Queries Dataset Documentation

Introduction

To support the safety analysis, it is quite common to define specific grouping of events. One of the most common ways is to group events or medications by a specific medical concept such as a Standard MedDRA Queries (SMQs) or WHO-Drug Standardized Drug Groupings (SDGs).

To help with the derivation of these variables, the {admiral} function derive_vars_query() can be used. This function takes as input the dataset (dataset) where the grouping must occur (e.g ADAE) and a dataset containing the required information to perform the derivation of the grouping variables (dataset_queries).

The dataset passed to the dataset_queries argument of the derive_vars_query() function can be created by the create_query_data() function. For SMQs and SDGs company-specific functions for accessing the SMQ and SDG database need to be passed to the create_query_data() function (see the description of the get_terms_fun argument for details).

This vignette describes the expected structure and content of the dataset passed to the dataset_queries argument in the derive_vars_query() function.

Structure of the Query Dataset

Variables

Variable	Scope	Type	Example Value
VAR_PREFIX	The prefix used to define the grouping variables	Character	"SMQ01"
QUERY_NAME	The value provided to the grouping variables name	Character	"Immune-Mediated Guillain-Barre Syndrome"
TERM_LEVEL	The variable used to define the grouping. Used in conjunction with TERM_NAME	Character	"AEDECOD"
TERM_NAME	A term used to define the grouping. Used in conjunction with TERM_LEVEL	Character	"GUILLAIN-BARRE SYNDROME"
TERM_ID	A code used to define the grouping. Used in conjunction with TERM_LEVEL	Integer	10018767
QUERY_ID	Id number of the query. This could be a SMQ identifier	Integer	20000131
QUERY_SCOPE	Scope (Broad/Narrow) of the query	Character	BROAD, NARROW, NA
QUERY_SCOPE_NUM	Scope (Broad/Narrow) of the query	Integer	1, 2, NA
VERSION	The version of the dictionary	Character	"20.1"

Bold variables are required in dataset_queries: an error is issued if any of these variables is missing. Other variables are optional.

The VERSION variable is not used by derive_vars_query() but can be used to check if the dictionary version of the queries dataset and the analysis dataset are in line.

Required Content

Each row must be unique within the dataset.

As described above, the variables VAR_PREFIX, QUERY_NAME, TERM_LEVEL, TERM_NAME and TERM_ID are required. The combination of these variables will allow the creation of the grouping variable.

Input

• VAR_PREFIX must be a character string starting with 2 or 3 letters, followed by a 2-digits number (e.g. “CQ01”).

• QUERY_NAME must be a non missing character string and it must be unique within VAR_PREFIX.

• TERM_LEVEL must be a non missing character string.

  • Each value in TERM_LEVEL represents a variable from dataset used to define the grouping variables (e.g. AEDECOD,AEBODSYS, AELLTCD).

  • The function derive_vars_query() will check that each value given in TERM_LEVEL has a corresponding variable in the input dataset and issue an error otherwise.

  • Different TERM_LEVEL variables may be specified within a VAR_PREFIX.

• TERM_NAME must be a character string. This must be populated if TERM_ID is missing.

• TERM_ID must be an integer. This must be populated if TERM_NAME is missing.

Output

• VAR_PREFIX will be used to create the grouping variable appending the suffix “NAM”. This variable will now be referred to as ABCzzNAM: the name of the grouping variable.

  • E.g. VAR_PREFIX == "SMQ01" will create the SMQ01NAM variable.

  • For each VAR_PREFIX, a new ABCzzNAM variable is created in dataset.

• QUERY_NAME will be used to populate the corresponding ABCzzNAM variable.

• TERM_LEVEL will be used to identify the variables from dataset used to perform the grouping (e.g. AEDECOD,AEBODSYS, AELLTCD).

• TERM_NAME (for character variables), TERM_ID (for numeric variables) will be used to identify the records meeting the criteria in dataset based on the variable defined in TERM_LEVEL.

