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Disease risk scores for skin cancers
We trained and validated risk prediction models for the three major types of skin cancer— basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma—on a cross-sectional and longitudinal dataset of 210,000 consented research participants who responded to an online survey covering person...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794415/ https://www.ncbi.nlm.nih.gov/pubmed/33420020 http://dx.doi.org/10.1038/s41467-020-20246-5 |
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author | Fontanillas, Pierre Alipanahi, Babak Furlotte, Nicholas A. Johnson, Michaela Wilson, Catherine H. Pitts, Steven J. Gentleman, Robert Auton, Adam |
author_facet | Fontanillas, Pierre Alipanahi, Babak Furlotte, Nicholas A. Johnson, Michaela Wilson, Catherine H. Pitts, Steven J. Gentleman, Robert Auton, Adam |
author_sort | Fontanillas, Pierre |
collection | PubMed |
description | We trained and validated risk prediction models for the three major types of skin cancer— basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma—on a cross-sectional and longitudinal dataset of 210,000 consented research participants who responded to an online survey covering personal and family history of skin cancer, skin susceptibility, and UV exposure. We developed a primary disease risk score (DRS) that combined all 32 identified genetic and non-genetic risk factors. Top percentile DRS was associated with an up to 13-fold increase (odds ratio per standard deviation increase >2.5) in the risk of developing skin cancer relative to the middle DRS percentile. To derive lifetime risk trajectories for the three skin cancers, we developed a second and age independent disease score, called DRSA. Using incident cases, we demonstrated that DRSA could be used in early detection programs for identifying high risk asymptotic individuals, and predicting when they are likely to develop skin cancer. High DRSA scores were not only associated with earlier disease diagnosis (by up to 14 years), but also with more severe and recurrent forms of skin cancer. |
format | Online Article Text |
id | pubmed-7794415 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-77944152021-01-21 Disease risk scores for skin cancers Fontanillas, Pierre Alipanahi, Babak Furlotte, Nicholas A. Johnson, Michaela Wilson, Catherine H. Pitts, Steven J. Gentleman, Robert Auton, Adam Nat Commun Article We trained and validated risk prediction models for the three major types of skin cancer— basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma—on a cross-sectional and longitudinal dataset of 210,000 consented research participants who responded to an online survey covering personal and family history of skin cancer, skin susceptibility, and UV exposure. We developed a primary disease risk score (DRS) that combined all 32 identified genetic and non-genetic risk factors. Top percentile DRS was associated with an up to 13-fold increase (odds ratio per standard deviation increase >2.5) in the risk of developing skin cancer relative to the middle DRS percentile. To derive lifetime risk trajectories for the three skin cancers, we developed a second and age independent disease score, called DRSA. Using incident cases, we demonstrated that DRSA could be used in early detection programs for identifying high risk asymptotic individuals, and predicting when they are likely to develop skin cancer. High DRSA scores were not only associated with earlier disease diagnosis (by up to 14 years), but also with more severe and recurrent forms of skin cancer. Nature Publishing Group UK 2021-01-08 /pmc/articles/PMC7794415/ /pubmed/33420020 http://dx.doi.org/10.1038/s41467-020-20246-5 Text en © The Author(s) 2021 Open Access 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 http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Fontanillas, Pierre Alipanahi, Babak Furlotte, Nicholas A. Johnson, Michaela Wilson, Catherine H. Pitts, Steven J. Gentleman, Robert Auton, Adam Disease risk scores for skin cancers |
title | Disease risk scores for skin cancers |
title_full | Disease risk scores for skin cancers |
title_fullStr | Disease risk scores for skin cancers |
title_full_unstemmed | Disease risk scores for skin cancers |
title_short | Disease risk scores for skin cancers |
title_sort | disease risk scores for skin cancers |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7794415/ https://www.ncbi.nlm.nih.gov/pubmed/33420020 http://dx.doi.org/10.1038/s41467-020-20246-5 |
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