1 / 29

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

vaughan-cantrell
Download Presentation

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

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. ADaM Implementation Guide: It’s Almost Here.  Are You Ready? Sandra Minjoe Principal Statistical Programmer Analyst Genentech, Inc ADaM IG, May 2008

  2. Outline • Purposes for Analysis Datasets and ADaM • Major Sections of ADaM IG • Basic ADaM structure • ADSL • Timing of IG Release ADaM IG, May 2008

  3. Purposes for Analysis Datasets and ADaM ADaM IG, May 2008

  4. 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

  5. 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

  6. 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

  7. 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

  8. Major Sections of ADaM IG ADaM IG, May 2008

  9. 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

  10. 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

  11. 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

  12. ADSL • Subject Level Analysis Data • Required if any ADaM data is submitted ADaM IG, May 2008

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. Population Indicators:Conversions between SDTM & ADaM * Include only population flag(s) needed for analysis ADaM IG, May 2008

  20. 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

  21. 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

  22. 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

  23. 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

  24. 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

  25. Timing of IG Release ADaM IG, May 2008

  26. 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

  27. 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

  28. IG Review ADaM IG, May 2008

  29. Summary • Purposes for Analysis Datasets/ADaM • Major Sections of ADaM IG • Basic ADaM structure • ADSL • Timing of IG Release • Questions? ADaM IG, May 2008

More Related