generation of a Core Set of Items to Develop Classification Criteria for Scleroderma Renal Crisis Using Consensus Methodology.
Butler E-A., Baron M., Fogo AB., Frech T., Ghossein C., Hachulla E., Hoa S., Johnson SR., Khanna D., Mouthon L., Nikpour M., Proudman S., Steen V., Stern E., Varga J., Denton C., Hudson M., Scleroderma Clinical Trials Consortium Scleroderma Renal Crisis Working Group None.
OBJECTIVE: To generate a core set of items to develop classification criteria for scleroderma renal crisis (SRC) using consensus methodology. METHODS: An international, multidisciplinary panel of experts was invited to participate in a 3-round Delphi exercise developed using a survey based on items identified by a scoping review. In round 1, participants were asked to identify omissions and clarify ambiguities regarding the items in the survey. In round 2, participants were asked to rate the validity and feasibility of the items using Likert-type scales ranging from 1 to 9 (where 1 = very invalid/unfeasible, 5 = uncertain, and 9 = very valid/feasible). In round 3, participants reviewed the results and comments from round 2 and were asked to provide final ratings. Items rated as highly valid and feasible (median scores ≥7 for each) in round 3 were selected as the provisional core set of items. A consensus meeting using a nominal group technique was conducted to further reduce the core set of items. RESULTS: Ninety-nine experts from 16 countries participated in the Delphi exercise. Of the 31 items in the survey, consensus was achieved on 13, in the categories hypertension, renal insufficiency, proteinuria, and hemolysis. Eleven experts took part in the nominal group technique discussion, where consensus was achieved in 5 domains: blood pressure, acute kidney injury, microangiopathic hemolytic anemia, target organ dysfunction, and renal histopathology. CONCLUSION: A core set of items that characterize SRC was identified using consensus methodology. This core set will be used in future data-driven phases of this project to develop classification criteria for SRC.