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Estimating the referral rate for cancer genetic assessment from a systematic review of the evidence
To estimate the optimal proportion of new patients diagnosed with cancer who require assessment and evaluation for familial cancer genetic risk, based on the best evidence available. We identified evidence of the patients who require assessment for familial genetic risk when diagnosed with cancer th...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Nature Publishing Group
2007
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2360013/ https://www.ncbi.nlm.nih.gov/pubmed/17242707 http://dx.doi.org/10.1038/sj.bjc.6603432 |
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author | Featherstone, C Colley, A Tucker, K Kirk, J Barton, M B |
author_facet | Featherstone, C Colley, A Tucker, K Kirk, J Barton, M B |
author_sort | Featherstone, C |
collection | PubMed |
description | To estimate the optimal proportion of new patients diagnosed with cancer who require assessment and evaluation for familial cancer genetic risk, based on the best evidence available. We identified evidence of the patients who require assessment for familial genetic risk when diagnosed with cancer through extensive literature reviews and searches of guidelines. Epidemiological data on the distribution of cancer type, presence of a family history, age and other factors that influence referral for genetic assessment were identified. Decision trees were constructed to merge the evidence-based recommendations with the epidemiological data to calculate the optimal proportion of patients who should be referred. We identified ‘high probability’ and ‘moderate probability’ groups for having a genetic susceptibility. The proportion of patients diagnosed with cancer in Australia who have a high probability of having a genetic predisposition and who should be referred for genetic assessment is 1%. If the moderate probability group is also assessed this proportion increases to 6%. This model has identified the proportion of new patients diagnosed with cancer who should be referred for genetic assessment. This data is the first step in determining the resources required for provision of an adequate cancer genetic service. |
format | Text |
id | pubmed-2360013 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-23600132009-09-10 Estimating the referral rate for cancer genetic assessment from a systematic review of the evidence Featherstone, C Colley, A Tucker, K Kirk, J Barton, M B Br J Cancer Genetics and Genomics To estimate the optimal proportion of new patients diagnosed with cancer who require assessment and evaluation for familial cancer genetic risk, based on the best evidence available. We identified evidence of the patients who require assessment for familial genetic risk when diagnosed with cancer through extensive literature reviews and searches of guidelines. Epidemiological data on the distribution of cancer type, presence of a family history, age and other factors that influence referral for genetic assessment were identified. Decision trees were constructed to merge the evidence-based recommendations with the epidemiological data to calculate the optimal proportion of patients who should be referred. We identified ‘high probability’ and ‘moderate probability’ groups for having a genetic susceptibility. The proportion of patients diagnosed with cancer in Australia who have a high probability of having a genetic predisposition and who should be referred for genetic assessment is 1%. If the moderate probability group is also assessed this proportion increases to 6%. This model has identified the proportion of new patients diagnosed with cancer who should be referred for genetic assessment. This data is the first step in determining the resources required for provision of an adequate cancer genetic service. Nature Publishing Group 2007-01-29 2007-01-23 /pmc/articles/PMC2360013/ /pubmed/17242707 http://dx.doi.org/10.1038/sj.bjc.6603432 Text en Copyright © 2007 Cancer Research UK https://creativecommons.org/licenses/by/4.0/This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material.If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit https://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Genetics and Genomics Featherstone, C Colley, A Tucker, K Kirk, J Barton, M B Estimating the referral rate for cancer genetic assessment from a systematic review of the evidence |
title | Estimating the referral rate for cancer genetic assessment from a systematic review of the evidence |
title_full | Estimating the referral rate for cancer genetic assessment from a systematic review of the evidence |
title_fullStr | Estimating the referral rate for cancer genetic assessment from a systematic review of the evidence |
title_full_unstemmed | Estimating the referral rate for cancer genetic assessment from a systematic review of the evidence |
title_short | Estimating the referral rate for cancer genetic assessment from a systematic review of the evidence |
title_sort | estimating the referral rate for cancer genetic assessment from a systematic review of the evidence |
topic | Genetics and Genomics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2360013/ https://www.ncbi.nlm.nih.gov/pubmed/17242707 http://dx.doi.org/10.1038/sj.bjc.6603432 |
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