Imaging and Clinical Data Integration In a caBIG trial setting… John Freymann, Justin Kirby SAIC-F November, 2007

Cancer Imaging Program NCI Division of Cancer Treatment & Diagnosis Cancer Therapy Evaluation Program (CTEP) Cancer Imaging Program (CIP)

Outline CIP leveraging of CTMS for imaging- relevant information collection Description of C3D contract trials experience NCIA imaging data existing practice Lookup table to normalize ID’s at pre-process stage Using caBIG for patient identifier management

Issues: CIP funds trials evaluating imaging agents and modalities for cancer management: Diagnosis Staging Response Evaluation These trials often have data collection and management needs that are distinct from therapy trials.

CIP Study Development Program – Progress To Date (October 2007 – October 2008) Activated Six Studies: 1. A Phase 2 Study of [ 18 F] Fluoroestradiol (FES) as a Marker for Hormone Sensitivity of Metastatic Breast Cancer Coordinating Center: University of Washington/ Principal Investigator: David Mankoff, MD, PhD Study set up completed/Patient enrollment: Open September A Phase 2 Study of Positron Emission Tomography Imaging with [ 18 F]Fluoromisonidasole (FMISO) and [ 18 F] Fluorodeoxyglucose (FDG) for Assessment of Tumor Hypoxia in Cervical Cancer Coordinating Center: University of Washington/ Principal Investigator: Joseph Rajendran, MD Study set up completed/Patient enrollment: Open September Phase 2 Study of 3'-Deoxy-3'- 18 F Fluorothymidine (FLT) in Invasive Breast Cancer Coordinating Center: Virginia Commonwealth University/ Principal Investigator: Paul Jolles, MD eCRF Design Completed/Database Development Phase

CIP Study Development Program – Progress To Date (October 2007 – October 2008), continued Activated Six Studies (Continued): 4. Phase 2 Single-Arm Trial Comparing the Use of FLT PET to Standard Computed Tomography to Assess the Treatment Response of Neoadjuvant Docetaxel and Cisplatin in Stage IB-IIIA Resectable Non-Small Cell Lung Cancer Coordinating Center: Johns Hopkins Sidney Kimmel Comprehensive Cancer/ Center/ Principal Investigator: Richard L. Wahl, MD eCRF Design Completed/Database Development Phase; under IRB review, scheduled to open January F NaF PET for Detection of Bone Metastases in Men with Prostate Cancer Coordinating Center: Massachusetts General Hospital (MGH)/ Principal Investigator: Mukesh Harisinghani, MD FDA approved, under IRB review, eCRF Design Completed/Database Development Phase, scheduled to open January Quantitative Assessment of the Early and Late Effects of Radiation and Chemotherapy on Glioblastoma Using Multiple MRI Techniques Coordinating Center: Massachusetts General Hospital (MGH)/ Principal Investigator: A. Gregory Sorensen, MD Enrollment open August 2008 (patient accrued), eCRF Design Completed and hard copy forms in use/Database Development Phase in progress scheduled for completion mid-December 2008

Issues: The data management needs of imaging trials are not well met by the available therapeutic trial data management systems: CDS CTMS

Available Solutions for CIP: Non-IND studies Abbreviated CDS which provides demographic information. IND studies Customizable solutions among NCI trial systems were evaluated.

C3D C3D is a web-based clinical data management solution. Originally developed for NCI's intramural research program Now available to other research organizations in a hosted Application Service Provider (ASP) model C3D supports data standardization, reuse, sharing, and interoperability through electronic Case Report Forms (eCRFs) based on Common Data Elements (CDEs) maintained in NCICB’s Cancer Data Standards Repository (caDSR) and controlled by terminology from the NCI Enterprise Vocabulary Services (EVS).

Introduction: C3D Components 1.CDE Browser / caDSR Microsoft Internet Explorer 2.a. Oracle Clinical™ Microsoft Internet Explorer J-Initiator b. Remote Data Capture (RDC) Microsoft Internet Explorer J-Initiator Adobe Reader Oracle / Adobe Acrobat Reader plug-in 3.J-Review Microsoft Internet Explorer J-Review plug-in

Study Conduct: Reports: J-Review J-Review is a Web-based tool for ad-hoc querying, reporting, and analysis of clinical data.

