Objective:This study aims to explore the risk factors of Multi-center Investigator-Initiated Clinical Trials (MIITs), and provide a basis for developing study management strategies.Methods:The original draft of MIIT risk evaluation factors was determined through literature analysis and internal discussions of the research group. Thirty five experts were consulted using the Delphi method, and then the MIIT risk evaluation elements were finally determined. Analytic Hierarchy Process (AHP) was used to calculate the weights of each index.Results:The recovery rates of both rounds of expert consultation were 100%, and the degree of expert authority was 0.856. The study ultimately formed an MIIT risk evaluation framework consisting of three first-class indexes, twelve second-class indexes, and thirty-eight third-class indexes. The weight values of the first-class indexes (start-up period, implementation period, and summary period) were 0.209 8, 0.710 6, and 0.079 6, respectively. Meanwhile, the weight values of the second-class indexes and third-class indexes were determined.Conclusions:Exploring the risk evaluation factors of MIIT provides valuable insights into identifying critical risk points, which, in turn, contributes to enhancing MIIT management efficiency, research progress, and quality.

Objective:This study aims to explore the risk factors of Multi-center Investigator-Initiated Clinical Trials (MIITs), and provide a basis for developing study management strategies.Methods:The original draft of MIIT risk evaluation factors was determined through literature analysis and internal discussions of the research group. Thirty five experts were consulted using the Delphi method, and then the MIIT risk evaluation elements were finally determined. Analytic Hierarchy Process (AHP) was used to calculate the weights of each index.Results:The recovery rates of both rounds of expert consultation were 100%, and the degree of expert authority was 0.856. The study ultimately formed an MIIT risk evaluation framework consisting of three first-class indexes, twelve second-class indexes, and thirty-eight third-class indexes. The weight values of the first-class indexes (start-up period, implementation period, and summary period) were 0.209 8, 0.710 6, and 0.079 6, respectively. Meanwhile, the weight values of the second-class indexes and third-class indexes were determined.Conclusions:Exploring the risk evaluation factors of MIIT provides valuable insights into identifying critical risk points, which, in turn, contributes to enhancing MIIT management efficiency, research progress, and quality.