CDISC-compliant clinical trial imaging management system with automatic verification and data Transformation: Focusing on tumor response assessment data in clinical trials

• Published in: Journal of biomedical informatics Vol. 117; p. 103782
• Main Authors: Lee, Amy Junghyun, Kim, Kyung Won, Shin, Youngbin, Lee, Jiwoo, Park, Hyo Jung, Cho, Young Chul, Ko, Yousun, Sung, Yu Sub, Yoon, Byung Sun
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.05.2021
• Subjects: CDISC; Clinical trial; Clinical Trials as Topic; CTIMS; Humans; Medical Informatics; Neoplasms - diagnostic imaging; RECIST; SDTM; Software; CDISC; Clinical trial; CTIMS; RECIST; SDTM
• ISSN: 1532-0464; 1532-0480
• DOI: 10.1016/j.jbi.2021.103782

[Display omitted] •CDISC standards are essential to standardize clinical trial datasets and submit to regulatory agencies.•Tumor response assessment criteria such as RECIST has been widely used as imaging endpoints in oncologic trials.•Automatic verification and transformation modules were developed and implemented into existing CTIMS.•This CTIMS generated SDTM dataset for tumor assessments of clinical trial. Major issues in imaging data management of tumor response assessment in clinical trials include high human errors in data input and unstandardized data structures, warranting a new breakthrough IT solution. Thus, we aim to develop a Clinical Data Interchange Standards Consortium (CDISC)-compliant clinical trial imaging management system (CTIMS) with automatic verification and transformation modules for implementing the CDISC Study Data Tabulation Model (SDTM) in the tumor response assessment dataset of clinical trials. In accordance with various CDISC standards guides and Response Evaluation Criteria in Solid Tumors (RECIST) guidelines, the overall system architecture of CDISC-compliant CTIMS was designed. Modules for standard-compliant electronic case report form (eCRF) to verify data conformance and transform into SDTM data format were developed by experts in diverse fields such as medical informatics, medical, and clinical trial. External validation of the CDISC-compliant CTIMS was performed by comparing it with our previous CTIMS based on real-world data and CDISC validation rules by Pinnacle 21 Community Software. The architecture of CDISC-compliant CTIMS included the standard-compliant eCRF module of RECIST, the automatic verification module of the input data, and the SDTM transformation module from the eCRF input data to the SDTM datasets based on CDISC Define-XML. This new system was incorporated into our previous CTIMS. External validation demonstrated that all 176 human input errors occurred in the previous CTIMS filtered by a new system yielding zero error and CDISC-compliant dataset. The verified eCRF input data were automatically transformed into the SDTM dataset, which satisfied the CDISC validation rules by Pinnacle 21 Community Software. To assure data consistency and high quality of the tumor response assessment data, our new CTIMS can minimize human input error by using standard-compliant eCRF with an automatic verification module and automatically transform the datasets into CDISC SDTM format.