| Title: |
Lung cancer risk discrimination of prediagnostic proteomics measurements compared with existing prediction tools |
| Authors: |
Feng, X; Wu, WYY; Onwuka, JU; Haider, Z; Alcala, K; Smith-Byrne, K; Zahed, H; Guida, F; Wang, R; Bassett, JK; Stevens, V; Wang, Y; Weinstein, S; Freedman, ND; Chen, C; Tinker, L; Nøst, TH; Koh, WP; Muller, D; Colorado-Yohar, SM; Tumino, R; Hung, RJ; Amos, CI; Lin, X; Zhang, X; Arslan, AA; Sánchez, MJ; Sørgjerd, EP; Severi, G; Hveem, K; Brennan, P; Langhammer, A; Milne, RL; Yuan, JM; Melin, B; Johansson, M; Robbins, HA |
| Publisher Information: |
OXFORD UNIV PRESS INC |
| Publication Year: |
2023 |
| Collection: |
The University of Melbourne: Digital Repository |
| Description: |
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-discriminatory performance of the protein-based model with that of the Early Cancer Detection Test (EarlyCDT)-Lung and the PLCOm2012 model using receiver operating characteristics analysis and by estimating models' sensitivity. All tests were 2-sided. RESULTS: The area under the curve for the protein-based risk model in the validation sample was 0.75 (95% confidence interval [CI] = 0.70 to 0.81) compared with 0.64 (95% CI = 0.57 to 0.70) for the PLCOm2012 model (Pdifference = .001). The EarlyCDT-Lung had a sensitivity of 14% (95% CI = 8.2% to 19%) and a specificity of 86% (95% CI = 81% to 92%) for incident lung cancer. At the same specificity of 86%, the sensitivity for the protein-based risk model was estimated at 49% (95% CI = 41% to 57%) and 30% (95% CI = 23% to 37%) for the PLCOm2012 model. CONCLUSION: Circulating proteins showed promise in predicting incident lung cancer and outperformed a standard risk prediction model and the commercialized EarlyCDT-Lung. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| ISSN: |
0027-8874 |
| Relation: |
NHMRC/209057; pii: 7186270; https://hdl.handle.net/11343/338907 |
| Availability: |
https://hdl.handle.net/11343/338907 |
| Rights: |
https://creativecommons.org/licenses/by-nc/4.0 ; CC BY-NC |
| Accession Number: |
edsbas.B69D28FF |
| Database: |
BASE |