1. How to go from an SDTM Finding Domain to an ADaM-Compliant Basic Data Structure Analysis Dataset: An Example Qian Wang, MSD, Brussels, Belgium Carl Herremans, MSD, Brussels, Belgium PhUSE 2010, Berlin

2. PhUSE 2010 - Berlin 2 ADaM versus SDTM ADaM datasets do use redundancy for easy analysis – common variables may be found across all analysis datasets (e.g., population flags, subject identifiers, etc.); ADaM datasets have a greater number of numeric variables (e.g., SAS formatted dates, numeric representation of a character grouping variable from SDTM); ADaM datasets may combine variables from multiple SDTM domains; ADaM datasets are named AD.

3. PhUSE 2010 - Berlin 3 ADaM-compliant Basic Data Structure (BDS) A BDS dataset contains one or more records per subject, per analysis parameter and per analysis time point. It describes the data being analyzed and also includes variables to support the analysis (e.g. covariates) as well as information to facilitate traceability.

4. PhUSE 2010 - Berlin 4 6 Basic Steps Step 1 Prepare ADaM Precursor Step 2 Convert ISO8601 Dates Step 3 Create Analysis Relative Day Step 4 Create Key Analysis Variables Step 5 Add Time Windows Step 6 Derive Change from Baseline

5. PhUSE 2010 - Berlin 5 STEP 1: Preparing for ADAM Precursor by Adding SUPPQUAL to SDTM LB SUPPQUAL LB + SUPPQUAL (where RDOMAIN=‘LB’)

6. PhUSE 2010 - Berlin 6 STEP 1: Preparing for ADAM Precursor by adding SUPPQUAL to SDTM USUBJIDSEXLBSEQLBTESTCDLBORRES LBFAST 0002_0001M1NA0.1Y STUDYIDRDOMAINUSUBJIDIDVARIDVARVARLQNAMQVAL 0002LB 0002_0001 LBSEQ1 LBFASTY USUBJIDSEXLBSEQLBTESTCDLBORRES 0002_0001M1NA0.1 +

7. PhUSE 2010 - Berlin 7 STEP 1: Preparing for ADAM Precursor by Adding SUPPQUAL to SDTM proc transpose data=supplb out=supplb2 (rename=(idvarval=lbseq)); by usubjid idvarval; var qval; id qnam; idlabel qlabel; run; %addsuppqual(input_libary =, input_dataset_suppqual =, input_dataset_define =, output_library = );

8. PhUSE 2010 - Berlin 8 6 Basic Steps Step 1 Prepare ADaM Precursor Step 2 Convert ISO8601 Dates Step 3 Create Analysis Relative Day Step 4 Create Key Analysis Variables Step 5 Add Time Windows Step 6 Derive Change from Baseline

9. PhUSE 2010 - Berlin 9 STEP 2: Converting ISO8601 Date/Time --DTC 2003-12-15T13:14:17

10. PhUSE 2010 - Berlin 10 STEP 2: Converting ISO8601 Date/Time If not missing ADT and ATM populate ADTM

11. PhUSE 2010 - Berlin 11 STEP 2: Converting ISO8601 Date/Time --DTCADTADTFATMATMFADTM 2003-12-15T13:14:1715Dec200313:14:1715Dec2003:13:14:17 2003-12-15T13:1415Dec200313:14:00S15Dec2003:13:14:00 2003-12-15T1315Dec200313:00:00M15Dec2003:13:00:00 2003-12-1515Dec2003 2003-1201Dec2003D 200301Jul2003M %convert2date(input_dataset=, output_dataset= );

12. PhUSE 2010 - Berlin 12 6 Basic Steps Step 1 Prepare ADaM Precursor Step 2 Convert ISO8601 Dates Step 3 Create Analysis Relative Day Step 4 Create Key Analysis Variables Step 5 Add Time Windows Step 6 Derive Change from Baseline

13. PhUSE 2010 - Berlin 13 STEP 3: Creating Analysis Relative Day ADY = LBDT - ADSL. TRTSDT + (LBDT > ADSL.TRTSDT)

14. PhUSE 2010 - Berlin 14 6 Basic Steps Step 1 Prepare ADaM Precursor Step 2 Convert ISO8601 Dates Step 3 Create Analysis Relative Day Step 4 Create Key Analysis Variables Step 5 Add Time Windows Step 6 Derive Change from Baseline

15. PhUSE 2010 - Berlin 15 SDTM LB LBTESTCDLBTESTLBSTRESNLBSTRESU NASodium139mmol/L KPotassium3.5mmol/L ADaM ADLB PARAMCDPARAMAVAL NASodium (mmol/L)139 KPotassium (mmol/L)3.5 STEP 4: Creating Key Analysis Parameter Variables PARAM(CD), AVAL

16. PhUSE 2010 - Berlin 16 STEP 4: Creating Key Analysis Parameter Variables PARAM(CD), AVAL SDTM LB LBDYLBTESTCDLBTESTLBSTRESNLBSTRESU 1NASodium139mmol/L 1NASodium145mmol/L ADaM ADLB ADYPARAMCDPARAMAVALDTYPE ANL01FL 1 NASodium (mmol/L)139 1 NASodium (mmol/L)145 1 NASodium (mmol/L)142 AVERAGEY

17. PhUSE 2010 - Berlin 17 STEP 4: Creating Key Analysis Parameter Variables PARAM(CD), AVAL %finding(input_dataset=, domain=, summaryfunction=AVERAGE, output_dataset= );

18. PhUSE 2010 - Berlin 18 6 Basic Steps Step 1 Prepare ADaM Precursor Step 2 Convert ISO8601 Dates Step 3 Create Analysis Relative Day Step 4 Create Key Analysis Variables Step 5 Add Time Windows Step 6 Derive Change from Baseline

19. PhUSE 2010 - Berlin 19 Time Point (Target Day) Time window in Days Baseline (1)-70 to 7 Treatment 1 (45)8 to 90 Treatment 2 (135)91to 180 1 Time -70790180 Baseline Treatment 1Treatment 2 STEP 5: ADDING TIME WINDOWS

20. PhUSE 2010 - Berlin 20 STEP 5: ADDING TIME WINDOWS Start dayStop dayTargetAVISITAVISITNBaseline -7071Baseline0Y 89045Treatment 11 91180135Treatment 22 ADYPARAMCDAVALAVISITAVISITNAWTARGETAWRANGEABLFLANL02FL -18NA141Baseline01-70 to 7 1NA140Baseline01-70 to 7YY 14NA145Treatment 11458 to 90 46NA149Treatment 11458 to 90Y

21. PhUSE 2010 - Berlin 21 6 Basic Steps Step 1 Prepare ADaM Precursor Step 2 Convert ISO8601 Dates Step 3 Create Analysis Relative Day Step 4 Create Key Analysis Variables Step 5 Add Time Windows Step 6 Derive Change from Baseline

22. PhUSE 2010 - Berlin 22 Step 6: Deriving Change From Baseline ADYPARAMCDAVALAVISITAVISITNABLFLBASECHG -18NA141Baseline01401 1NA140Baseline0Y1400 14NA145Treatment 111405 46NA149Treatment 111409 %change(input_dataset=, input_timewindow_dataset=, output_dataset= );

23. PhUSE 2010 - Berlin 23 Conclusion Step 1 Prepare ADaM Precursor Step 2 Convert ISO8601 Dates Step 3 Create Analysis Relative Day Step 4 Create Key Analysis Variables Step 5 Add Time Windows Step 6 Derive Change from Baseline 6 Steps have been described to transform a SDTM finding dataset into an ADaM-compliant BDS analysis dataset.