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- Larose, Tricia L., et al.
(author)
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Circulating cotinine concentrations and lung cancer risk in the Lung Cancer Cohort Consortium (LC3)
- 2018
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In: International Journal of Epidemiology. - : Oxford University Press. - 0300-5771 .- 1464-3685. ; 47:6, s. 1760-1771
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Journal article (peer-reviewed)abstract
- Background: Self-reported smoking is the principal measure used to assess lung cancer risk in epidemiological studies. We evaluated if circulating cotinine—a nicotine metabolite and biomarker of recent tobacco exposure—provides additional information on lung cancer risk.Methods: The study was conducted in the Lung Cancer Cohort Consortium (LC3) involving 20 prospective cohort studies. Pre-diagnostic serum cotinine concentrations were measured in one laboratory on 5364 lung cancer cases and 5364 individually matched controls. We used conditional logistic regression to evaluate the association between circulating cotinine and lung cancer, and assessed if cotinine provided additional risk-discriminative information compared with self-reported smoking (smoking status, smoking intensity, smoking duration), using receiver-operating characteristic (ROC) curve analysis.Results: We observed a strong positive association between cotinine and lung cancer risk for current smokers [odds ratio (OR ) per 500 nmol/L increase in cotinine (OR500): 1.39, 95% confidence interval (CI): 1.32–1.47]. Cotinine concentrations consistent with active smoking (≥115 nmol/L) were common in former smokers (cases: 14.6%; controls: 9.2%) and rare in never smokers (cases: 2.7%; controls: 0.8%). Former and never smokers with cotinine concentrations indicative of active smoking (≥115 nmol/L) also showed increased lung cancer risk. For current smokers, the risk-discriminative performance of cotinine combined with self-reported smoking (AUCintegrated: 0.69, 95% CI: 0.68–0.71) yielded a small improvement over self-reported smoking alone (AUCsmoke: 0.66, 95% CI: 0.64–0.68) (P = 1.5x10–9).Conclusions: Circulating cotinine concentrations are consistently associated with lung cancer risk for current smokers and provide additional risk-discriminative information compared with self-report smoking alone.
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- Robbins, Hilary A., et al.
(author)
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Design and methodological considerations for biomarker discovery and validation in the Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Program
- 2023
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In: Annals of Epidemiology. - : Elsevier. - 1047-2797 .- 1873-2585. ; 77, s. 1-12
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Journal article (peer-reviewed)abstract
- The Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) program is an NCI-funded initiative with an objective to develop tools to optimize low-dose CT (LDCT) lung cancer screening. Here, we describe the rationale and design for the Risk Biomarker and Nodule Malignancy projects within INTEGRAL. The overarching goal of these projects is to systematically investigate circulating protein markers to include on a panel for use (i) pre-LDCT, to identify people likely to benefit from screening, and (ii) post-LDCT, to differentiate benign versus malignant nodules. To identify informative proteins, the Risk Biomarker project measured 1161 proteins in a nested-case control study within 2 prospective cohorts (n = 252 lung cancer cases and 252 controls) and replicated associations for a subset of proteins in 4 cohorts (n = 479 cases and 479 controls). Eligible participants had a current or former history of smoking and cases were diagnosed up to 3 years following blood draw. The Nodule Malignancy project measured 1078 proteins among participants with a heavy smoking history within four LDCT screening studies (n = 425 cases diagnosed up to 5 years following blood draw, 430 benign-nodule controls, and 398 nodule-free controls). The INTEGRAL panel will enable absolute quantification of 21 proteins. We will evaluate its performance in the Risk Biomarker project using a case-cohort study including 14 cohorts (n = 1696 cases and 2926 subcohort representatives), and in the Nodule Malignancy project within five LDCT screening studies (n = 675 cases, 680 benign-nodule controls, and 648 nodule-free controls). Future progress to advance lung cancer early detection biomarkers will require carefully designed validation, translational, and comparative studies.
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- Feng, Xiaoshuang, et al.
