Efficient Safety Assessment in Clinical Trials Using the Computer-Generated AE Narratives
Feb 20, 2017 7:29 AM
Richard C. Zink, Principal Research Statistician Developer
Drew Foglia, Principal Software Developer
ICH Guideline E3 recommends that sponsors provide narratives describing each death, serious adverse event (SAE), or significant AE of special interest to the disease under investigation. Narratives summarize the details surrounding these events to enable understanding of the circumstances that led to its occurrence and subsequent management. Ultimately, narratives may shed light on factors associated with severe events, or describe effective means for managing patients for recovery. Information contained in the typical narrative requires the medical writer to review many disparate sources. This is time consuming and often requires additional review and quality control. Further, while changes to the study database are easily reflected in statistical tables by re-running programs, changes to narratives occur manually which may result in incorrect reporting. Finally, patients with severe disease likely experience numerous SAEs; the volume of events to summarize can consume a great deal of resources. In this talk, we describe how AE narratives can be generated directly from study data sets using JMP Clinical, and discuss the benefits of automating the narrative process. Through several examples, we illustrate how various options and templates customize narratives according to researcher needs – even providing support for translation of the narrative into other languages.