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The iCaRe2 is a multi-institutional resource created and maintained by the Fred & Pamela Buffett Cancer Center to collect and manage standardized, multi-dimensional, longitudinal data and biospecimens on consented adult cancer patients, high-risk individuals, and normal controls. The distinct characteristic of the iCaRe2 is its geographical coverage, with a significant percentage of small and rural hospitals and cancer centers. The iCaRe2 advances comprehensive studies of risk factors of cancer development and progression and enables the design of novel strategies for prevention, screening, early detection and personalized treatment of cancer. Centers with expertise in cancer epidemiology, genetics, biology, early detection, and patient care can collaborate by using the iCaRe2 as a platform for cohort and population studies.
Full description
The integrated Cancer Repository for Cancer Research (iCaRe2 http://icare2project.org) is a unique sociotechnical resource for the collection and management of cancer and health-related data at the Fred & Pamela Buffett Cancer Center at University of Nebraska Medical Center (UNMC). The iCaRe2 is a multi-center, semantically-interoperable and easily-customizable cancer data resource which is aimed at collecting, managing, mining and sharing the comprehensive, multi-dimensional cancer-related data on cancer patients and biospecimens (such as tumor specimens, germ line DNA, serum, urine, and plasma) collected from those individuals.
The iCaRe2 provides: (i) a HIPAA compliant, secure, efficient and user-friendly mechanism for data and validation; (ii) utilization of standard vocabulary and data elements; and (iii) the ad-hoc data reporting capabilities. The iCaRe2 serves as a collaboration platform for studies (including clinical trials) performed in centers with expertise in cancer biology, pathology, epidemiology, genetics, early detection, and patient care.
The iCaRe2 has been developed as an expansion of the biocomputing framework that initially included four multi-center collaborative registries:
(i) the Pancreatic Cancer Collaborative Registry (PCCR) established in 2001, (ii) the Breast Cancer Collaborative Registry (BCCR) established in 2006, (iii) the Thyroid Cancer Collaborative Registry (TCCR) established in 2006, and (iv) the Great Plains Health Informatics Database (GPHID) established in 2011, to enroll subjects who have no personal history of cancer diagnosis at the time of enrollment.
At present, this framework has been incrementally expanded to include the Thoracic Oncology Collaborative Registry (TOCR), GenitoUrinary Cancer Collaborative Registry (GUCARE), Head and Neck Cancer Collaborative Registry (HNCCR), Gastrointestinal & Abdominal Cavity Cancer Collaborative Registry (GACCaRe), Central Nervous System Tumor Collaborative Registry (CTCR), Leukemia and Myeloid Neoplasm Registry (LEMN) , Gynecological Cancer Collaborative Registry (GCCR), Sarcoma Collaborative Registry (SARCR), Melanoma Collaborative Registry (MELCR), Plasma Cell Dyscrasias Collaborative Registry (PDCR), Neuroendocrine Collaborative Registry (NETR), and Auxiliary Cancer Registry (ACR).
The iCaRe2 group elected to use a "confederation model", as opposed to a traditional registry or network model. It was felt that these latter models implied that the registry or network would assume control of an individual Center's database. The major advantages of a confederation model include the flexibility to use selected Centers for different research projects based on a Center's resources and expertise and the ability to have different strategies to address various research questions. It was also recognized that for this model to be successful, it is essential to have a standardized approach to data collection (patient information and biospecimen annotation) and reporting. A confederation would also encourage participation of any interested Center, irrespective of its size or location. A web-based registry iCaRe2 was developed and made available to any Center to participate in data collection and storage of cancer related data.
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Ken Cowan, MD; Michelle M Desler, MS
Data sourced from clinicaltrials.gov
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