201107 CDISC ESUG-TC Trial Design

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Trial Design in the CDISC World
Albert Chau
26 July 2011
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Agenda
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How to construct Trial Design datasets
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Challenges for new users
o
o
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Relationships with other SDTM domains
Confusion of definitions/terms
Granularity
Case study in oncology
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Trial Design Domains
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Information about study design
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
No subject data
Describe the overall trial design and plan via data
representation
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Trial Design Datasets
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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!
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Trial Summary (TS) Dataset
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Summary of trial information
No link to subject-level data in SDTM
Common questions:
o
o
What need to be included?
Why are we generating this?
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Trial Inclusion/Exclusion (TI)
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Not subject-oriented
Link to IE domain
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o
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STUDYID, IECAT, IETESTCD, IETEST
Best to create TI first, before you tackle IE
Common questions:
o
o
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How to truncate if >200 characters?
Protocol amendment: do we need to add to TI only the
changed criteria or all criteria?
Local amendment
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TA / TE / TV datasets
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A data representation on the different epochs,
arms and visit structure in the study
Where to start?
Is there a systematic approach?
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Example 1 – Trial Design Schema
Drug A
Follow-up
Drug B
Follow-up
Screen
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Epoch
Drug A
Follow-up
Drug B
Follow-up
Treatment
Follow-up
Screen
EPOCH
Screening
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(Treatment
Strategy)
ARM
Arm / Treatment Strategy
2
Follow-up
Drug B
Follow-up
Treatment
Follow-up
Screen
Screening
1
Drug A
11
Arm / Treatment Strategy
Drug A
Follow-up
Drug B
Follow-up
Screening
Treatment
Follow-up
1
Screen
Drug A
Follow-up
2
Screen
Drug B
Follow-up
Screen
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Trial Design Matrix
Screening
Treatment
Follow-up
A
Screen
Drug A
Follow-up
B
Screen
Drug B
Follow-up
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TE (Trial Elements)
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What are the elements?
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Unique study cell values (=ELEMENT)
Screen
Drug A
Drug B
Follow-up
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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)
ETCD
ELEMENT
TESTRL
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SCRN
Screen
Informed Consent
A
Drug A
First dose of drug A
B
Drug B
First dose of drug B
FU
Follow-up
1 week after last dose of drug
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Trial Arms (TA) Dataset
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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
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= Treatment Strategy
Not necessarily the same as the actual drug
names/codes
ETCD / ELEMENT
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Must match up with the values in TE
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TE -> SE (Subject Elements)
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Shows the trial progress of each subject
o
o
Whether a subject passes through each element
Timing of each element
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Trial Visit (TV) Dataset
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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
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A “visit” may span over several days (eg screening
visit)
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TV -> SV (Subject Visits)
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Shows the actual visits of each subject
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Compare against the scheduled/planned visits or
assessments in TV
Include unscheduled visits
Designation of VISITNUM becomes crucial
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Whole number for planned visits
Decimals for unscheduled visits in SV – and slot into
right place
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Challenges in 1 oncology study
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Leukemia
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Patients to receive:
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Drug X (Days 1-4) is the current standard of treatment
Drug A (Days 1-7) is the experimental treatment
Drug A+X vs Drug X (1 course of treatment)
If patients on drug X not responding, then option to
“crossover” to drug A+X (1 further course)
Follow-up
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Responders: Efficacy follow-up (+ post-remission
therapies where applicable)
Non-responders and relapse: Survival follow-up
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Study schema
Efficacy FU
(q 1 months)
Drug A + X
Screen
Survival FU
(q 3 months)
Drug X
Drug A + X
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Question 1 – what are the epochs?
Efficacy FU
(q 1 months)
Drug A + X
Screen
Survival FU
(q 3 months)
Drug X
Drug A + X
Screening
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Treatment
Efficacy FU
1 Treatment epoch or separate into 2?
1 Follow-up epoch or separate into 2?
Survival FU
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Question 2 – How many arms?
Efficacy FU
(q 1 months)
Drug A + X
Screen
Survival FU
(q 3 months)
Drug X
Drug A + X
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For the patients on Drug X and then rollover to
Drug A+X – should this considered as a separate
“arm”?
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Question 3 – Granularity of Elements
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Do we model using “Treatment”+”Rest” or simply
“Treatment” (which includes rest period)?
Treatment
Rest
(Day 1 - 7)
(Day 8 – ??)
Treatment
(Day 1 - 37)
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Length of “Rest” differs between patients
Do we need to distinguish between “Treatment”
and “Rest”?
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Question 4 – Describing Trial Visits
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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:
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1st course of treatment: Start with VISITNUM=11
Cross-over: Start with VISITNUM=51
Efficacy follow-up: Start with VISITNUM=201
Survival follow-up: Start with VISITNUM=501
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Question 5 – Varying Trial Visits
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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?
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Question 5 – Varying Trial Visits
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Suggestion:
o
o
o
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Start with VISITNUM=201 for Efficacy Follow-up
Trial Element: Up to the next post-remission therapy
1st Post-Remission therapy: VISITNUM=250
2nd Post-Remission therapy: VISITNUM=300
etc
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Question 6 – Post-remission therapies
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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?
Question 7 – Randomised but not
treated
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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?
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Question 8 – When is a visit no longer
“planned”
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Planned visits for lab assessments: Day 15, Day
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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?
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Other challenges in oncology studies
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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?
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Summary
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Construction of TA/TE/TV
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Study Schema  Epoch  Arm  Study Cells
Unique study cells = rows in TE
All study cells = rows in TA
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
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Systematic approach will make life easier
Think at protocol/CRF design stage – don’t wait till the
end
Details vs ease of use
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Thank you!
E-mail: albert@datacision.co.uk
Tel: +44 (0)7904 106966
Web: www.datacision.co.uk
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