Presence or Absence of Prespecified Interventions and Events in Clinical Studies
In clinical research, the collection of data on interventions (e.g., concomitant medications) and events (e.g., medical history) can be approached in two primary ways: recording verbatim free text or using a prespecified list of treatments or terms. The method chosen can significantly impact the frequency and accuracy of reported data, making it crucial for reviewers to understand whether the data was prespecified.
The –PRESP variable is used to indicate if a specific intervention (–TRT) or event (–TERM) was solicited. This variable uses controlled terminology of “Y” (Yes) or a null value and should only be used when the topic variable values come from a prespecified list. For example, questions like “Did the subject have any concomitant medications?” or “Did the subject have any medical history?” should not have records in an SDTM domain, as these are not valid values for the respective topic variables of CMTRT and MHTERM.
The –OCCUR variable indicates whether a prespecified intervention or event occurred, using “Y” (Yes) and “N” (No). This variable is permissible and may be omitted if no topic-variable values were prespecified. When both prespecified and free-text events and interventions are collected, --OCCUR should be “Y” or “N” for all prespecified items and null for those reported as free text.
Additionally, the –STAT and --REASND variables provide information about prespecified interventions and events for which there is no response, such as when an investigator forgot to ask. The --STAT variable uses controlled terminology of NOT DONE.
Recommended by LinkedIn
Understanding these variables and their proper usage is essential for accurate data collection and analysis in clinical studies.
#ClinicalResearch #DataCollection #ClinicalTrials #MedicalResearch #HealthcareData #ClinicalData #ResearchMethods #DataAccuracy #ClinicalStudy #PharmaceuticalResearch #MedicalInterventions #HealthData #ClinicalVariables #DataManagement #ResearchInnovation #Healthcare #MedicalScience #ClinicalDevelopment #DataIntegrity #ClinicalOperations #LinkedInArticle #ResearchCommunity #HealthcareInnovation #ClinicalInsights #MedicalData #sdtm
Statistical Programmer
1moWow, love this. Beautifully explained
Yes, rightly mentioned 👍