(author)
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Lung cancer risk discrimination of prediagnostic proteomics measurements compared with existing prediction tools
- 2023
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In: Journal of the National Cancer Institute. - : Oxford University Press. - 0027-8874 .- 1460-2105. ; 115:9, s. 1050-1059
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Journal article (peer-reviewed)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.
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- Muller, David C., et al.
(author)
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Circulating high sensitivity C reactive protein concentrations and risk of lung cancer : nested case-control study within Lung Cancer Cohort Consortium
- 2019
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In: The BMJ. - : BMJ Publishing Group Ltd. - 1756-1833 .- 0959-8138. ; 364
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Journal article (peer-reviewed)abstract
- Objectives To conduct a comprehensive analysis of prospectively measured circulating high sensitivity C reactive protein (hsCRP) concentration and risk of lung cancer overall, by smoking status (never, former, and current smokers), and histological sub-type.Design Nested case-control study.Setting 20 population based cohort studies in Asia, Europe, Australia, and the United States.Participants 5299 patients with incident lung cancer, with individually incidence density matched controls.Exposure Circulating hsCRP concentrations in prediagnostic serum or plasma samples.Main outcome measure Incident lung cancer diagnosis.Results A positive association between circulating hsCRP concentration and the risk of lung cancer for current (odds ratio associated with a doubling in hsCRP concentration 1.09, 95% confidence interval 1.05 to 1.13) and former smokers (1.09, 1.04 to 1.14) was observed, but not for never smokers (P<0.01 for interaction). This association was strong and consistent across all histological subtypes, except for adenocarcinoma, which was not strongly associated with hsCRP concentration regardless of smoking status (odds ratio for adenocarcinoma overall 0.97, 95% confidence interval 0.94 to 1.01). The association between circulating hsCRP concentration and the risk of lung cancer was strongest in the first two years of follow-up for former and current smokers. Including hsCRP concentration in a risk model, in addition to smoking based variables, did not improve risk discrimination overall, but slightly improved discrimination for cancers diagnosed in the first two years of follow-up.Conclusions Former and current smokers with higher circulating hsCRP concentrations had a higher risk of lung cancer overall. Circulating hsCRP concentration was not associated with the risk of lung adenocarcinoma. Circulating hsCRP concentration could be a prediagnostic marker of lung cancer rather than a causal risk factor.
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- Zahed, Hana, et al.
(author)
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Epidemiology of 40 blood biomarkers of one-carbon metabolism, vitamin status, inflammation, and renal and endothelial function among cancer-free older adults
- 2021
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In: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 11:1
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Journal article (peer-reviewed)abstract
- Imbalances of blood biomarkers are associated with disease, and biomarkers may also vary non-pathologically across population groups. We described variation in concentrations of biomarkers of one-carbon metabolism, vitamin status, inflammation including tryptophan metabolism, and endothelial and renal function among cancer-free older adults. We analyzed 5167 cancer-free controls aged 40–80 years from 20 cohorts in the Lung Cancer Cohort Consortium (LC3). Centralized biochemical analyses of 40 biomarkers in plasma or serum were performed. We fit multivariable linear mixed effects models to quantify variation in standardized biomarker log-concentrations across four factors: age, sex, smoking status, and body mass index (BMI). Differences in most biomarkers across most factors were small, with 93% (186/200) of analyses showing an estimated difference lower than 0.25 standard-deviations, although most were statistically significant due to large sample size. The largest difference was for creatinine by sex, which was − 0.91 standard-deviations lower in women than men (95%CI − 0.98; − 0.84). The largest difference by age was for total cysteine (0.40 standard-deviation increase per 10-year increase, 95%CI 0.36; 0.43), and by BMI was for C-reactive protein (0.38 standard-deviation increase per 5-kg/m2 increase, 95%CI 0.34; 0.41). For 31 of 40 markers, the mean difference between current and never smokers was larger than between former and never smokers. A statistically significant (p < 0.05) association with time since smoking cessation was observed for 8 markers, including C-reactive protein, kynurenine, choline, and total homocysteine. We conclude that most blood biomarkers show small variations across demographic characteristics. Patterns by smoking status point to normalization of multiple physiological processes after smoking cessation.
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