The CDISC Analysis Data Model Implementation Guide (ADaMIG) provides several timing variables for modeling clinical trial designs in analysis datasets. APHASE, APERIOD, and ASPER can be used in conjunction with related treatment variables to meet a variety of analysis requirements, from single-period parallel studies to much more complicated situations involving multiple treatment periods and even different studies. The goal of this article is to provide guidelines for identifying when to use the different timing variables that are available. Additional examples can be found in the References and Resources listed at the end of the article.
This article aims to clarify and establish a shared understanding of the recommended CDISC approach for identifying CDISC Biomedical Concepts (BCs) within a defined group of interest, with particular emphasis on Questionnaires, Ratings, and Scales (QRS) instruments.
The ADaMIG provides multiple ways to categorize and flag values to be analyzed. These ways may seem overlapping, and the most appropriate set of variables for a particular analysis may not be obvious to the user. This article is intended to provide some clarity on how to use appropriate variables and how to select the appropriate analysis variables.
The SDTM Implementation Guide for Associated Persons (SDTMIG-AP) v1.0 provides guidance on how to include data collected about persons who are not the study subjects in SDTM. However, the ADaM Implementation Guide has not provided guidance regarding how to include data from SDTM AP-- domains in ADaM datasets if needed for analysis.
In an events or interventions domain, the variable --PRESP = "Y" can be used to indicate that the value in the topic variable (--TERM or --TRT) was pre-specified. However, --PRESP is not a variable that is allowed in findings domains.
In some cases, the reason for the restriction is fairly obvious, but in other cases, understanding the reason requires understanding the differences between how human clinical trials and nonclinical trials are conducted.
CDISC has published the first of a new kind of QRS supplement to the SDTMIG, a supplement for an oncology response criterion, Response Evaluation Criteria in Solid Tumors Version 1.1 (RECIST 1.1).
This article provides information on the ISO international standard for country codes is ISO-3166, which provides several representations of names for countries (ISO-3166-1) and their subdivisions (ISO-3166-2).
This article was written to explain why there are so many Analysis Data Model (ADaM) documents and to help the ADaM user see how they have been designed to work together.
The current Immunogenicity Specimen Assessments (IS) domain in the SDTMIG v3.4 is designed to represent data pertaining to specimen-based assessments that measure the “presence, magnitude and scale of the immune response upon an antigen stimulation or encounter.” Not only does the new domain definition better align with the scientific definition of “immunogenicity”, but it also expands the scope of the IS domain from the previous versions of SDTMIG (i.e., v3.2 and v3.3), where the IS domain was defined to represent data pertaining to “assessments that describe whether a therapy provoked/caused/induced an immune response”.
Therapeutic Area User Guides (TAUGs) contain many useful examples, but it can be hard to find a useful example since there are over 40 TAUGs, and many TAUGs include examples that are useful outside a particular therapeutic area. The spreadsheet classifies TAUG examples by domain, so if a user has data that would be represented in a particular domain, the spreadsheet can identify TAUGs that might have examples relevant to their data.
When the Guidance for Ongoing Studies Disrupted by COVID-19 was being developed, one of the issues was how to represent subject visits, given that regulators wanted to know about visits that were missed or modified due to the pandemic.
The CDASHIG section "PE - Physical Examination" describes a best practice for collecting physical examination data. Basically, any abnormalities would be recorded as medical history or adverse events, depending on timing whether an exam was performed would be recorded by treating the exam as a procedure.
This article provides a good example for documenting study subject site transfers, using existing SDTMIG domains and minimal supplemental qualifiers. Originally modeled for COVID studies, this approach could be used any time a study subject change sites during their participation in the study.