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1. Investigator and site identification: Companies use different methods to distinguish sites and investigators. CDISC assumes that SITEID will always be present, with INVID and INVNAM used as necessary. 
2. Every subject in a study must have a subject identifier (SUBJID). In some cases a subject may participate in more than 1 study. To identify a subject uniquely across all studies for all applications or submissions involving the product, a unique identifier (USUBJID) must be included in all datasets. Subjects occasionally change sites during the course of a clinical study. Applicants must decide how to populate variables such as USUBJID, SUBJID and SITEID based on their operational and analysis needs, but only 1 DM record should be submitted for each subject. The Supplemental Qualifiers dataset may be used if appropriate to provide additional information.
3. Concerns for subject privacy suggest caution regarding the collection of variables like BRTHDTC. This variable is included in the Demographics model in the event that an applicant intends to submit it; however, applicants should follow regulatory guidelines and guidance as appropriate.

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   With the exception of trials studies that use multistage processes to assign subjects to arms described below, ARM and ACTARM must be populated with ARM values from the Trial Arms (TA) dataset and ARMCD and ACTARMCD must be populated with ARMCD values from the TA dataset or be null. The ARM and ARMCD values in the TA dataset have a one-to-one relationship, and that one-to-one relationship must be preserved in the values used to populate ARM and ARMCD in DM, and to populate the values of ACTARM and ACTARMCD in DM.
   1. Rules for the arm-related variables: 
      1. If ARMCD is null, then ARM must be null and ARMNRS must be populated with the reason ARMCD is null.
      2. If ACTARMCD is null, then ACTARM must be null and ARMNRS must be populated with the reason ACTARMCD is null. Both ARMCD and ACTARMCD will be null for subjects who were not assigned to an arm. The same reason will provide the reason that both are null.
      3. ARMNRS may not be populated if both ARMCD and ACTARMCD are populated. ARMCD and ACTARMCD will be populated if the subject was assigned to an arm and received exposure consistent with 1 of the arms in the TA dataset. If ARMCD and ACTARMCD are not the same, that is sufficient to explain the situation; ARMNRS should not be populated.
   2. Multistage assignment to an arm: Some trials studies use a multistage process for assigning a subject to an arm. In such a case, best practice is to create ARMCD values composed of codes representing the results of the multiple stages of the are assignment process. If a subject is partially assigned, then truncated codes representing the stages completed can be used in ARMCD, and similar truncated codes can be used in ACTARMCD. The descriptions used to populate ARM and ACTARM should be similarly truncated, and the one-to-one relationship between these truncated codes should be maintained for all affected subjects in the trialstudy. Note that this use of values not in the TA dataset is allowable only for trials studies with multistage assignment to arms and to subjects in those trials studies who do not complete all stages of the assignment.
5. Study population flags should not be included in SDTM data. The ADaM Subject-level Analysis Dataset (ADSL) specifies standard variable names for the most common populations and requires the inclusion of these flags when necessary for analysis.
6. Race and ethnicity will be represented per regulatory requirements. Submission of multiple race responses should be represented in the Demographics (DM) domain and Supplemental Qualifiers (SUPPDM) dataset. If multiple races are collected, then the value of RACE should be “MULTIPLE” and the additional information will be included in the Supplemental Qualifiers dataset. Controlled terminology for RACE should be used in both DM and SUPPDM so that consistent values are available for summaries regardless of whether the data are found in a column or row. If multiple races were collected and 1 was designated as primary, RACE in DM should be the primary race and additional races should be reported in SUPPDM. For subjects who refuse to provide or do not know their race information, the value of RACE could be “UNKNOWN”.
7. RFSTDTC, RFENDTC, RFXSTDTC, RFXENDTC, RFCSTDTC, RFCENDTC, RFICDTC, RFPENDTC, DTHDTC, and BRTHDTC represent date/time values, but they are considered to have a record qualifier role in DM. They are not considered to be timing variables because they are not intended for use in the general observation classes.
8. Additional permissible identifier, qualifier, and timing variables:
   1. Only the following timing variables are permissible and may be added as appropriate: VISITNUM, VISIT, VISITDY. The record qualifier DMXFN (External File Name) is the only additional qualifier variable that may be added, which is adopted from the Findings general observation class, may also be used to refer to an external file, such as a patient narrative.
   2. The order of these additional variables within the domain should follow variable order in the SDTM.
9. RFSTDTC is used to calculate study day variables. RFSTDTC is usually defined as the date/time when a subject was first exposed to study product.
10. The DM domain contains several pairs of reference period variables: RFSTDTC and RFENDTC, RFXSTDTC and RFXENDTC, RFCSTDTC and RFCENDTC, and RFICDTC and RFPENDTC. There are 4 sets of reference variables to accommodate distinct reference-period definitions and there are instances when the values of the variables may be exactly the same, particularly with RFSTDTC-RFENDTC and RFXSTDTC-RFXENDTC.
    1. RFSTDTC and RFENDTC: This pair of variables is applicant-defined, but usually represents the date/time of first and last study exposure. However, there are certain study designs where the start of the reference period is defined differently, such as studies that have a washout period. In these cases, RFSTDTC may be the enrollment date, which is prior to first exposure. Because study day values are calculated using RFSTDTC, in this case study days would not be based on the date of first exposure.   
    2. RFXSTDTC and RFXENDTC: This pair of variables defines a consistent reference period for all studies and is not open to customization. RFXSTDTC and RFXENDTC always represent the date/time of first and last study exposure. This reference period often duplicates the reference period defined in RFSTDTC and RFENDTC, but not always. Therefore, this pair of variables is important as they guarantee that a reviewer will always be able to reference the first and last study exposure reference period. RFXSTDTC should be the same as SESTDTC for the first element described in the SE dataset. RFXENDTC may often be the same as the SEENDTC for the last element described in the SE dataset.
    3. RFICDTC and RFPENDTC: The definitions of this pair of variables are consistent in every study in which they are used: They represent the entire period of a subject’s involvement in a study, from providing informed consent through the last participation event or activity. There may be times when this period coincides with other reference periods but that is unusual. RFICDTC should correspond to the date of the informed consent protocol milestone in Disposition (DS), if that protocol milestone is documented in DS. In the event that there are multiple informed consents, this will be the date of the first. RFPENDTC will be the last date of participation for a subject for data included in a submission. This should be the last date of any record for the subject in the database at the time it is locked for submission. As such, it may not be the last date of participation in the study if the submission includes interim data.