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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Aggregation of Adverse Event Terms for Signal Detection and Labeling in Clinical Trials
Richard C Zink1,2, Rebecca Lyzinski3, Geoffrey Mann3
1JMP Statistical Discovery LLC, 100 SAS Campus Drive, Cary, NC, 27513, USA. richard.zink@jmp.com.
None:
The Medical Dictionary for Regulatory Activities (MedDRA) was developed in the mid-to-late 1990s to address the shortcomings of other medical dictionaries used for coding adverse events. Since that time, MedDRA has become the required coding dictionary for major regulatory authorities involved with the International Council for Harmonisation. Due to the increased specificity and significant increase in terminology over time, several approaches have been developed to aggregate terms for the purposes of signal detection and labeling. We present the approaches taken and suggested to date to aggregate preferred terms into meaningful medical concepts. We discuss the pros and cons of different methods in which to group terms, and illustrate that analyses performed for MedDRA preferred terms can also be conducted using aggregated terms. However, some features of adverse events available at the preferred term level, such as severity and relationship to study therapy, require additional consideration for analysis. In the last 25 years, the pendulum for medical coding is swinging in the other direction. Faced with a deluge of preferred terms, users of MedDRA are developing new ways in which to collapse terms into medical concepts. The ability to identify safety concerns and communicate important data in drug labels effectively and consistently are at risk, particularly with the introduction of new aggregations.
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