1. Trial Design in the CDISC World Albert Chau 26 July 2011 1

2. Agenda How to construct Trial Design datasets o Relationships with other SDTM domains Challenges for new users o Confusion of definitions/terms o Granularity Case study in oncology 2

3. Trial Design Domains Information about study design o No subject data Describe the overall trial design and plan via data representation 3

4. Trial Design Datasets Trial Arms (TA) Trial Elements (TE) Trial Visits (TV) Trial Inclusion /Exclusion (TI) Trial Summary (TS) Start thinking about this before you start the other SDTM datasets! 4

5. Trial Summary (TS) Dataset Summary of trial information No link to subject-level data in SDTM Common questions: o What need to be included? o Why are we generating this? 5

6. Trial Inclusion/Exclusion (TI) Not subject-oriented Link to IE domain o STUDYID, IECAT, IETESTCD, IETEST o Best to create TI first, before you tackle IE Common questions: o How to truncate if >200 characters? o Protocol amendment: do we need to add to TI only the changed criteria or all criteria? o Local amendment 6

7. TA / TE / TV datasets A data representation on the different epochs, arms and visit structure in the study Where to start? Is there a systematic approach? 7

8. Example 1 – Trial Design Schema 8 Screen Drug A Drug B Follow-up

9. Epoch 9 Screen Drug A Drug B Follow-up Screening Treatment Follow-up EPOCH

10. Arm / Treatment Strategy 10 Screen Drug A Drug B Follow-up Screening Treatment Follow-up ARM (Treatment Strategy) 1 2

11. Arm / Treatment Strategy 11 Screen Drug A Drug B Follow-up Screening Treatment Follow-up Study Cell 1 2 Screen Drug A Drug B Follow-up

12. Trial Design Matrix 12 Screening Treatment Follow-up A B Screen Drug A Drug B Follow-up

13. TE (Trial Elements) What are the elements? o Unique study cell values (=ELEMENT) 13 Screen Drug A Drug B Follow-up

14. TE (Trial Elements) Assign an element code (ETCD) to each value, define the start of each element (TESTRL) and end of each element (TEENRL or TEDUR) 14 Screen Drug A Drug B Follow-up SCRN A B FU Informed Consent First dose of drug A First dose of drug B 1 week after last dose of drug ETCDELEMENTTESTRL

15. Trial Arms (TA) Dataset Go back to the Trial Design Matrix 1 study cell = 1 row of record in TA So in our example we expect 6 rows of record ARM / ARMCD o = Treatment Strategy o Not necessarily the same as the actual drug names/codes ETCD / ELEMENT o Must match up with the values in TE 15

16. TE -> SE (Subject Elements) Shows the trial progress of each subject o Whether a subject passes through each element o Timing of each element 16

17. Trial Visit (TV) Dataset Describe the planned visits in a trial VISITNUM and TRSTRL is required ARMCD expected VISIT and VISITDY permissible 1 record per planned visit per arm o A “visit” may span over several days (eg screening visit) 17

18. TV -> SV (Subject Visits) Shows the actual visits of each subject o Compare against the scheduled/planned visits or assessments in TV o Include unscheduled visits Designation of VISITNUM becomes crucial o Whole number for planned visits o Decimals for unscheduled visits in SV – and slot into right place 18

19. Challenges in 1 oncology study Leukemia o Drug X (Days 1-4) is the current standard of treatment o Drug A (Days 1-7) is the experimental treatment Patients to receive: o Drug A+X vs Drug X (1 course of treatment) o If patients on drug X not responding, then option to “crossover” to drug A+X (1 further course) Follow-up o Responders: Efficacy follow-up (+ post-remission therapies where applicable) o Non-responders and relapse: Survival follow-up 19

20. Study schema 20 Screen Drug A + X Drug X Drug A + X Efficacy FU (q 1 months) Survival FU (q 3 months)

21. Question 1 – what are the epochs? 1 Treatment epoch or separate into 2? 1 Follow-up epoch or separate into 2? 21 Screen Drug A + X Drug X Drug A + X Efficacy FU (q 1 months) Survival FU (q 3 months) Screening TreatmentEfficacy FUSurvival FU

22. Question 2 – How many arms? For the patients on Drug X and then rollover to Drug A+X – should this considered as a separate “arm”? 22 Screen Drug A + X Drug X Drug A + X Efficacy FU (q 1 months) Survival FU (q 3 months)

23. Question 3 – Granularity of Elements Do we model using “Treatment”+”Rest” or simply “Treatment” (which includes rest period)? Length of “Rest” differs between patients Do we need to distinguish between “Treatment” and “Rest”? 23 Treatment (Day 1 - 7) Rest (Day 8 – ??) Treatment (Day 1 - 37)

24. Question 4 – Describing Trial Visits How to number the visits, when you don’t know how many visits there are up-front? Don’t have to be consecutive numbers Example: o 1 st course of treatment: Start with VISITNUM=11 o Cross-over: Start with VISITNUM=51 o Efficacy follow-up: Start with VISITNUM=201 o Survival follow-up: Start with VISITNUM=501 24

25. Question 5 – Varying Trial Visits During Efficacy Follow-up, patients can receive “post-remission therapies”. “Reset” follow-up clock from post-remission therapies How to model Trial Elements and Visits? 25

26. Question 5 – Varying Trial Visits Suggestion: o Start with VISITNUM=201 for Efficacy Follow-up o Trial Element: Up to the next post-remission therapy o 1 st Post-Remission therapy: VISITNUM=250 o 2 nd Post-Remission therapy: VISITNUM=300 o etc 26

27. Question 6 – Post-remission therapies For post-remission therapies in efficacy follow-up, the choice is down to the treating physician Can potentially be Drug X or any other therapies Should we create Trial Elements for the different therapies? 27

28. Question 7 – Randomised but not treated Randomisation usually starts 1-2 days before start of treatment due to logistic reason What is the start and end of “Screen” and “Drug A”/”Drug A+X” trial elements in TE? How to capture these patients in SE? Should randomisation be a separate visit in TV/SV? 28

29. Question 8 – When is a visit no longer “planned” Planned visits for lab assessments: Day 15, Day 21 A patient had lab taken on Day 17 and Day 22 instead Should these be put into planned visits of Day 15 and Day 21, or unscheduled visits? 29

30. Other challenges in oncology studies Post-remission therapy will be given and patients will be followed up “according to institution’s standard treatment practice” Dose escalation studies – how many arms? Legacy studies: Do we need to provide trial design datasets? 30

31. Summary Construction of TA/TE/TV o Study Schema  Epoch  Arm  Study Cells o Unique study cells = rows in TE o All study cells = rows in TA o If all arms have same visits, then 1 set of visits for all arms. Otherwise 1 set of visits for each arm. Complex study designs o Systematic approach will make life easier o Think at protocol/CRF design stage – don’t wait till the end o Details vs ease of use 31

32. Thank you! E-mail: albert@datacision.co.ukalbert@datacision.co.uk Tel: +44 (0)7904 106966 Web: www.datacision.co.ukwww.datacision.co.uk 32