A Pragmatic Method to Integrate Data from Pre-existing Cohort Studies using the Clinical Data Interchange Standards Consortium (CDISC) Study Data Tabulation Model: Practical use of REDCap2SDTM.

ABSTRACT

BACKGROUND: In recent years, many researchers have focused on legacy data utilization, such as pooled analyses that collect and re-analyze data from multiple studies. However, the methodology for the integration of pre-existing databases whose data were collected for different purposes has not been established. Previously, we developed a tool to efficiently generate Study Data Tabulation Model (SDTM) data from hypothetical clinical trial data using the Clinical Data Interchange Standards Consortium (CDISC) SDTM. OBJECTIVE: To design a practical model for integrating pre-existing databases using the CDISC SDTM. METHODS: Data integration was performed in three phases i) confirmation of the variables, ii) SDTM mapping, and iii) generation of the SDTM data. In phase 1, the definitions of the variables in detail were confirmed, and the datasets were converted to vertical datasets. In phase 2, the items derived from the SDTM format were set as mapping items. Three types of metadata (domain name, variable name, and test code), based on the CDISC SDTM, were embedded in the REDCap field annotation. In phase 3, the data dictionary, including the SDTM metadata, were output in the Operational Data Model (ODM) format. Finally, the mapped SDTM were generated using REDCap2SDTM v2. RESULTS: SDTM data were generated as a comma-separated values file for each of the seven domains defined in the metadata. Twenty-two items were commonly mapped to three databases. Because the SDTM data were set in each database correctly, we were able to integrate three independently pre-existing databases into one database in the CDISC SDTM format. CONCLUSIONS: Our project suggests that the CDISC SDTM is useful for integrating multiple pre-existing databases.