Automated uro-oncology data collection: the Cancer Research Uro-Oncology Database.
OBJECTIVE: To develop a relational database (Cancer Research Uro-Oncology Database, CRUD) to enable automatic data collection on all urological malignancies within our region, as there is increasing emphasis on good data collection for surgical patients with cancer, and numerous overlapping systems...
| Main Authors: | , , , , , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2010
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| _version_ | 1826294873621266432 |
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| author | Charlesworth, P Kilbey, N Taylor, M Leek, R Cranston, D Turner, G Crew, J Harris, A Protheroe, A |
| author_facet | Charlesworth, P Kilbey, N Taylor, M Leek, R Cranston, D Turner, G Crew, J Harris, A Protheroe, A |
| author_sort | Charlesworth, P |
| collection | OXFORD |
| description | OBJECTIVE: To develop a relational database (Cancer Research Uro-Oncology Database, CRUD) to enable automatic data collection on all urological malignancies within our region, as there is increasing emphasis on good data collection for surgical patients with cancer, and numerous overlapping systems that are amassing data on the same patients. METHODS: Links have been established between pathological databases, multidisciplinary team data-collection systems and patient-survival monitoring facilities, providing accurate pathology, treatment and survival data on all of uro-oncology patients. We are also developing individual modules for the oncological surgeons within our unit that are compatible with the British Association of Urological Surgeons (Section of Oncology), and have plans to connect to the Medical and Clinical Oncology data systems in the future. RESULTS: Pre-existing protocols for fresh tissue, plasma and urine collection have been incorporated within CRUD via a tissue-tracking system, to comply with the Human Tissue Act 2004, and link these samples to accurate clinical, pathological and survival data. Many research and audit projects have already used these data, including the construction of a 274-case tissue microarray for renal cell carcinoma, microRNA hybridization arrays and analysis of 900 nephrectomy cases from the past three decades. CONCLUSIONS: Our work over the past 3 years in Oxford has established numerous links with organizations collecting data on our uro-oncological patients, and we are now able to collect this excellent combined data on all of these patients, in an automated manner. |
| first_indexed | 2024-03-07T03:52:24Z |
| format | Journal article |
| id | oxford-uuid:c1b90c44-f55e-4252-9e03-b2dee8f762c4 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T03:52:24Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | oxford-uuid:c1b90c44-f55e-4252-9e03-b2dee8f762c42022-03-27T06:03:40ZAutomated uro-oncology data collection: the Cancer Research Uro-Oncology Database.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:c1b90c44-f55e-4252-9e03-b2dee8f762c4EnglishSymplectic Elements at Oxford2010Charlesworth, PKilbey, NTaylor, MLeek, RCranston, DTurner, GCrew, JHarris, AProtheroe, A OBJECTIVE: To develop a relational database (Cancer Research Uro-Oncology Database, CRUD) to enable automatic data collection on all urological malignancies within our region, as there is increasing emphasis on good data collection for surgical patients with cancer, and numerous overlapping systems that are amassing data on the same patients. METHODS: Links have been established between pathological databases, multidisciplinary team data-collection systems and patient-survival monitoring facilities, providing accurate pathology, treatment and survival data on all of uro-oncology patients. We are also developing individual modules for the oncological surgeons within our unit that are compatible with the British Association of Urological Surgeons (Section of Oncology), and have plans to connect to the Medical and Clinical Oncology data systems in the future. RESULTS: Pre-existing protocols for fresh tissue, plasma and urine collection have been incorporated within CRUD via a tissue-tracking system, to comply with the Human Tissue Act 2004, and link these samples to accurate clinical, pathological and survival data. Many research and audit projects have already used these data, including the construction of a 274-case tissue microarray for renal cell carcinoma, microRNA hybridization arrays and analysis of 900 nephrectomy cases from the past three decades. CONCLUSIONS: Our work over the past 3 years in Oxford has established numerous links with organizations collecting data on our uro-oncological patients, and we are now able to collect this excellent combined data on all of these patients, in an automated manner. |
| spellingShingle | Charlesworth, P Kilbey, N Taylor, M Leek, R Cranston, D Turner, G Crew, J Harris, A Protheroe, A Automated uro-oncology data collection: the Cancer Research Uro-Oncology Database. |
| title | Automated uro-oncology data collection: the Cancer Research Uro-Oncology Database. |
| title_full | Automated uro-oncology data collection: the Cancer Research Uro-Oncology Database. |
| title_fullStr | Automated uro-oncology data collection: the Cancer Research Uro-Oncology Database. |
| title_full_unstemmed | Automated uro-oncology data collection: the Cancer Research Uro-Oncology Database. |
| title_short | Automated uro-oncology data collection: the Cancer Research Uro-Oncology Database. |
| title_sort | automated uro oncology data collection the cancer research uro oncology database |
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