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...

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Main Authors: Guida, F., Sun, N., Bantis, L.E., Muller, D.C., Li, P., Taguchi, A., Dhillon, D., Kundnani, D.L., Patel, N.J., Yan, Q., Byrnes, G., Moons, K.G.M., Tjønneland, A., Panico, S., Agnoli, C., Vineis, P., Palli, D., Bueno-De-Mesquita, B., Peeters, P.H., Agudo, A., Huerta, J.M., Dorronsoro, M., Barranco, M.R., Ardanaz, E., Travis, R.C., Byrne, K.S., Boeing, H., Steffen, A., Kaaks, R., Hüsing, A., Trichopoulou, A., Lagiou, P., La Vecchia, C., Severi, G., Boutron-Ruault, M.-C., Sandanger, T.M., Weiderpass, E., Nøst, T.H., Tsilidis, K., Riboli, E., Grankvist, K., Johansson, M., Goodman, G.E., Feng, Z., Brennan, P., Hanash, S.M.
Format: Article in Journal/Newspaper
Language:English
Published: 2018
Subjects:
Online Access:https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3085626
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spelling ftnkunivathens:oai:lib.uoa.gr:uoadl:3085626 2024-02-11T10:07:12+01:00 Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins Guida, F. Sun, N. Bantis, L.E. Muller, D.C. Li, P. Taguchi, A. Dhillon, D. Kundnani, D.L. Patel, N.J. Yan, Q. Byrnes, G. Moons, K.G.M. Tjønneland, A. Panico, S. Agnoli, C. Vineis, P. Palli, D. Bueno-De-Mesquita, B. Peeters, P.H. Agudo, A. Huerta, J.M. Dorronsoro, M. Barranco, M.R. Ardanaz, E. Travis, R.C. Byrne, K.S. Boeing, H. Steffen, A. Kaaks, R. Hüsing, A. Trichopoulou, A. Lagiou, P. La Vecchia, C. Severi, G. Boutron-Ruault, M.-C. Sandanger, T.M. Weiderpass, E. Nøst, T.H. Tsilidis, K. Riboli, E. Grankvist, K. Johansson, M. Goodman, G.E. Feng, Z. Brennan, P. Hanash, S.M. 2018-01-01 https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3085626 Αγγλικά English eng uoadl:3085626 https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3085626 scientific_publication_article Επιστημονική δημοσίευση - Άρθρο Περιοδικού Scientific publication - Journal Article 2018 ftnkunivathens 2024-01-18T19:11:48Z 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 ... Article in Journal/Newspaper Northern Sweden Pergamos - Library and Information Center of National and Kapodistrian University of Athens
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collection Pergamos - Library and Information Center of National and Kapodistrian University of Athens
op_collection_id ftnkunivathens
language English
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 Article in Journal/Newspaper
author Guida, F.
Sun, N.
Bantis, L.E.
Muller, D.C.
Li, P.
Taguchi, A.
Dhillon, D.
Kundnani, D.L.
Patel, N.J.
Yan, Q.
Byrnes, G.
Moons, K.G.M.
Tjønneland, A.
Panico, S.
Agnoli, C.
Vineis, P.
Palli, D.
Bueno-De-Mesquita, B.
Peeters, P.H.
Agudo, A.
Huerta, J.M.
Dorronsoro, M.
Barranco, M.R.
Ardanaz, E.
Travis, R.C.
Byrne, K.S.
Boeing, H.
Steffen, A.
Kaaks, R.
Hüsing, A.
Trichopoulou, A.
Lagiou, P.
La Vecchia, C.
Severi, G.
Boutron-Ruault, M.-C.
Sandanger, T.M.
Weiderpass, E.
Nøst, T.H.
Tsilidis, K.
Riboli, E.
Grankvist, K.
Johansson, M.
Goodman, G.E.
Feng, Z.
Brennan, P.
Hanash, S.M.
spellingShingle Guida, F.
Sun, N.
Bantis, L.E.
Muller, D.C.
Li, P.
Taguchi, A.
Dhillon, D.
Kundnani, D.L.
Patel, N.J.
Yan, Q.
Byrnes, G.
Moons, K.G.M.
Tjønneland, A.
Panico, S.
Agnoli, C.
Vineis, P.
Palli, D.
Bueno-De-Mesquita, B.
Peeters, P.H.
Agudo, A.
Huerta, J.M.
Dorronsoro, M.
Barranco, M.R.
Ardanaz, E.
Travis, R.C.
Byrne, K.S.
Boeing, H.
Steffen, A.
Kaaks, R.
Hüsing, A.
Trichopoulou, A.
Lagiou, P.
La Vecchia, C.
Severi, G.
Boutron-Ruault, M.-C.
Sandanger, T.M.
Weiderpass, E.
Nøst, T.H.
Tsilidis, K.
Riboli, E.
Grankvist, K.
Johansson, M.
Goodman, G.E.
Feng, Z.
Brennan, P.
Hanash, S.M.
Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins
author_facet Guida, F.
Sun, N.
Bantis, L.E.
Muller, D.C.
Li, P.
Taguchi, A.
Dhillon, D.
Kundnani, D.L.
Patel, N.J.
Yan, Q.
Byrnes, G.
Moons, K.G.M.
Tjønneland, A.
Panico, S.
Agnoli, C.
Vineis, P.
Palli, D.
Bueno-De-Mesquita, B.
Peeters, P.H.
Agudo, A.
Huerta, J.M.
Dorronsoro, M.
Barranco, M.R.
Ardanaz, E.
Travis, R.C.
Byrne, K.S.
Boeing, H.
Steffen, A.
Kaaks, R.
Hüsing, A.
Trichopoulou, A.
Lagiou, P.
La Vecchia, C.
Severi, G.
Boutron-Ruault, M.-C.
Sandanger, T.M.
Weiderpass, E.
Nøst, T.H.
Tsilidis, K.
Riboli, E.
Grankvist, K.
Johansson, M.
Goodman, G.E.
Feng, Z.
Brennan, P.
Hanash, S.M.
author_sort Guida, F.
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
publishDate 2018
url https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3085626
genre Northern Sweden
genre_facet Northern Sweden
op_relation uoadl:3085626
https://pergamos.lib.uoa.gr/uoa/dl/object/uoadl:3085626
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