Background: Standardized MedDRA Queries (SMQs) are sets of terms determined by experts that are used to identify adverse events (AEs) related to different disease processes. Their use can be challenging because most SMQs have 50 to 100 preferred terms and AE databases can have many thousands of events. Aim: The aim of this study is to develop a technique where AEs corresponding to preferred terms in SMQs may be easily detected. Methodology: The method I developed uses the Table Join function of the JMP® software program to quickly and easily probe clinical trial AE databases. The SMQ Severe cutaneous adverse reactions was used as a probe in a mock AE dataset. Potentially confounding demographic or study-specific factors were evaluated by combining these datasets with the dataset containing the AEs identified with the SMQs. Results: AEs were successfully detected in an AE database using the method described. Cases with potential confounding factors, such as concomitant medications, were identified. Conclusions: The method developed allows for AEs to be found in clinical trial databases and evaluated using software programs that are readily available to clinical researchers.
ASJC Scopus subject areas
- Pharmacology (medical)