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ADaM Implementation Guide: It’s Almost Here.  Are You Ready?. Sandra Minjoe Principal Statistical Programmer Analyst Genentech, Inc. Outline. Purposes for Analysis Datasets and ADaM Major Sections of ADaM IG Basic ADaM structure ADSL Timing of IG Release.

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adam implementation guide it s almost here are you ready

ADaM Implementation Guide: It’s Almost Here.  Are You Ready?

Sandra Minjoe

Principal Statistical Programmer Analyst

Genentech, Inc

ADaM IG, May 2008

outline
Outline
  • Purposes for Analysis Datasets and ADaM
  • Major Sections of ADaM IG
    • Basic ADaM structure
    • ADSL
  • Timing of IG Release

ADaM IG, May 2008

purposes for analysis datasets
Purposes for Analysis Datasets
  • Combine data needed for specific analysis(es)
    • Imputed data
    • Target windows
    • Selection Flags
  • Allow “One Proc Away” Analysis
    • Generated with minimal programming
  • Allow alternate analysis(es) and exploration

ADaM IG, May 2008

other needs for analysis datasets
Other Needs for Analysis Datasets
  • Provide information
    • How to appropriately use data
    • How to replicate results and explore alternate analyses
  • Convey traceability
    • How variables and observations were derived

ADaM IG, May 2008

purposes of adam
Purposes of ADaM
  • Combine data across domains
  • Provide derived data
    • Variables and observations used for statistical analyses
  • Provide metadata
    • Explain the analysis and results
  • Provide traceability
    • Back to collected data

ADaM IG, May 2008

adam and reviewers
ADaM and Reviewers
  • ADaM helps the reviewer trace:
    • What you said you would do
    • What you did
    • Why they are different
  • Traceability is important
    • Does NOT replace communication with FDA

ADaM IG, May 2008

major sections of adam ig
Major Sections of ADaM IG

ADaM IG, May 2008

major sections of adam ig1
Major Sections of ADaM IG
  • ADaM Data Structure
  • Standard ADaM Metadata
    • Categories of variables
    • ADSL
  • Implementation Issues & Solutions
    • Columns vs. Rows
    • Examples

ADaM IG, May 2008

basic adam structure
Basic ADaM Structure
  • A vertical structure
    • One record per subject per analysis parameter per analysis time point
  • Includes observations for
    • Observed values
    • Derived values required for analysis
  • Value-level metadata is needed
  • Allows flexibility
  • Predictable structure

ADaM IG, May 2008

categories of variables
Categories of Variables
  • Subject Identifiers
  • SDTM Identifiers
  • ADaM Timing Identifiers (e.g. AVISIT)
  • ADaM Parameter Identifiers (e.g. PARAM)
  • ADaM Analysis Values (e.g. AVAL)
  • Analysis Enabling Variables (e.g. ANLFL, TRTP)
  • Supportive Variables (e.g. --SEQ)

ADaM IG, May 2008

slide12
ADSL
  • Subject Level Analysis Data
  • Required if any ADaM data is submitted

ADaM IG, May 2008

adsl content
ADSL Content
  • Contains basic subject information
    • Demographic, baseline, disposition data
    • Used as source for these variables in other analysis datasets
  • Has standard names and attributes
    • Tools can be built to use it
  • Use it for Baseline and Disposition table programming

ADaM IG, May 2008

adsl structure
ADSL Structure
  • Structure: 1 record per subject
    • Regardless of trial design
  • Allows simple merging with any other dataset
    • Even SDTM
  • Use it for population denominators

ADaM IG, May 2008

what goes into adsl
What goes into ADSL
  • Required variables
    • Study identifiers
    • Subject demographics
    • Population indicator(s)
    • Treatment variables
    • Trial dates
  • Permissible variables
    • Numeric equivalents of flags
    • Stratification variables
    • Treatment duration and compliance variables
    • Other key visit dates and durations
    • Protocol specific event information, such as death/survival

