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- Guida, Florence, et al.
(författare)
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Assessment of Lung Cancer Risk on the Basis of a Biomarker Panel of Circulating Proteins
- 2018
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Ingår i: JAMA Oncology. - : American Medical Association (AMA). - 2374-2437 .- 2374-2445. ; 4:10
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Tidskriftsartikel (refereegranskat)abstract
- 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 screening criteria, the sensitivity of the integrated risk prediction (biomarker) model was 0.63 compared with 0.43 for the smoking model. Conversely, at an overall sensitivity of 0.42, based on the US Preventive Services Task Force screening criteria, the integrated risk prediction model yielded a specificity of 0.95 compared with 0.86 for the smoking model.Conclusions and Relevance This study provided a proof of principle in showing that a panel of circulating protein biomarkers may improve lung cancer risk assessment and may be used to define eligibility for computed tomography screening.
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| 2. |
- Lin, Daniel W., et al.
(författare)
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Genetic variants in the LEPR, CRY1, RNASEL, IL4, and ARVCF genes are prognostic markers of prostate cancer-specific mortality
- 2011
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Ingår i: Cancer Epidemiology, Biomarkers and Prevention. - Philadelphia : American Association for Cancer Research. - 1055-9965 .- 1538-7755. ; 20:9, s. 1928-1936
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Tidskriftsartikel (refereegranskat)abstract
- Background: Prostate cancer is the second leading cause of cancer-related deaths in men, accounting for more than 30,000 deaths annually. The purpose of this study was to test whether variation in selected candidate genes in biological pathways of interest for prostate cancer progression could help distinguish patients at higher risk for fatal prostate cancer. Methods: In this hypothesis-driven study, we genotyped 937 single nucleotide polymorphisms (SNPs) in 156 candidate genes in a population-based cohort of 1,309 prostate cancer patients. We identified 22 top-ranking SNPs (P <= 0.01, FDR <= 0.70) associated with prostate cancer-specific mortality (PCSM). A subsequent validation study was completed in an independent population-based cohort of 2,875 prostate cancer patients. Results: Five SNPs were validated (P <= 0.05) as being significantly associated with PCSM, one each in the LEPR, CRY1, RNASEL, IL4, and ARVCF genes. Compared with patients with 0 to 2 of the at-risk genotypes those with 4 to 5 at-risk genotypes had a 50% (95% CI, 1.2-1.9) higher risk of PCSM and risk increased with the number of at-risk genotypes carried (P(trend) = 0.001), adjusting for clinicopathologic factors known to influence prognosis. Conclusion: Five genetic markers were validated to be associated with lethal prostate cancer. Impact: This is the first population-based study to show that germline genetic variants provide prognostic information for prostate cancer-specific survival. The clinical utility of this five-SNP panel to stratify patients at higher risk for adverse outcomes should be evaluated. Cancer Epidemiol Biomarkers Prev; 20(9); 1928-36. (C)2011 AACR.
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