A Phase 2 Study of [ 18 F] Fluoroestradiol (FES) as a Marker for Hormone Sensitivity of Metastatic Breast Cancer Principal Investigator: David Mankoff, MD, PhD University of Washington

FES Trial – Example eCRFs

FES Trial

Imaging studies in C3D - FES FES Study (U of Washington) Total 169 CDEs used in study 127 existing CDEs reused 42 new CDEs created for C3D build 5 of the new variables were created using imaging standards from DICOM (NCIA) Multiple new variables could be candidates for extension of ACRIN standard 75% reuse for FES study

caBIG/CIP/ACRIN Curation Efforts ACRIN is a member of caBIG CRF harmonization and standardization workgroups 1. Length of Time working with content: October 5, 2006 to present 2. Number of Data Elements identified: Number of Data Elements curated : 505 (415 assoc with CSI) 4. Number of Data Elements released: Number of Data Elements available for review: Treatment Modalities

CIP Study Development Program – Advantages of Using C3D and Support Team (continued) Provides overall support to study sites. Conducts site visits and communicates with the sites/study teams frequently to triage study staff questions and facilitated protocol amendments, and CRF/eCRF finalization for CIP, CTEP, IRB, and FDA submissions. Provides training for adhering to CIP requirements (e.g., CDUS/CDS, AdEERS reporting) and use of standard study tools including C3D Database and eCRF guidelines.

C3D Adoption Process C3D Database Developed eCRF Guidelines CreatedeCRF templates generated in Word l Guidelines Developed Finalize and Approval eCRFsProtocol Site Visit Protocol ReviewCRF ReviewStudy procedure reviewC3D demo C3D-based CRFs drafted for review Reviewed by CIPReviewed by PI / Site Protocol Drafted C3D Development Team Organized

Next Steps Continued use of C3D to collect metadata in CIP IND studies Potential pilot of C3D in ACRIN Phase II study in GBM (FMISO and MR) Linkage of images to metadata ECRFs

Outline CIP leveraging of CTMS for imaging- relevant information collection Description of C3D contract trials experience NCIA imaging data existing practice Lookup table to normalize ID’s at pre-process stage Using caBIG for patient identifier management

What NCIA does now CTP Client NCIA SystemCTP Server 26

What NCIA does now CTP Client NCIA SystemCTP Server IRB and IT Security Issues Addressed

What NCIA does now CTP Client NCIA SystemCTP Server Lookup tables can be used to “map” patient IDs

What NCIA does now – Example RTOG 0522 Site One CTP Client DICOMRT Lookup tables used to “map” patient IDs Site Two CTP Client PET/CT Lookup tables used to “map” patient IDs

Potential CTMS/NCIA integration CTP Client NCIA SystemCTP Server “Lookup table” generated by API call to C3PR NCIA system now using same patient IDs as C3D/C3PR

Expectation Not realistic to expect to be able to pre- process all patient identifiers…

Outline CIP leveraging of CTMS for imaging- relevant information collection Description of C3D contract trials experience NCIA imaging data existing practice Lookup table to normalize ID’s at pre-process stage Using caBIG for patient identifier management

C3PR patient ID management

Issues Using C3PR Needs caExchange integration? Will it be hosted as enterprise at NCI? C3PR timeline? Integrate AIM? New CDMS integration Reusability of eCRFs? Integration with C3PR?

Issues Image collection at clinical sites: may occur asynchronously to clinical data collection, maybe in batch mode additional players may need to be trained FDA requirements – auditting, etc?

Issues Flow Scenarios: Before you get images, go to c3pr to create the patient, register them on the image trial. Since C3D is already populated with cases, C3PR will have to be backfilled… (190 trials with patients in C3D currently) Include Demographic information in queries

Tactical Issues Separate “trusted registry” from “demographic validation engine” Start with smaller scope of implementation: Research Study / Trial / Coop Group / etc.. Be clear about Purpose – Queries across Grid or normalizing data for caIntegrator2 application

Cross-Enterprise Document Sharing

XDS and PIX/PDQ Integration

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