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CNS Clinical Trials: Suicidality and Data Collection - Workshop Summary
behavior. The FDA recognized the importance of a strong evidence base from randomized clinical trials (RCTs) on which to make policy. The FDA worked with researchers at Columbia University to develop an algorithm for classifying suicidality events from case narratives in previous clinical trials. The classification tool that emerged, with the assistance of Kelly Posner of Columbia University, was C-CASA, the Columbia Classification Algorithm for Suicide Assessment (Box 1-1). Four of the algorithm’s major categories served, for the purpose of the meta-analysis, as primary outcome measures: completed suicide, suicide attempt, preparatory acts toward imminent suicidal behavior, and suicidal ideation. The FDA sought to collect and further analyze additional data beyond what drug sponsors previously submitted to them from clinical trials. The FDA’s solicitation covered all psychiatric drugs and all psychiatric indications. The FDA made a specific request for the case narratives, which would enhance the FDAs capacity to reclassify and pool the data into a meta-analysis, and used these C-CASA categories to classify trial-level and patient-level data that it required drug sponsors to submit.