Transcript GDP - Association for Pathology Informatics

An Update on the Informatics Supported
Annotation and Integration of Datasets for
the Gynecologic Disease Program (GDP)
Waqas Amin MD1, Sambit K. Mohanty MD1&7, Anil V. Parwani MD PhD1&3, Sharon
B. Winters MS1, Nancy B. Whelan BS1, Althea M. Schneider BS1, John T. Milnes BS1,
Charma D. Chaussard BS4, Gail Harger MS2, Katherine Farrow BS2, Debra Bass MS2,
Tim D. Fennell MS1, Hai Hu PhD6, Thomas C. Krivak MD4, Rajiv Dhir MD3, Robert
P. Edwards MD4, Larry Maxwell MD5 Michael J. Becich MD PhD1&3,
1Department
of Biomedical Informatics and 2Department of Epidemiology, University of
Pittsburgh, PA. USA. 3Department of Pathology and 4Department of Obstetrics Gynecology,
Magee-Women Hospital, University of Pittsburgh Medical Center, PA USA. 5Walter Reed Army
Medical Center, Washington, DC. USA. 6Windber Research Institute Windber, PA, USA.
7Winthrop University Hospital, New York, USA
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Introduction:
 The Gynecologic Disease Program (GDP), a.k.a Gynecologic Cancer
Center, is funded by the Department of Defense (DOD).
 Primary objective is to develop state-of-the-art capabilities in clinical
and basic science research aimed at improving screening, early
detection, prevention, and treatment of gynecologic disease.
 Collaborators: Walter Reed Army Medical Center, University of
Pittsburgh Cancer Institute, Windber Research Institute and
Georgetown Medical Center.
 At UPitt this program constitutes three cores:
 Luminex
 Proteomics
 Tissue Banking Informatics
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Objectives:
 To create a well-characterized and standard-based biospecimen
repository for Ovarian and Endometrial malignancies.
 To facilitate the collection and transfer of well annotated
datasets to the central data warehouse (Windber Research
Institute).
 To create an internal storage system of transferred data using
the Clinical Trial Management Application (CTMA).
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Common Data Elements
 Through the combined efforts of experts from various fields,
Common Data Elements (demographic, epidemiologic, clinical,
pathologic specimen and block annotation, genotype, follow up and
outcome) were developed for gynecological conditions.
 Common Data Elements (CDEs) allow consistency and
interoperability in biospecimen collection and better understanding
of research and experimental data.
 Major standards used to build CDEs:
 College of American Pathology (CAP) checklists
 Elements from coPath-synoptics
 North American Association of Cancer Registry (NAACR) core
elements
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PATHOLOGY DATA
(coPATH and Synoptics – CAP Checklist)
OVARIAN TUMORS
EXTRAOVARIAN ABDOMINAL
TUMORS
ENDOMETRIAL TUMORS
OTHERS (HYPERPLASIAS)
•GDP # (for patient)
• Date of Surgery
• Surgical Procedure
• Macroscopic Attributes
- Anatomic Location
- Size
• Microscopic Attributes
- Histologic Type
- Grade (Silverberg grade
etc.)
- Perifocal reaction
- Nodal status
- Pathologic Stage
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CANCER REGISTRY DATA ELEMENTS
(NAACCR STANDRARD)
OVARIAN TUMORS
EXTRAOVARIAN ABDOMINAL
TUMORS
ENDOMETRIAL TUMORS
•GDP # (for patient)
• Date of Surgery
• Surgical Procedure
• Clinical Staging (AJCC Staging)
• Therapy related variables
• Recurrence / Metastasis attributes
• Vital status
• Biochemical data
- Tumor markers
- Hormone receptors
OTHERS (HYPERPLASIAS)
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Core Data Sources:
Questionnaire Data
Pathological Evaluation
(coPATH and synoptic)
Cancer Registry System
Clinical Trial Management Application
De-identified Data Export
Central Data Center (WRI)
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Questionnaire Data:
 Pre-operative Case/Control Matching
 Postoperative Questionnaire
HOPE Ovarian
Endometrial
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Pathology Data ( coPATH & Synoptics)
• Synoptic worksheet are implemented for use in data acquisition.
This provides a structured way of entering the diagnostic /
prognostic information for particular pathology specimen and
ultimately serves as medium for capturing and storing data for
translational research.
•
The data is stored as discrete data elements which appear as an
accession summary within the final pathology report.
• The synoptic data is manually or electronically imported into the
CTMA for linking pathological details on banked tissues.
