Misclassification of smoking habits: An updated review of the literature

Urinary Oxidative Damage Markers and Their Association with Obesity-Related Metabolic Risk Factors

Oxidative damage and inflammation are possible mechanisms linking obesity to diabetes and related complications. This study investigates the levels of oxidative damage markers in the urine of community free-living subjects with increased prevalence of obesity. Methods: Participants were assessed regarding clinical, anthropometric, and physical activity data at baseline and at 6 months. Blood and urine samples were taken for the measurements of oxidative markers in urine ((glutathione (GSH), thiobarbituric acid reactive substances (TBARS), pteridine, 8-isoprostane and 8-hydroxy-2′-deoxyguanosine (8-OH-dG)), metabolic and inflammatory markers, and related biochemical variables in the blood. Univariate and multiple regression analyses were used to assess the association between oxidative markers and other clinical prognostic indicators. Results: Overall, 168 participants with a complete 6-month follow-up with a mean (±SD) age of 41 ± 12 (119 (71%) females) were included in the study. In multiple regression analysis, log-transformed urinary pteridine levels were significantly correlated with log-transformed urinary GSH, 8-isoprostane, and TBARS after adjusting for urinary creatinine at both baseline and follow-up. Significant correlations were also found between oxidative damage markers and cardiovascular disease risk factors, including systolic blood pressure, HbA1c, plasma glucose, us-C-reactive proteins, total cholesterol, and HDL. Higher TBARS levels were found in males and diabetic subjects, with lower GSH in diabetic hypertensive and obese subjects, but the latter result did not reach statistical significance. We found nonsignificantly higher TBARS, 8-isoprostane, and pteridine levels in smokers compared to those in nonsmokers. All measured urinary oxidative damage markers levels were higher in obese subjects compared with normal-weight subjects, but results did not reach statistical significance. Conclusion: we found significant associations between urinary oxidative damage and metabolic risk factors, and higher levels of urinary oxidative damage markers in diabetic, hypertensive, smoker, and male subjects.

Associations of coffee and tea consumption with lung cancer risk

Associations of coffee and tea consumption with lung cancer risk have been inconsistent, and most lung cancer cases investigated were smokers. Included in this study were over 1.1 million participants from 17 prospective cohorts. Cox regression analyses were conducted to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Potential effect modifications by sex, smoking, race, cancer subtype and coffee type were assessed. After a median 8.6 years of follow-up, 20 280 incident lung cancer cases were identified. Compared with noncoffee and nontea consumption, HRs (95% CIs) associated with exclusive coffee drinkers (≥2 cups/d) among current, former and never smokers were 1.30 (1.15-1.47), 1.49 (1.27-1.74) and 1.35 (1.15-1.58), respectively. Corresponding HRs for exclusive tea drinkers (≥2 cups/d) were 1.16 (1.02-1.32), 1.10 (0.92-1.32) and 1.37 (1.17-1.61). In general, the coffee and tea associations did not differ significantly by sex, race or histologic subtype. Our findings suggest that higher consumption of coffee or tea is associated with increased lung cancer risk. However, these findings should not be assumed to be causal because of the likelihood of residual confounding by smoking, including passive smoking, and change of coffee and tea consumption after study enrolment.

The shape of low-concentration dose-response functions for benzene: implications for human health risk assessment

Are dose-response relationships for benzene and health effects such as myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML) supra-linear, with disproportionately high risks at low concentrations, e.g. below 1 ppm? To investigate this hypothesis, we apply recent mode of action (MoA) and mechanistic information and modern data science techniques to quantify air benzene-urinary metabolite relationships in a previously studied data set for Tianjin, China factory workers. We find that physiologically based pharmacokinetics (PBPK) models and data for Tianjin workers show approximately linear production of benzene metabolites for air benzene (AB) concentrations below about 15 ppm, with modest sublinearity at low concentrations (e.g. below 5 ppm). Analysis of the Tianjin worker data using partial dependence plots reveals that production of metabolites increases disproportionately with increases in air benzene (AB) concentrations above 10 ppm, exhibiting steep sublinearity (J shape) before becoming saturated. As a consequence, estimated cumulative exposure is not an adequate basis for predicting risk. Risk assessments must consider the variability of exposure concentrations around estimated exposure concentrations to avoid over-estimating risks at low concentrations. The same average concentration for a specified duration is disproportionately risky if it has higher variance. Conversely, if chronic inflammation via activation of inflammasomes is a critical event for induction of MDS and other health effects, then sufficiently low concentrations of benzene are predicted not to cause increased risks of inflammasome-mediated diseases, no matter how long the duration of exposure. Thus, we find no evidence that the dose-response relationship is supra-linear at low doses; instead sublinear or zero excess risk at low concentrations is more consistent with the data. A combination of physiologically based pharmacokinetic (PBPK) modeling, Bayesian network (BN) analysis and inference, and partial dependence plots appears a promising and practical approach for applying current data science methods to advance benzene risk assessment.

Commonly Applied Selection Criteria for Lung Cancer Screening May Have Strongly Varying Diagnostic Performance in Different Countries

Simple Summary

Smoking causes the majority of lung cancers. Smoking history is thus used to select individuals among whom screening for lung cancer could be the most beneficial. The aim of our study was to estimate sensitivity and specificity of pre-selection by heavy smoking in individual European countries. Due to differences in smoking histories across the countries and sexes within the countries, the sensitivities were found to be between 33 and 80% for men and between 9 and 79% for women. Corresponding specificities of heavy smoking varied between 48 and 90% (men) and 70 and 99% (women). Our results may inform the design of lung cancer screening programs in European countries and serve as benchmarks for novel alternative or complementary tests for selecting people at high risk for computed tomography-based lung cancer screening.

Abstract

Lung cancer (LC) screening often focuses heavy smokers as a target for screening group. Heavy smoking can thus be regarded as an LC pre-screening test with sensitivities and specificities being different in various populations due to the differences in smoking histories. We derive here expected sensitivities and specificities of various criteria to preselect individuals for LC screening in 27 European countries with diverse smoking prevalences. Sensitivities of various heavy-smoking-based pre-screening criteria were estimated by combining sex-specific proportions of people meeting these criteria in the target population for screening with associations of heavy smoking with LC risk. Expected specificities were approximated by the proportion of individuals not meeting the heavy smoking definition. Estimated sensitivities and specificities varied widely across countries, with sensitivities being generally higher among men (range: 33–80%) than among women (range: 9–79%), and specificities being generally lower among men (range: 48–90%) than among women (range: 70–99%). Major variation in sensitivities and specificities was also seen across different pre-selection criteria for LC screening within individual countries. Our results may inform the design of LC screening programs in European countries and serve as benchmarks for novel alternative or complementary tests for selecting people at high risk for CT-based LC screening.