Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins
IMPORTANCE: There is an urgent need to improve lung cancer risk assessment because current screening criteria miss a large proportion of cases. OBJECTIVE: To investigate whether a lung cancer risk prediction model based on a panel of selected circulating protein biomarkers can outperform a tradition...
Published in: | JAMA Oncology |
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American Medical Association
2018
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Online Access: | http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6233784/ http://www.ncbi.nlm.nih.gov/pubmed/30003238 https://doi.org/10.1001/jamaoncol.2018.2078 |
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ftpubmed:oai:pubmedcentral.nih.gov:6233784 2023-05-15T17:45:07+02:00 Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins Guida, Florence Sun, Nan Bantis, Leonidas E. Muller, David C. Li, Peng Taguchi, Ayumu Dhillon, Dilsher Kundnani, Deepali L. Patel, Nikul J. Yan, Qingxiang Byrnes, Graham Moons, Karel G. M. Tjønneland, Anne Panico, Salvatore Agnoli, Claudia Vineis, Paolo Palli, Domenico Bueno-de-Mesquita, Bas Peeters, Petra H. Agudo, Antonio Huerta, Jose M. Dorronsoro, Miren Barranco, Miguel Rodriguez Ardanaz, Eva Travis, Ruth C. Byrne, Karl Smith Boeing, Heiner Steffen, Annika Kaaks, Rudolf Hüsing, Anika Trichopoulou, Antonia Lagiou, Pagona La Vecchia, Carlo Severi, Gianluca Boutron-Ruault, Marie-Christine Sandanger, Torkjel M. Weiderpass, Elisabete Nøst, Therese H. Tsilidis, Kostas Riboli, Elio Grankvist, Kjell Johansson, Mikael Goodman, Gary E. Feng, Ziding Brennan, Paul Johansson, Mattias Hanash, Samir M. 2018-07-12 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6233784/ http://www.ncbi.nlm.nih.gov/pubmed/30003238 https://doi.org/10.1001/jamaoncol.2018.2078 en eng American Medical Association http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6233784/ http://www.ncbi.nlm.nih.gov/pubmed/30003238 http://dx.doi.org/10.1001/jamaoncol.2018.2078 Copyright 2018 American Medical Association. All Rights Reserved. Brief Report Text 2018 ftpubmed https://doi.org/10.1001/jamaoncol.2018.2078 2019-07-14T00:25:53Z IMPORTANCE: There is an urgent need to improve lung cancer risk assessment because current screening criteria miss a large proportion of cases. OBJECTIVE: To investigate whether a lung cancer risk prediction model based on a panel of selected circulating protein biomarkers can outperform a traditional risk prediction model and current US screening criteria. DESIGN, SETTING, AND PARTICIPANTS: Prediagnostic samples from 108 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and samples from 216 smoking-matched controls from the Carotene and Retinol Efficacy Trial (CARET) cohort were used to develop a biomarker risk score based on 4 proteins (cancer antigen 125 [CA125], carcinoembryonic antigen [CEA], cytokeratin-19 fragment [CYFRA 21-1], and the precursor form of surfactant protein B [Pro-SFTPB]). The biomarker score was subsequently validated blindly using absolute risk estimates among 63 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and 90 matched controls from 2 large European population-based cohorts, the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Northern Sweden Health and Disease Study (NSHDS). MAIN OUTCOMES AND MEASURES: Model validity in discriminating between future lung cancer cases and controls. Discrimination estimates were weighted to reflect the background populations of EPIC and NSHDS validation studies (area under the receiver-operating characteristics curve [AUC], sensitivity, and specificity). RESULTS: In the validation study of 63 ever-smoking patients with lung cancer and 90 matched controls (mean [SD] age, 57.7 [8.7] years; 68.6% men) from EPIC and NSHDS, an integrated risk prediction model that combined smoking exposure with the biomarker score yielded an AUC of 0.83 (95% CI, 0.76-0.90) compared with 0.73 (95% CI, 0.64-0.82) for a model based on smoking exposure alone (P = .003 for difference in AUC). At an overall specificity of 0.83, based on the US Preventive Services Task Force ... Text Northern Sweden PubMed Central (PMC) JAMA Oncology 4 10 e182078 |
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Brief Report |
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Brief Report Guida, Florence Sun, Nan Bantis, Leonidas E. Muller, David C. Li, Peng Taguchi, Ayumu Dhillon, Dilsher Kundnani, Deepali L. Patel, Nikul J. Yan, Qingxiang Byrnes, Graham Moons, Karel G. M. Tjønneland, Anne Panico, Salvatore Agnoli, Claudia Vineis, Paolo Palli, Domenico Bueno-de-Mesquita, Bas Peeters, Petra H. Agudo, Antonio Huerta, Jose M. Dorronsoro, Miren Barranco, Miguel Rodriguez Ardanaz, Eva Travis, Ruth C. Byrne, Karl Smith Boeing, Heiner Steffen, Annika Kaaks, Rudolf Hüsing, Anika Trichopoulou, Antonia Lagiou, Pagona La Vecchia, Carlo Severi, Gianluca Boutron-Ruault, Marie-Christine Sandanger, Torkjel M. Weiderpass, Elisabete Nøst, Therese H. Tsilidis, Kostas Riboli, Elio Grankvist, Kjell Johansson, Mikael Goodman, Gary E. Feng, Ziding Brennan, Paul Johansson, Mattias Hanash, Samir M. Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins |