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UPMC Cancer Registry
 The UPMC Registry Information Services (RIS) is designed for the
collection, management and analysis of demographic, grading, staging,
treatment and progression data on cancer patients
 Primary sources for documentation are both the “paper” and “electronic”
medical records from which data is abstracted into the Cancer Registry
database by Certified Cancer Registrars.
 The entire UPMC RIS is built on the North American Association of Central
Cancer Registries (NAACCR) data standard architecture.
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CANCER REGISTRY DATA ELEMENTS
(NAACCR STANDRARD)
Treatment
Follow Up
Recurrence
• Data imported from
Cancer Registry Tool.
• Data entry done at
source application (IMPAC)
by cancer registrars.
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Technology:
 Clinical Trial Management Application is a web-based Java
application for managing various aspects of clinical trails, research
protocols and outcome initiatives.
 Provides an integrated set of components for managing
administrative and regulatory tracking (e.g., IRB-related issues).
 Facilitates study protocol schema, treatment calendar and financial
management issues for capturing study specific patient
information.
 Used for internal storage of data in GDP study.
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Result:
 At UPMC (Magee Women’s Hospital) total number of consented
patients is 109. Endometrial cancer (45), ovarian cancer (13),
withdrew from the project (33), benign conditions (12), and the rest
are pending for surgical procedures.
 Patient privacy protection is of utmost importance and is enforced in
accordance with Health Insurance Portability and Accountability Act
(HIPAA) and only de-identified is transferred to WRI
 Well-structured study protocol is implemented for the acquisition of
high quality and well characterized annotated biospecimens and
transfer of data to central data warehouse (WRI).
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Overall Workflow for GDP
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Overall Workflow for GDP
Patient consented by Research Nurse Coordinator
(RNC) and enrolled in GDP study.
RNC assigns a GDP Number to the patient, or case, fills out the
Paper-based and Web-based (Clinical Trials Management
Application [CTMA]) Pre-operative Case/Control Matching
Questionnaire, and collects blood sample.
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Overall Workflow for GDP
Patient undergoes operation and surgical specimen is accessioned for
pathological examination (generating coPATH Data). Biospecimen are
stored in Magee women Hospital Tissue bank tissue bank and data is
Stored in TBINV
BENIGN
MALIGNANT
Post-operative blood
sample collected.
CASE COMPLETE
FROM GDP STUDY
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Workflow for GDP
Hope Survey
RNC completes Paper-based and Web-based (CTMA) Post-operative questionnaire (HOPE
for Ovarian / Endometrial post-operative questionnaire) and collects blood sample.
RNC MAKES A COPY OF ENTIRE QUESTIONNAIRE DATA & SENDS THE
ORIGINAL AND THE COPY TO THE FOLLOWING:
ORIGINAL
Data Manager, Department of
Epidemiology, University of Pittsburgh
COPY
Department of Biomedical Informatics
(DBMI) and Cancer Registry Team
Scansoft
Processing
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Workflow for GDP
Data Transfer
Transfer Electronic version of Questionnaire Data (Excel layout)
to Windber Research Institute (WRI) and send one copy to DBMI.
Scansoft CSV
Output Files
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Workflow for GDP
CTMA Annotation
DBMI post-doctoral fellows enter pathology data into CTMA (internal use) which is
pulled into Excel layout for WRI. Medical Registry data directly pulled for transfer to
WRI (Excel layout). Tissue bank inventory data is pulled out in Excel format and
transfer to WRI
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Workflow for GDP
Excel File Generation
Transfer Pathology and
Registry Data to WRI
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Conclusion:
 The Gynecologic Disease Program acts as a central repository
for clinically annotated gynecological tumor tissues for the
research community.
 This tissue banking initiative provides an infrastructure of joint
multi-institutional bioinformatics network that facilitates the
sharing of clinically annotated data and high quality
biospecimens to support important research activities.
 With information gained from these research activities, we will
continue to improve screening, early detection, prevention, and
treatment of gynecologic disease.
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Acknowledgments
Collaborators:
–
–
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Walter Reed Army Medical Center
University of Pittsburgh Cancer Institute
Windber Research Institute
Georgetown Medical Center
Leadership
Dr.
Dr.
Dr.
Dr.
Ronald Herberman
Robert Edwards
Rajiv Dhir
Anil Parwani
Dr. Michael Becich
Dr. Larry Maxwell
Dr. Michael Feldman
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THANK YOU
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