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Comparison of discriminatory power and accuracy of three lung cancer risk models
BACKGROUND: Three lung cancer (LC) models have recently been constructed to predict an individual's absolute risk of LC within a defined period. Given their potential application in prevention strategies, a comparison of their accuracy in an independent population is important. METHODS: We used...
Autores principales: | , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2010
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2920015/ https://www.ncbi.nlm.nih.gov/pubmed/20588271 http://dx.doi.org/10.1038/sj.bjc.6605759 |
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author | D'Amelio, A M Cassidy, A Asomaning, K Raji, O Y Duffy, S W Field, J K Spitz, M R Christiani, D Etzel, C J |
author_facet | D'Amelio, A M Cassidy, A Asomaning, K Raji, O Y Duffy, S W Field, J K Spitz, M R Christiani, D Etzel, C J |
author_sort | D'Amelio, A M |
collection | PubMed |
description | BACKGROUND: Three lung cancer (LC) models have recently been constructed to predict an individual's absolute risk of LC within a defined period. Given their potential application in prevention strategies, a comparison of their accuracy in an independent population is important. METHODS: We used data for 3197 patients with LC and 1703 cancer-free controls recruited to an ongoing case–control study at the Harvard School of Public Health and Massachusetts General Hospital. We estimated the 5-year LC risk for each risk model and compared the discriminatory power, accuracy, and clinical utility of these models. RESULTS: Overall, the Liverpool Lung Project (LLP) and Spitz models had comparable discriminatory power (0.69), whereas the Bach model had significantly lower power (0.66; P=0.02). Positive predictive values were highest with the Spitz models, whereas negative predictive values were highest with the LLP model. The Spitz and Bach models had lower sensitivity but better specificity than did the LLP model. CONCLUSION: We observed modest differences in discriminatory power among the three LC risk models, but discriminatory powers were moderate at best, highlighting the difficulty in developing effective risk models. |
format | Text |
id | pubmed-2920015 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-29200152011-07-27 Comparison of discriminatory power and accuracy of three lung cancer risk models D'Amelio, A M Cassidy, A Asomaning, K Raji, O Y Duffy, S W Field, J K Spitz, M R Christiani, D Etzel, C J Br J Cancer Epidemiology BACKGROUND: Three lung cancer (LC) models have recently been constructed to predict an individual's absolute risk of LC within a defined period. Given their potential application in prevention strategies, a comparison of their accuracy in an independent population is important. METHODS: We used data for 3197 patients with LC and 1703 cancer-free controls recruited to an ongoing case–control study at the Harvard School of Public Health and Massachusetts General Hospital. We estimated the 5-year LC risk for each risk model and compared the discriminatory power, accuracy, and clinical utility of these models. RESULTS: Overall, the Liverpool Lung Project (LLP) and Spitz models had comparable discriminatory power (0.69), whereas the Bach model had significantly lower power (0.66; P=0.02). Positive predictive values were highest with the Spitz models, whereas negative predictive values were highest with the LLP model. The Spitz and Bach models had lower sensitivity but better specificity than did the LLP model. CONCLUSION: We observed modest differences in discriminatory power among the three LC risk models, but discriminatory powers were moderate at best, highlighting the difficulty in developing effective risk models. Nature Publishing Group 2010-07-27 2010-06-29 /pmc/articles/PMC2920015/ /pubmed/20588271 http://dx.doi.org/10.1038/sj.bjc.6605759 Text en Copyright © 2010 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 | Epidemiology D'Amelio, A M Cassidy, A Asomaning, K Raji, O Y Duffy, S W Field, J K Spitz, M R Christiani, D Etzel, C J Comparison of discriminatory power and accuracy of three lung cancer risk models |
title | Comparison of discriminatory power and accuracy of three lung cancer risk models |
title_full | Comparison of discriminatory power and accuracy of three lung cancer risk models |
title_fullStr | Comparison of discriminatory power and accuracy of three lung cancer risk models |
title_full_unstemmed | Comparison of discriminatory power and accuracy of three lung cancer risk models |
title_short | Comparison of discriminatory power and accuracy of three lung cancer risk models |
title_sort | comparison of discriminatory power and accuracy of three lung cancer risk models |
topic | Epidemiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2920015/ https://www.ncbi.nlm.nih.gov/pubmed/20588271 http://dx.doi.org/10.1038/sj.bjc.6605759 |
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