CDISC data standards

Under construction

CDISC stands for Clinical Data Interchange Standards Consortium. CDISC provides several interrelated standards, each addressing a specific stage of the data lifecycle Figure 1. Each standard has an Implementation Guide (IG) that shows exactly how to apply that standard practically, e.g. SDTMIG for SDTM. All the implementations have version numbers that are important to keep track of.

CDISC also provides TAUGs (Therapeutic Area User Guides). A TAUG is a document providing guidance on applying CDISC standards to a specific therapeutic area (oncology, diabetes, CNS, etc.).

Figure 1

CDASH

CDASH (Clinical Data Acquisition Standards Harmonization) standardizes how data are entered into case report forms (CRFs) at clinical sites.

SDTM

SDTM (Study Data Tabulation Model) organizes the data from CDASH into submission-ready datasets. It includes different domains/datasets (e.g., exposure, and lab-values) and controlled terminology (e.g., how to name variables).

General Observation Classes

General Observation Classes are high-level classifications within SDTM that group domains based on the type of data they contain.

There are three general observation classes: Interventions, Events, and Findings. There is also a fourth observation class: Special purpose.

Observation classes are then grouped into domains, organized around a particular topic. Each “domain” is usually a separate dataset; for example, EX can be a dataset containing exposure (dosing) data. However, a domain can also be split into multiple datasets. A typical example is splitting the Laboratory Test Results (LB) domain due to size.

Table 1: General observation classes in SDTM.

Observation Class	Domain Name	Domain Abbreviation
Interventions	Procedure agents	AG
	Concomitant/prior medications	CM
	Exposure	EX
	Exposure as collected	EC
	Meal data	ML
	Procedures	PR
	Substance use	SU
Events	Adverse events	AE
	Biospecimen events	BE
	Clinical events	CE
	Disposition	DS
	Healthcare encounters	HO
	Medical history	MH
	Protocol deviations	DV
Findings	Product/drug accountability	DA
	Death details	DD
	ECG test results	EG
	Inclusion/Exclusion criteria not met	IE
	Biospecimen findings	BS
	Cell phenotype findings	CP
	Genomics findings	GF
	Immunogenicity specimen assessments	IS
	Laboratory test results	LB
	Microbiology specimen	MB
	Microbiology susceptibility	MS
	Microscopic findings	MI
	PK concentrations	PC
	PK parameters	PP
	Morphology	MO
	Cardiovascular system findings	CV
	Musculoskeletal system findings	MK
	Nervous system findings	NV
	Ophthalmic examinations	OE
	Reproductive system findings	RP
	Respiratory system findings	RE
	Urinary system findings	UR
	Physical examination	PE
	Functional tests	FT
	Questionnaires	QS
	Disease response and clinical classification	RS
	Subject characteristics	SC
	Subject status	SS
	Tumor/lesion identification	TU
	Tumor/lesion results	TR
	Vital signs	VS
	Findings about events or interventions	FA
	Skin response	SR
Special Purpose	Comments	CO
	Demographics	DM
	Subject elements	SE
	Subject disease milestones	SM
	Subject visits	SV

SDTM variables

Variables are classified as required, expected, or permissible for each domain.

Identifier

• STUDYID
• DOMAIN
• USUBJID
• –SEQ

Topic

Contain the focus of the observation.

• –TRT
• –TERM
• –TESTCD

Qualifier

Qualifiers provide additional information about the topic variables.

• Grouping
• Result
• Synonym
• Record
• Variable

Timing

Describes the timing of the observation.

• Date/times
• Study days
• Durations
• Intervals
• Visits
• Time points
• Relative times

ADaM

ADaM (Analysis Data Model) takes SDTM data and transforms it into datasets suitable for statistical analysis. It contains derived datasets used for tables, listings, figures. Like SDTM it is organized into different domains/datasets, each with its specific setup.

https://www.cdisc.org/system/files/members/standard/foundational/ADaMIG_v1.3.pdf

ADaM Standard data structures

• ADSL: Subject-level analysis dataset
  • One record per subject
• BDS: Basic data structure
  • One (or more) record per subject/parameter/timepoint
• OCCDS: Occurrence data structure
  • Designed for counting occurrences
• ADaM Other data structure

ADaM variable conventions

General variable conventions

All ADaM variable names must be no more than 8 characters in length, start with a letter (not underscore), and be composed only of letters (A–Z), underscore ( _ ), and numerals (0–9).

ADaM adheres to a principle of harmonization known as “same name, same meaning, same values.”

Generally, suppose an SDTM character variable is converted to a numeric variable in an ADaM dataset. In that case, it should be named as it is in the SDTM dataset with an “N” suffix added.

In a pair of corresponding variables (e.g., TRTP and TRTPN), the primary or most commonly used variable does not have the suffix or extension (i.e., N for numeric or C for character). The relevant suffix is used only on the name of the secondary member of the variable pair.

Variables whose names end in FL are character flag (or indicator) variables.

Variables whose names end in GRy, Gy, or CATy are grouping variables, where “y” refers to the grouping scheme or algorithm (not the category within the grouping).

It is recommended that producer-defined grouping or categorization variables begin with the name of the variable being grouped and end in GRy (e.g., variable ABCGRy is a character description of a grouping or categorization of the values from the ABC variable for analysis purposes).

Timing variable conventions

Variables whose names end in DT are numeric dates.

Variables whose names end in DTM are numeric datetimes.

Variables whose names end in TM are numeric times.

Names of timing start variables end with an S followed by the characters indicating the type of timing (i.e., SDT, STM, SDTM).

Names of timing end variables end with an E followed by the characters indicating the type of timing (i.e., EDT, ETM, EDTM)

Variables whose names end in DY are relative day variables.

Variable naming fragments

Fragment	Notes
GRy	Grouping variables
Gy	Abbreviation of GRy
FL	Flag/indicator
DT	Numeric date
TM	Numeric time
DTM	Numeric datetime
DTF	Date imputation flag
TMF	Time imputation flag
DY	Relative days (does not include day 0)

Fragment	Notes
BL	Baseline
CHG	Change
FU	Follow-up
OT	On treatment
RU	Run-in
SC	Screening
TA	Taper
TI	Titer
U	Units
WA	Washout

ADSL variables

Variable	Notes

Variable	Notes

BDS variables

Analysis-enabling variables

SEND

SEND (Standard for Exchange of Nonclinical Data) mirrors SDTM but for non-clinical (animal) studies, describing how data is organized.