Lung cancer risk discrimination of prediagnostic proteomics measurements compared with existing prediction tools.
J Natl Cancer Inst
; 115(9): 1050-1059, 2023 09 07.
Article
em En
| MEDLINE
| ID: mdl-37260165
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-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.
Texto completo:
1
Coleções:
01-internacional
Temas:
Geral
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Tipos_de_cancer
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Pulmao
Base de dados:
MEDLINE
Assunto principal:
Proteômica
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Neoplasias Pulmonares
Tipo de estudo:
Diagnostic_studies
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Etiology_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
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Screening_studies
Limite:
Humans
Idioma:
En
Revista:
J Natl Cancer Inst
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
França