athn data summit thrombosis data collection: lessons learned from the htrs teregistry

2008© COPYRIGHTBryce A. Kerlin

ATHN Data Summit

Thrombosis Data Collection: Lessons Learned from the HTRS TERegistryBryce A. Kerlin, MDDirector, Hemostasis & Thrombosis CenterNationwide Children’s Hospital Assistant Professor of PediatricsThe Ohio State University College of Medicine


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Topics

• HTRS TERegistry:

– Registry Objectives

– Data Collection

– Quality Control / Data Integrity

– Accrual and Enrollment Limitations

• ATHN Specific Issues:

– Limitations of Data Quantity

– Role of ATHN in Thrombosis Research

– Protection of Investigator(s)


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TERegistry Obejectives

1. Prospectively evaluate the epidemiology and clinical characteristics of the known prothrombotic risk factors in persons with TE by developing a clinical informatics database (“registry”).

2. Identify the frequency and nature of complications associated with TE and its treatment.

3. Describe the phenotypes and complications seen in persons with multiple molecular risk factors.

4. Compare the epidemiology, clinical characteristics, and complications seen in persons with and without known risk factors.

May be better described as a “natural history” study.


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Inclusion / Exclusion

• Inclusion:

– Patient’s first TE.

– DVT, Arterial, Intra-Cardiac Thrombi; PE; Arterial TE; Stroke (<20 yrs); MI (<20 yrs).

– Specific criteria for diagnosis must be met.

• Exclusion:

– Bleeding Disorders; TIA; Sickle Cell; Metabolic Disorders associated with Stroke; Hemorrhagic Stroke; Bacterial Endocarditis; MAHA.


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Data Entry

• Paper Data Worksheets– For medical record abstraction

• Worksheets– Broken down into data types (registration, lab

data, etc.)• Worksheets faxed to main study center (NCH/OSU)• Data Transcribed into secure database

– Quality Control• Worksheets archived at NCH and at primary

institution


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Data Collection Flow


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Typical Worksheets


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Database Screenshots


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Database Screenshots


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Quality Control / Data Integrity

• Data Entry

– Single person enters data

• Quarterly Data Survey

– 6 random charts audited for accurate data entry on a quarterly basis

– 3 new registrations / 2 follow-ups / 1 recurrence

• Database

– Nightly Backup

– Password Protected

– Encrypted

– Access Limited to Study Personnel


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Enrollment

• Current: 110 patients <20 years old

– Adult enrollment much slower

• Goal: 500 patients <20 years old

Total # Patients Enrolled (Peds/Adults vs. Time)

0

10

20

30

40

50

60

70

80

90

Sep-0

5

Nov-05

Jan-

06

Mar

-06

May

-06

Jul-0

6

Sep-0

6

Nov-06

Jan-

07

Mar

-07

May

-07

Jul-0

7

Sep-0

7

Nov-07

Time (Month)

# p

atie

nts

en

roll

ed

Pediatric Patients Adult Patients


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Adult Enrollment Barriers

• Late presentation to study center

• Limited Diagnostic Data available

• Less frequently tested for thrombophilia

• Epidemiology / Natural History already better defined

• Lack of Research Assistant Support / Infrastructure


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Pediatric Enrollment Issues


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Pediatric Enrollment Issues

• Other:

– Debate regarding utility of thrombophilia testing


ATHN Specific Issues


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Data Quantity• “UDC Style”

– Epidemiology Driven Database / Registry

• “COG / Alternate Style”

– Hypothesis Driven Database / Registry

MDA

MDB

MDC

MDD

E

MDA

MDA

B

MDA

B

C

MDA

B

C

D

E


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ATHN Role in Thrombosis Research

• Facilitator?– i.e. Data Warehouse– Provides means to collect data, distribute data, and

provider of research tools• Statistical support• Scientific Review• Prioritization

• Scientific Body?– i.e. Study Group– Development of Hypotheses– Study Design

• Both?


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Investigator Protection

• Massive Time and Effort• Intellectual Property• Data integrity must be preserved for the initiating

investigator(s) utilization

• Examples:– HTRS TERegistry

• Co-owned by Kerlin, NCH, HTRS– CDC Pilot

• Co-owned by CDC and Pilot Centers

athn data summit thrombosis data collection: lessons learned from the htrs teregistry

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