Journal article
Lung cancer risk discrimination of prediagnostic proteomics measurements compared with existing prediction tools
X Feng, WYY Wu, JU Onwuka, Z Haider, K Alcala, K Smith-Byrne, H Zahed, F Guida, R Wang, JK Bassett, V Stevens, Y Wang, S Weinstein, ND Freedman, C Chen, L Tinker, TH Nøst, WP Koh, D Muller, SM Colorado-Yohar Show all
Journal of the National Cancer Institute | OXFORD UNIV PRESS INC | Published : 2023
DOI: 10.1093/jnci/djad071
Abstract
Background: We sought to develop a proteomics-based risk model for lung cancer and evaluate its risk-discriminatory performance in comparison with a smoking-based risk model (PLCOm2012) and a commercially available autoantibody biomarker test Methods: We designed a case-control study nested in 6 prospective cohorts, including 624 lung cancer participants who donated blood samples at most 3 years prior to lung cancer diagnosis and 624 smoking-matched cancer free participants who were assayed for 302 proteins. We used 470 case-control pairs from 4 cohorts to select proteins and train a protein-based risk model. We subsequently used 154 case-control pairs from 2 cohorts to compare the risk-disc..
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Grants
Awarded by Fakulteit Geneeskunde en Gesondheidswetenskappe, Universiteit Stellenbosch
Funding Acknowledgements
This study was supported by the US NCI (INTEGRAL program U19 CA203654 and R03 CA245979), l'Institut National Du Cancer (2019-1-TABAC-01, INCa, France), the Cancer Research Foundation of Northern Sweden (AMP19-962), an early detection of cancer development grant from Swedish Department of Health ministry, and Cancer Research UK [C18281/A29019]. RJH is supported by the Canada Research Chair of the Canadian Institute of Health Research.