PURPOSE: Biospecimen-based research offers tremendous promise as a way to increase understanding of the molecular epidemiology of cancers. Population-based cancer registries can augment this research by providing more clinical detail and long-term follow-up information than is typically available from biospecimen annotations. In order to demonstrate the feasibility of this concept, we performed a pilot linkage between the California Cancer Registry (CCR) and the University of California, Davis Cancer Center Biorepository (UCD CCB) databases to determine if we could identify patients with records in both databases. METHODS: We performed a probabilistic data linkage between 2180 UCD CCB biospecimen records collected during the years 2005-2009 and all CCR records for cancers diagnosed from 1988-2009 based on standard data linkage procedures. RESULTS: The 1040 UCD records with a unique medical record number, tissue site, and pathology date were linked to 3.3 million CCR records. Of these, 844 (81.2%) were identified in both databases. Overall, record matches were highest (100%) for cancers of the cervix and testis/other male genital system organs. For the most common cancers, matches were highest for cancers of the lung and respiratory system (93%), breast (91.7%), and colon and rectum (89.5%), and lower for prostate (72.9%). CONCLUSIONS: This pilot linkage demonstrated that information on existing biospecimens from a cancer center biorepository can be linked successfully to cancer registry data. Linkages between existing biorepositories and cancer registries can foster productive collaborations and provide a foundation for virtual biorepository networks to support population-based biospecimen research.
PURPOSE: Biospecimen-based research offers tremendous promise as a way to increase understanding of the molecular epidemiology of cancers. Population-based cancer registries can augment this research by providing more clinical detail and long-term follow-up information than is typically available from biospecimen annotations. In order to demonstrate the feasibility of this concept, we performed a pilot linkage between the California Cancer Registry (CCR) and the University of California, Davis Cancer Center Biorepository (UCD CCB) databases to determine if we could identify patients with records in both databases. METHODS: We performed a probabilistic data linkage between 2180 UCD CCB biospecimen records collected during the years 2005-2009 and all CCR records for cancers diagnosed from 1988-2009 based on standard data linkage procedures. RESULTS: The 1040 UCD records with a unique medical record number, tissue site, and pathology date were linked to 3.3 million CCR records. Of these, 844 (81.2%) were identified in both databases. Overall, record matches were highest (100%) for cancers of the cervix and testis/other male genital system organs. For the most common cancers, matches were highest for cancers of the lung and respiratory system (93%), breast (91.7%), and colon and rectum (89.5%), and lower for prostate (72.9%). CONCLUSIONS: This pilot linkage demonstrated that information on existing biospecimens from a cancer center biorepository can be linked successfully to cancer registry data. Linkages between existing biorepositories and cancer registries can foster productive collaborations and provide a foundation for virtual biorepository networks to support population-based biospecimen research.
Authors: Marc T Goodman; Brenda Y Hernandez; Stephen Hewitt; Charles F Lynch; Timothy R Coté; Henry F Frierson; Christopher A Moskaluk; Jeffrey L Killeen; Wendy Cozen; Charles R Key; Limin Clegg; Marsha Reichman; Benjamin F Hankey; Brenda Edwards Journal: Hum Pathol Date: 2005-07 Impact factor: 3.466
Authors: Eero Pukkala; Aage Andersen; Göran Berglund; Randi Gislefoss; Vilmundur Gudnason; Göran Hallmans; Egil Jellum; Pekka Jousilahti; Paul Knekt; Pentti Koskela; P Pentti Kyyrönen; Per Lenner; Tapio Luostarinen; Arthur Löve; Helga Ogmundsdóttir; Pär Stattin; Leena Tenkanen; Laufey Tryggvadóttir; Jarmo Virtamo; Göran Wadell; Anders Widell; Matti Lehtinen; Joakim Dillner Journal: Acta Oncol Date: 2007 Impact factor: 4.089
Authors: Rajiv Dhir; Ashok A Patel; Sharon Winters; Michelle Bisceglia; Dennis Swanson; Roger Aamodt; Michael J Becich Journal: Cancer Date: 2008-10-01 Impact factor: 6.860
Authors: Mark E Sherman; Will Howatt; Fiona M Blows; Paul Pharoah; Stephen M Hewitt; Montserrat Garcia-Closas Journal: Cancer Epidemiol Biomarkers Prev Date: 2010-03-23 Impact factor: 4.254