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.
A single person may participate in a study multiple times. A common scenario for multiple participations is when a screening failure subject later goes through the screening process again in another attempt to enroll. There are also studies where a subject may participate more than once with more than 1 body part, such as a subject who participates with the left eye, and then enrolls again with the right eye. Some studies of rare diseases allow a subject to participate in and complete a study, and then later participate again. Subjects may receive different treatments in these different participations.
If the safety analysis will report adverse events, clinical events, or laboratory grading according to a standard toxicity grading scale (e.g., Common Terminology Criteria for Adverse Events, CTCAE), then analysis toxicity variables should be implemented. These toxicity variables may be copied directly from SDTM as predecessor variables or they may be imputed or assigned based on the statistical analysis plan and sponsor requirements.
If an analysis is assessing low toxicity separately from high toxicity, then bidirectional toxicity variables should be used in the ADaM dataset. Toxicity variable ATOXGR may be used in addition to the bidirectional toxicity variables to capture shifts from low to high or high to low within a parameter. The low and high toxicity grade variables may be copied directly from SDTM as predecessor variables or they may be imputed or assigned based on the statistical analysis plan and sponsor requirements (e.g., unidirectional toxicity variables).
Unified Code for Units of Measure (UCUM) was developed by Regenstrief Institute and the UCUM Organization as an unambiguous system of units and their combinations. UCUM is intended to include all units of measure currently used internationally in science, engineering and business and has been adopted internationally by IEEE, DICOM, LOINC, and HL7, and is also in the ISO 11240:2012 standard.
LOINC is a pre-coordinated laboratory coding system used in healthcare IT systems. It includes lab tests, clinical measures, HIPAA documents and standardized survey instruments. It also contains terms for human clinical research but its scope goes beyond research use. LOINC is used in over 170 countries and is mandated in 30.
SDTM describes several types of datasets. This diagram illustrates hierarchical view of these types of datasets. Findings may be findings about a study subject or about an associated person. A finding record can be linked to supplemental qualifiers, to comments, or to other records via relationships represented in RELREC.
A query about adverse events is, at heart, an observation. Data on the adverse event may also include location and pattern. This concept map includes those details, as well as terminology that would be used in SDTM.
A substance administration consists of a substance and the activity of administering the substance. Some data items describe the substance, others the administration.
This is an example for the familiar test Temperature.
If data is collected in a log form, and if you know the range of dates or visits for collection of log data then The date or visit at which the log is initiated can be used to populate STTPT and CDASH PRIOR or ONGO can be used to populate STRTPT, The date or visit at which the log is finalized can be used to populate ENTPT and CDASH PRIOR or ONGO can be used to populate ENRTPT. STRF and ENRF are not needed and should not be used.