ADaM IG, May 2008

required adsl category study identifiers
Required ADSL Category: Study Identifiers
  • Required variables: Likely from the SDTM DM domain
    • STUDYID
    • USUBJID
    • SITEID
  • Optional study-specific identifiers, e.g:
    • SITEGRP (pooled group of sites used for analysis)

ADaM IG, May 2008

required adsl category subject demographics
Required ADSL Category:Subject Demographics
  • Required variables: Likely from the SDTM DM domain
    • AGE
    • SEX
    • RACE
  • Optional study-specific identifiers, e.g.:
    • AGEGRP (age group)
    • RACEGRP (race group)

ADaM IG, May 2008

required adsl category population indicator s
Required ADSL Category:Population Indicator(s)
  • Required variables:
    • At least one flag
    • Flag for each population defined in SAP
    • Character flag is required
      • Numeric flags can be included
  • Some common example flags:
    • FASFL (full analysis set)
    • ITTFL (intent-to-treat population)
    • PPROTFL (per-protocol population)
    • SAFFL (safety population)

ADaM IG, May 2008

population indicators conversions between sdtm adam
Population Indicators:Conversions between SDTM & ADaM

* Include only population flag(s) needed for analysis

ADaM IG, May 2008

required adsl category treatment variables
Required ADSL Category:Treatment Variables
  • Required variables:
    • ARM (planned arm)
    • TRTP (planned treatment)
  • Optional study-specific variables, e.g.:
    • TRTA (actual treatment)
    • Use when subject received something other than planned treatment
  • TRTxA and TRTxP
    • Used instead of TRTA and TRTP
    • For when multiple treatment regimens are assigned, e.g., cross-over design

ADaM IG, May 2008

required adsl category trial dates
Required ADSL Category:Trial Dates
  • Required SDTM variables
    • RFSTDTC and RFENDTC
    • Retained for reference, traceability
  • Required numeric dates
    • RANDDT (if trial is randomized)
    • TRTSTDT (Date of 1st treatment start)
    • TRTENDT (Date of last treatment end)
    • Format to be human-readable
  • If appropriate, instead use
    • TRTxSTDT and TRTxENDT
    • Date-time if appropriate

ADaM IG, May 2008

implementation issues solutions
Implementation Issues & Solutions
  • Building Analysis Datasets
    • Step 1: bring in data from elsewhere
    • Step 2: derive new data
      • Columns
      • Rows
    • Step 3: clean up

ADaM IG, May 2008

rules for rows vs columns
Rules for Rows vs. Columns
  • Add column if all data needed for derivation is in the row
    • Change from baseline
  • Add row if need more than one row to derive new information
    • LOCF, Average across a visit, AUC
  • Add row for transformations that go across all analysis variables
    • Log10

ADaM IG, May 2008

after derivations
After Derivations
  • How much SDTM to keep in AD?
    • Data used to derive analysis variables but otherwise not needed for analysis
  • Consider keeping if:
    • Helps with traceability
    • Easy to subset to get analysis records
    • “Extra” data will allow for derivation of alternate analyses
  • Keep audience in mind

ADaM IG, May 2008

timing of ig release
Timing of IG Release

ADaM IG, May 2008

timing of ig release1
Timing of IG Release
  • Jan 30, 2008
    • Released for internal CDISC review
  • March – May, 2008
    • ADaM making doc modifications
  • May 30, 2008
    • Planned date for public review release
  • Late August, 2008
    • Approximate review due date

ADaM IG, May 2008

ig review
IG Review
  • Review process will be similar to other CDISC reviews
    • Spreadsheet to collect comments
  • Review can be done by:
    • Company
    • Individual
    • Other?

ADaM IG, May 2008

ig review1
IG Review

ADaM IG, May 2008

summary
Summary
  • Purposes for Analysis Datasets/ADaM
  • Major Sections of ADaM IG
    • Basic ADaM structure
    • ADSL
  • Timing of IG Release
  • Questions?

ADaM IG, May 2008