trial design in the cdisc world albert chau 26 july 2011 1

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

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

Trial Design in the CDISC World

Albert Chau

26 July 2011

1

Page 2: Trial Design in the CDISC World Albert Chau 26 July 2011 1

2

Agenda

How to construct Trial Design datasetso Relationships with other SDTM domains

Challenges for new userso Confusion of definitions/termso Granularity

Case study in oncology

Page 3: Trial Design in the CDISC World Albert Chau 26 July 2011 1

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Trial Design Domains

Information about study designo No subject data

Describe the overall trial design and plan via data representation

Page 4: Trial Design in the CDISC World Albert Chau 26 July 2011 1

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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!

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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?

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Trial Inclusion/Exclusion (TI)

Not subject-oriented Link to IE domain

o STUDYID, IECAT, IETESTCD, IETESTo 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

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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?

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Example 1 – Trial Design Schema

ScreenDrug A

Drug B

Follow-up

Follow-up

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Epoch

ScreenDrug A

Drug B

Follow-up

Follow-up

Screening Treatment Follow-upEPOCH

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Arm / Treatment Strategy

ScreenDrug A

Drug B

Follow-up

Follow-up

Screening Treatment Follow-up

AR

M(T

rea

tme

nt

Str

ate

gy)

1

2

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Arm / Treatment Strategy

ScreenDrug A

Drug B

Follow-up

Follow-up

Screening Treatment Follow-up

Study Cell

1

2

Screen

Screen

Drug A

Drug B

Follow-up

Follow-up

Page 12: Trial Design in the CDISC World Albert Chau 26 July 2011 1

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Trial Design Matrix

Screening Treatment Follow-up

A

B

Screen

Screen

Drug A

Drug B

Follow-up

Follow-up

Page 13: Trial Design in the CDISC World Albert Chau 26 July 2011 1

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TE (Trial Elements)

What are the elements?o 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)

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

ETCD ELEMENT TESTRL

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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

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TE -> SE (Subject Elements)

Shows the trial progress of each subjecto Whether a subject passes through each elemento Timing of each element

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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)

Page 18: Trial Design in the CDISC World Albert Chau 26 July 2011 1

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TV -> SV (Subject Visits)

Shows the actual visits of each subjecto Compare against the scheduled/planned visits or

assessments in TVo Include unscheduled visits

Designation of VISITNUM becomes crucialo Whole number for planned visitso Decimals for unscheduled visits in SV – and slot into

right place

Page 19: Trial Design in the CDISC World Albert Chau 26 July 2011 1

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Challenges in 1 oncology study

Leukemiao Drug X (Days 1-4) is the current standard of treatmento 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

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Study schema

Screen

Drug A + X

Drug X

Drug A + X

Efficacy FU (q 1 months)

Survival FU (q 3 months)

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Question 1 – what are the epochs?

1 Treatment epoch or separate into 2? 1 Follow-up epoch or separate into 2?

Screen

Drug A + X

Drug X

Drug A + X

Efficacy FU (q 1 months)

Survival FU (q 3 months)

Screening Treatment Efficacy FU Survival FU

Page 22: Trial Design in the CDISC World Albert Chau 26 July 2011 1

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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”?

Screen

Drug A + X

Drug X

Drug A + X

Efficacy FU (q 1 months)

Survival FU (q 3 months)

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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”?

Treatment(Day 1 - 7)

Rest(Day 8 – ??)

Treatment(Day 1 - 37)

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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 1st course of treatment: Start with VISITNUM=11o Cross-over: Start with VISITNUM=51o Efficacy follow-up: Start with VISITNUM=201o Survival follow-up: Start with VISITNUM=501

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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?

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Question 5 – Varying Trial Visits

Suggestion:o Start with VISITNUM=201 for Efficacy Follow-upo Trial Element: Up to the next post-remission therapyo 1st Post-Remission therapy: VISITNUM=250o 2nd Post-Remission therapy: VISITNUM=300o etc

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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?

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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?

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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?

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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?

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Summary

Construction of TA/TE/TVo Study Schema Epoch Arm Study Cellso Unique study cells = rows in TEo All study cells = rows in TAo 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 easiero Think at protocol/CRF design stage – don’t wait till the

endo Details vs ease of use

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Thank you!

E-mail: [email protected]

Tel: +44 (0)7904 106966

Web: www.datacision.co.uk