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Brief Report |
description |
IMPORTANCE: There is an urgent need to improve lung cancer risk assessment because current screening criteria miss a large proportion of cases. OBJECTIVE: To investigate whether a lung cancer risk prediction model based on a panel of selected circulating protein biomarkers can outperform a traditional risk prediction model and current US screening criteria. DESIGN, SETTING, AND PARTICIPANTS: Prediagnostic samples from 108 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and samples from 216 smoking-matched controls from the Carotene and Retinol Efficacy Trial (CARET) cohort were used to develop a biomarker risk score based on 4 proteins (cancer antigen 125 [CA125], carcinoembryonic antigen [CEA], cytokeratin-19 fragment [CYFRA 21-1], and the precursor form of surfactant protein B [Pro-SFTPB]). The biomarker score was subsequently validated blindly using absolute risk estimates among 63 ever-smoking patients with lung cancer diagnosed within 1 year after blood collection and 90 matched controls from 2 large European population-based cohorts, the European Prospective Investigation into Cancer and Nutrition (EPIC) and the Northern Sweden Health and Disease Study (NSHDS). MAIN OUTCOMES AND MEASURES: Model validity in discriminating between future lung cancer cases and controls. Discrimination estimates were weighted to reflect the background populations of EPIC and NSHDS validation studies (area under the receiver-operating characteristics curve [AUC], sensitivity, and specificity). RESULTS: In the validation study of 63 ever-smoking patients with lung cancer and 90 matched controls (mean [SD] age, 57.7 [8.7] years; 68.6% men) from EPIC and NSHDS, an integrated risk prediction model that combined smoking exposure with the biomarker score yielded an AUC of 0.83 (95% CI, 0.76-0.90) compared with 0.73 (95% CI, 0.64-0.82) for a model based on smoking exposure alone (P = .003 for difference in AUC). At an overall specificity of 0.83, based on the US Preventive Services Task Force ... |
format |
Text |
author |
Guida, Florence Sun, Nan Bantis, Leonidas E. Muller, David C. Li, Peng Taguchi, Ayumu Dhillon, Dilsher Kundnani, Deepali L. Patel, Nikul J. Yan, Qingxiang Byrnes, Graham Moons, Karel G. M. Tjønneland, Anne Panico, Salvatore Agnoli, Claudia Vineis, Paolo Palli, Domenico Bueno-de-Mesquita, Bas Peeters, Petra H. Agudo, Antonio Huerta, Jose M. Dorronsoro, Miren Barranco, Miguel Rodriguez Ardanaz, Eva Travis, Ruth C. Byrne, Karl Smith Boeing, Heiner Steffen, Annika Kaaks, Rudolf Hüsing, Anika Trichopoulou, Antonia Lagiou, Pagona La Vecchia, Carlo Severi, Gianluca Boutron-Ruault, Marie-Christine Sandanger, Torkjel M. Weiderpass, Elisabete Nøst, Therese H. Tsilidis, Kostas Riboli, Elio Grankvist, Kjell Johansson, Mikael Goodman, Gary E. Feng, Ziding Brennan, Paul Johansson, Mattias Hanash, Samir M. |
author_facet |
Guida, Florence Sun, Nan Bantis, Leonidas E. Muller, David C. Li, Peng Taguchi, Ayumu Dhillon, Dilsher Kundnani, Deepali L. Patel, Nikul J. Yan, Qingxiang Byrnes, Graham Moons, Karel G. M. Tjønneland, Anne Panico, Salvatore Agnoli, Claudia Vineis, Paolo Palli, Domenico Bueno-de-Mesquita, Bas Peeters, Petra H. Agudo, Antonio Huerta, Jose M. Dorronsoro, Miren Barranco, Miguel Rodriguez Ardanaz, Eva Travis, Ruth C. Byrne, Karl Smith Boeing, Heiner Steffen, Annika Kaaks, Rudolf Hüsing, Anika Trichopoulou, Antonia Lagiou, Pagona La Vecchia, Carlo Severi, Gianluca Boutron-Ruault, Marie-Christine Sandanger, Torkjel M. Weiderpass, Elisabete Nøst, Therese H. Tsilidis, Kostas Riboli, Elio Grankvist, Kjell Johansson, Mikael Goodman, Gary E. Feng, Ziding Brennan, Paul Johansson, Mattias Hanash, Samir M. |
author_sort |
Guida, Florence |
title |
Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins |
title_short |
Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins |
title_full |
Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins |
title_fullStr |
Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins |
title_full_unstemmed |
Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins |
title_sort |
assessment of lung cancer risk on the basis of a biomarker panel of circulating proteins |
publisher |
American Medical Association |
publishDate |
2018 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6233784/ http://www.ncbi.nlm.nih.gov/pubmed/30003238 https://doi.org/10.1001/jamaoncol.2018.2078 |
genre |
Northern Sweden |
genre_facet |
Northern Sweden |
op_relation |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6233784/ http://www.ncbi.nlm.nih.gov/pubmed/30003238 http://dx.doi.org/10.1001/jamaoncol.2018.2078 |
op_rights |
Copyright 2018 American Medical Association. All Rights Reserved. |
op_doi |
https://doi.org/10.1001/jamaoncol.2018.2078 |
container_title |
JAMA Oncology |
container_volume |
4 |
container_issue |
10 |
container_start_page |
e182078 |
_version_ |
1766147878717227008 |