| Num | Record and Variable Population | Implementation |
|---|
| 1 | Multiple values |
Multiple Values | for an Intervention or Event |
Topic Variable| topic variable | Product Impact on Individual Health only: If multiple values are reported for an |
intervention or event Intervention or Event general-observation class topic variable (e.g., --TRT in |
an Interventions general observation-class dataset or - an general observation-class dataset it is expected that the sponsor then the applicant will split the values into multiple records or otherwise resolve the multiplicity per the |
sponsor's data management standard operating procedures (e.g. |
For example if an adverse event term of "Headache and nausea" or a concomitant medication of "Tylenol and Benadryl" is reported, sponsors will often split the original report into separate records and/or query the site for clarification. By the time of submission, datasets should be in conformance with the record structures described in the SDTMIG.Note: The query the data for clarification). - The Disposition (DS) dataset is an exception to the general rule of splitting multiple topic values into separate records. For DS, 1 record for each disposition or protocol milestone
|
is permitted according to the domain structure- . For cases of multiple reasons for discontinuation
|
see Section 6.2.4, Disposition, assumption 5 for additional information. | | 2 | Multiple values for a Findings result variable |
Multiple Values for a Findings Result Variable | If multiple result values (represented in --ORRES) are |
reported in a Findings class dataset should submitted for that represented for the test (represented in --TESTCD). |
For example,- EGTESTCD = "SPRTARRY", EGTEST = "Supraventricular Tachyarrhythmias", EGORRES = "ATRIAL FIBRILLATION"
- EGTESTCD = "SPRTARRY", EGTEST = "Supraventricular Tachyarrhythmias", EGORRES = "ATRIAL FLUTTER"
When a finding can have multiple results, the key structure for the findings dataset must be adequate to distinguish between the multiple results. See Section 4.1.9, Assigning Natural Keys in the Metadata. | | 3 | Multiple values for a variable with role: - Grouping qualifier
- Synonym qualifier
- Record qualifier
- Variable qualifier
| Product Impact on Individual Health only: For multiple values |
Multiple Values for a Non-result Qualifier Variable | The SDTM permits 1 value for each qualifier variable per record. If multiple values exist (e.g., due to a "Check all that apply" instruction on a CRF) |
, then the value for the qualifier variable should be : - The variable will be populated with "MULTIPLE"
|
and should be used to store the individual responses. It is recommended that the SUPP-- QNAM value reference the corresponding standard domain variable with an appended number or letter. In some cases, the standard variable name will be shortened to meet the 8-character variable name requirement, or it may be clearer to append a meaningful character string as shown in the second Adverse Events (AE) example below, where the first 3 characters of the drug name are appended. Likewise, the QLABEL value should be similar to the standard label. The values stored in QVAL should be consistent with the controlled terminology associated with the standard variable. See Section 8.4, Relating Non-standard Variable Values to a Parent Domain, for additional guidance on maintaining appropriately unique QNAM values.The following example includes selected variables from the ae.xpt and suppae.xpt datasets for a rash with locations on the face, neck, and chest.In some cases, values for QNAM and QLABEL more specific than these may be needed.For example, a sponsor might conduct a study with 2 study drugs (e.g., open-label study of Abcicin + Xyzamin), and may require the investigator assess causality and describe action taken for each drug for the rash:In each of these examples, the use of SUPPAE should be documented in the Define-XML document and the annotated CRF. The controlled terminology used should be documented as part of value-level metadata.If the sponsor has clearly documented that one response is of primary interest (e.g., in the CRF, protocol, or analysis plan), the standard domain variable may be populated with the primary response and SUPP-- may be used to store the secondary response(s). For example, if Abcicin is designated as the primary study drug in the example above:Note that in the latter case, the label for standard variables AEREL and AEACN will have no indication that they pertain to Abcicin. This association must be clearly documented in the metadata and annotated CRF.Multiple Values for a Parameter | f multiple values (--VAL) are reported for a parameter in a Trial Design or Study Reference dataset (e.g., TS, OI), multiple records should be submitted for that --PARMCD.
For example, - TSPARMCD = "TTYPE", TSPARM = "Trial Type", TSVAL = "EFFICACY"
- TSPARMCD = "TTYPE", TSPARM = "Trial Type", TSVAL = "SAFETY"
When a parameter can have multiple values, the key structure for the dataset must be adequate to distinguish between the multiple records. See Section 4.1.9, Assigning Natural Keys in the Metadata.- dataset will represent individual responses.
- The values for QNAM will be sequential variable names, formed by appending a 1-digit integer, beginning with 1, to the original domain variable name. In cases where the standard domain variable name is already 8 characters in length, applicants will replace the last character with a digit when creating values for QNAM.
- The value for QLABEL should be the original domain variable label for all QNAM values.
| | 4 | Multiple values for a parameter | If multiple values (--VAL) are reported for a parameter in a Trial Design dataset (e.g., TS), multiple records should be submitted for the --PARMCD, unless the CDISC notes for the parameter indicate otherwise (e.g., TXPARMCD=LIGHT) | | 5 | Single concept represented by multiple values | Nonclinical only: - A single value may represent a combination of multiple contributing items, delimited by slashes ("/"). In such cases, the combination is the collected value, the value analyzed, and so on—not the individual contributing items composing the value.
- When controlled terminology applies to the variable, the combination of concepts may already exist as a controlled terminology term. If this is not the case, then a new term will be constructed by combining existing controlled terms, when possible.
- For example, DEGENERATION/REGENERATION is a microscopic finding that is a single concept represented by multiple values (which is different from having 2 separately collected findings of degeneration and regeneration, with 2 separate records respectively).
| | 6 | Multiple concepts represented by multiple values | Nonclinical only: - A variable value may represent multiple individual values. In such cases, each contributing value is a separately collected or analyzed item.
- When controlled terminology applies to the variable, controlled terms for each value will be represented delimited by semicolons.
- For example, multiple distinct values may be collected for directionality (--DIR), may be collected for a result. Values may be represented using controlled terminology as "VENTRAL;SURFACE".
|
|