Use of large medical databases to study associations between diseases.
We describe the use of a dataset of statistical medical records, the Oxford Record Linkage Study (ORLS), to identify diseases which occur together more commonly (association), or less commonly (dissociation), than their individual frequencies in the population would predict. We investigated some con...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
2000
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| _version_ | 1797092570618134528 |
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| author | Goldacre, M Kurina, L Yeates, D Seagroatt, V Gill, L |
| author_facet | Goldacre, M Kurina, L Yeates, D Seagroatt, V Gill, L |
| author_sort | Goldacre, M |
| collection | OXFORD |
| description | We describe the use of a dataset of statistical medical records, the Oxford Record Linkage Study (ORLS), to identify diseases which occur together more commonly (association), or less commonly (dissociation), than their individual frequencies in the population would predict. We investigated some conditions known or suspected to enhance the subsequent risk of cancer, some conditions thought to be linked with schizophrenia, and some associations between conditions with a known autoimmune component. Diseases may occur in combination more often (or less often) than expected by chance because one predisposes to (or protects against) another or because they share environmental and/or genetic mechanisms in common. The investigation of such associations can yield important information for clinicians interested in potential disease sequelae, for epidemiologists trying to understand disease aetiology, and for geneticists attempting to determine the genetic basis of variation in disease course among individuals. We suggest that, through the use of datasets like the ORLS, it will be possible to 'map' comprehensively the phenomic expression of co-occurring diseases. |
| first_indexed | 2024-03-07T03:47:51Z |
| format | Journal article |
| id | oxford-uuid:c022ec2f-d24f-4aa6-b8bf-d4c4e25d976a |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T03:47:51Z |
| publishDate | 2000 |
| record_format | dspace |
| spelling | oxford-uuid:c022ec2f-d24f-4aa6-b8bf-d4c4e25d976a2022-03-27T05:52:25ZUse of large medical databases to study associations between diseases.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:c022ec2f-d24f-4aa6-b8bf-d4c4e25d976aEnglishSymplectic Elements at Oxford2000Goldacre, MKurina, LYeates, DSeagroatt, VGill, LWe describe the use of a dataset of statistical medical records, the Oxford Record Linkage Study (ORLS), to identify diseases which occur together more commonly (association), or less commonly (dissociation), than their individual frequencies in the population would predict. We investigated some conditions known or suspected to enhance the subsequent risk of cancer, some conditions thought to be linked with schizophrenia, and some associations between conditions with a known autoimmune component. Diseases may occur in combination more often (or less often) than expected by chance because one predisposes to (or protects against) another or because they share environmental and/or genetic mechanisms in common. The investigation of such associations can yield important information for clinicians interested in potential disease sequelae, for epidemiologists trying to understand disease aetiology, and for geneticists attempting to determine the genetic basis of variation in disease course among individuals. We suggest that, through the use of datasets like the ORLS, it will be possible to 'map' comprehensively the phenomic expression of co-occurring diseases. |
| spellingShingle | Goldacre, M Kurina, L Yeates, D Seagroatt, V Gill, L Use of large medical databases to study associations between diseases. |
| title | Use of large medical databases to study associations between diseases. |
| title_full | Use of large medical databases to study associations between diseases. |
| title_fullStr | Use of large medical databases to study associations between diseases. |
| title_full_unstemmed | Use of large medical databases to study associations between diseases. |
| title_short | Use of large medical databases to study associations between diseases. |
| title_sort | use of large medical databases to study associations between diseases |
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