The Supplemental Qualifiers (SUPP--) special purpose dataset model is used to represent both nonstandard variables (NSVs) and attributions with their relationship to records in a parent dataset. SUPP-- datasets will only be used with datasets based on the general-observation classes described in the SDTM (Events, Findings, Interventions) and Demographics (DM).
There will be only one SUPP-- dataset for a parent dataset. Relationships between records in the SUPP-- dataset and observations in the parent dataset are specified using the key variables STUDYID, RDOMAIN (the domain code of the observation in the relationship), USUBJID or POOLID (for nonclinical studies only), along with IDVAR (the variable that identifies the related observation) and IDVARVAL (the value of the identifying variable). IDVARVAL will contain the value of the variable described in IDVAR. Single records can be related by using a unique-record-identifier variable, such as --SPID or --SEQ, in IDVAR. Groups of records can be related by using grouping variables such as --GRPID in IDVAR. Using --GRPID can be a more efficient method of representing relationships when relating an NSV or attribution to a group of observations in the parent dataset.
Variable QORIG represents where values represented in IDVARVAL originated (e.g., a value was collected via CRF). QORIG be populated with origin types for SDTM datasets described in the CDISC Define-XML standard.
Nonstandard Variables
SUPP-- represents the metadata and data for each NSV/value combination and relates this to the observation or observations qualified by the NSV in the parent dataset. The name, label, and value of the NSV are represented in SUPP-- dataset variables QNAM, QLABEL, and QVAL respectively. The origin of the NSV value will be represented in variable QORIG. When the value of an NSV is assigned, variable QEVAL will represent the role of the individual or individuals who assigned the value.
Attributions
An attribution is typically an interpretation or subjective classification of 1 or more observations by a specific evaluator. A SUPP-- dataset can contain both objective data (where values are collected or derived algorithmically) and subjective data (attributions where values are assigned by a person or committee). A variable name, label, and value for the attribution are represented in SUPP-- dataset variables QNAM, QLABEL, and QVAL respectively. The origin for the attribution will be represented in variable QORIG. For objective data, the value in QEVAL will be null. For subjective data, the value in QEVAL should reflect the role of the person assigning the value.
For Interventions and Events general observation class domains, all subjective data are assumed to be attributed to the investigator. For observations that have primary and secondary evaluations of specific qualifier variables, applicants should put data from the primary evaluation into the parent dataset and data from the secondary evaluation into the Supplemental Qualifier datasets (SUPP--). Within each SUPP-- record, the value for QNAM should be formed by appending a "1" to the corresponding standard domain variable name. In cases where the standard domain variable name is already 8 characters in length, applicants should replace the last character with a "1" (incremented for each additional attribution).
Overview
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