• Result:

  • For each record in dataset, where the variable defined by TERM_LEVEL match a term from the TERM_NAME (for character variables) or TERM_ID (for numeric variables) in the datasets_queries, ABCzzNAM is populated with QUERY_NAME.

  • Note: The type (numeric or character) of the variable defined in TERM_LEVEL is checked in dataset. If the variable is a character variable (e.g. AEDECOD), it is expected that TERM_NAME is populated, if it is a numeric variable (e.g. AEBDSYCD), it is expected that TERM_ID is populated, otherwise an error is issued.

Example

In this example, one standard MedDRA query (VAR_PREFIX = "SMQ01") and one customized query (VAR_PREFIX = "CQ02") are defined to analyze the adverse events.

• The standard MedDRA query variable SMQ01NAM [VAR_PREFIX] will be populated with “Standard Query 1” [QUERY_NAME] if any preferred term (AEDECOD) [TERM_LEVEL] in dataset is equal to “AE1” or “AE2” [TERM_NAME]

• The customized query (CQ02NAM) [VAR_PREFIX] will be populated with “Query 2” [QUERY_NAME] if any Low Level Term Code (AELLTCD) [TERM_LEVEL] in dataset is equal to 10 [TERM_ID] or any preferred term (AEDECOD) [TERM_LEVEL] in dataset is equal to “AE4” [TERM_NAME].

Query Dataset (ds_query)

VAR_PREFIX	QUERY_NAME	TERM_LEVEL	TERM_NAME	TERM_ID
SMQ01	Standard Query 1	AEDECOD	AE1
SMQ01	Standard Query 1	AEDECOD	AE2
CQ02	Query 2	AELLTCD		10
CQ02	Query 2	AEDECOD	AE4

Adverse Event Dataset (ae)

USUBJID	AEDECOD	AELLTCD
0001	AE1	101
0001	AE3	10
0001	AE4	120
0001	AE5	130

Output Dataset

Generated by calling derive_vars_query(dataset = ae, dataset_queries = ds_query).

USUBJID	AEDECOD	AELLTCD	SMQ01NAM	CQ02NAM
0001	AE1	101	Standard Query 1
0001	AE3	10		Query 2
0001	AE4	120		Query 2
0001	AE5	130

Subject 0001 has one event meeting the Standard Query 1 criteria (AEDECOD = "AE1") and two events meeting the customized query (AELLTCD = 10 and AEDECOD = "AE4").

Optional Content

When standardized MedDRA Queries are added to the dataset, it is expected that the name of the query (ABCzzNAM) is populated along with its number code (ABCzzCD), and its Broad or Narrow scope (ABCzzSC).

The following variables can be added to queries_datset to derive this information.

Input

• QUERY_ID must be an integer.

• QUERY_SCOPE must be a character string. Possible values are: “BROAD”, “NARROW” or NA.

• QUERY_SCOPE_NUM must be an integer. Possible values are: 1, 2 or NA.

Output

• QUERY_ID, QUERY_SCOPE and QUERY_SCOPE_NUM will be used in the same way as QUERY_NAME (see here) and will help in the creation of the ABCzzCD, ABCzzSC and ABCzzSCN variables.

Output Variables

These variables are optional and if not populated in dataset_queries, the corresponding output variable will not be created:

VAR_PREFIX	QUERY_NAME	QUERY_ID	QUERY_SCOPE	QUERY_SCOPE_NUM	Variables created
SMQ01	Query 1	XXXXXXXX	NARROW	2	SMQ01NAM, SMQ01CD, SMQ01SC, SMQ01SCN
SMQ02	Query 2	XXXXXXXX	BROAD		SMQ02NAM, SMQ02CD, SMQ02SC
SMQ03	Query 3	XXXXXXXX		1	SMQ03NAM, SMQ03CD, SMQ03SCN
SMQ04	Query 4	XXXXXXXX			SMQ04NAM, SMQ04CD
SMQ05	Query 5				SMQ05NAM