Pronk A.,U.S. National Cancer Institute |
Pronk A.,TNO |
Stewart P.A.,U.S. National Cancer Institute |
Stewart P.A.,Stewart Exposure Assessments LLC |
And 9 more authors.
Occupational and Environmental Medicine | Year: 2012
Objectives: Professional judgment is necessary to assess occupational exposure in population-based case-control studies; however, the assessments lack transparency and are time-consuming to perform. To improve transparency and efficiency, we systematically applied decision rules to questionnaire responses to assess diesel exhaust exposure in the population-based case-control New England Bladder Cancer Study. Methods: 2631 participants reported 14 983 jobs; 2749 jobs were administered questionnaires ('modules') with diesel-relevant questions. We applied decision rules to assign exposure metrics based either on the occupational history (OH) responses (OH estimates) or on the module responses (module estimates); we then combined the separate OH and module estimates (OH/module estimates). Each job was also reviewed individually to assign exposure (one-by-one review estimates). We evaluated the agreement between the OH, OH/module and one-by-one review estimates. Results: The proportion of exposed jobs was 20-25% for all jobs, depending on approach, and 54-60% for jobs with diesel-relevant modules. The OH/module and one-by- one review estimates had moderately high agreement for all jobs (κ w=0.68-0.81) and for jobs with diesel-relevant modules (κw=0.62-0.78) for the probability, intensity and frequency metrics. For exposed subjects, the Spearman correlation statistic was 0.72 between the cumulative OH/module and one-by-one review estimates. Conclusions: The agreement seen here may represent an upper level of agreement because the algorithm and one-by-one review estimates were not fully independent. This study shows that applying decision-based rules can reproduce a one-by-one review, increase transparency and efficiency, and provide a mechanism to replicate exposure decisions in other studies. Source
Lenz P.,U.S. National Cancer Institute |
Pfeiffer R.,U.S. National Cancer Institute |
Baris D.,U.S. National Cancer Institute |
Takikita M.,U.S. National Cancer Institute |
And 8 more authors.
Cancer Epidemiology Biomarkers and Prevention | Year: 2012
Background: Cell-cycle proteins are important predictive markers in urothelial carcinoma but may also exhibit exposure-specific heterogeneity. Methods: Tumor tissue from 491 bladder cancer cases enrolled in the Maine and Vermont component of the New England Bladder Cancer Study was assembled as tissue microarrays and examined for aberrant expression of p53, p63, p16, cyclin D1, Rb, and Ki-67. The association between expression and histopathology, demographics, and cigarette smoking was examined using c2 tests, multivariable Poisson, and multinomial regression models. Results: We found that overexpression of p53 and Ki-67 was associated with high-stage/grade tumors [relative risk (RR), 1.26; Ptrend = 0.003; and RR, 3.21; P trend < 0.0001, respectively], whereas expression of p63 and p16 was decreased in high-stage/grade tumors (RR, 0.52; Ptrend < 0.0001; and RR, 0.88; Ptrend = 0.04, respectively). No significant aberrations of cell-cycle proteins were identified using various smoking variables and multiple statistical models. Conclusion: The results of this population-based study of histologically confirmed urothelial carcinomas show significant aberration of cell-cycle proteins p53, p63, p16, and Ki-67, but not Rb or cyclin D1. p53 showed the most significant heterogeneity with respect to tumor stage and grade, especially when stratified for different staining intensities using novel digital image analysis techniques. Our findings do not support that smoking modifies expression of cell-cycle proteins. Impact: Our study shows significant heterogeneity in the expression of key cell-cycle proteins that are associated with disease progression in bladder cancer. Further studies may lead to the identification of biomarkers and their multiplexed interactions as useful prognostic and therapeutic targets. ©2012 AACR. Source
Friesen M.C.,U.S. National Cancer Institute |
Pronk A.,U.S. National Cancer Institute |
Pronk A.,TNO |
Wheeler D.C.,U.S. National Cancer Institute |
And 11 more authors.
Annals of Occupational Hygiene | Year: 2013
Objectives: Algorithm-based exposure assessments based on patterns in questionnaire responses and professional judgment can readily apply transparent exposure decision rules to thousands of jobs quickly. However, we need to better understand how algorithms compare to a one-by-one job review by an exposure assessor. We compared algorithm-based estimates of diesel exhaust exposure to those of three independent raters within the New England Bladder Cancer Study, a population-based case-control study, and identified conditions under which disparities occurred in the assessments of the algorithm and the raters.Methods: Occupational diesel exhaust exposure was assessed previously using an algorithm and a single rater for all 14 983 jobs reported by 2631 study participants during personal interviews conducted from 2001 to 2004. Two additional raters independently assessed a random subset of 324 jobs that were selected based on strata defined by the cross-tabulations of the algorithm and the first rater's probability assessments for each job, oversampling their disagreements. The algorithm and each rater assessed the probability, intensity and frequency of occupational diesel exhaust exposure, as well as a confidence rating for each metric. Agreement among the raters, their aggregate rating (average of the three raters' ratings) and the algorithm were evaluated using proportion of agreement, kappa and weighted kappa (κw). Agreement analyses on the subset used inverse probability weighting to extrapolate the subset to estimate agreement for all jobs. Classification and Regression Tree (CART) models were used to identify patterns in questionnaire responses that predicted disparities in exposure status (i.e., unexposed versus exposed) between the first rater and the algorithm-based estimates.Results: For the probability, intensity and frequency exposure metrics, moderate to moderately high agreement was observed among raters (κw = 0.50-0.76) and between the algorithm and the individual raters (κw = 0.58-0.81). For these metrics, the algorithm estimates had consistently higher agreement with the aggregate rating (κw = 0.82) than with the individual raters. For all metrics, the agreement between the algorithm and the aggregate ratings was highest for the unexposed category (90-93%) and was poor to moderate for the exposed categories (9-64%). Lower agreement was observed for jobs with a start year <1965 versus ≥1965. For the confidence metrics, the agreement was poor to moderate among raters (κw = 0.17-0.45) and between the algorithm and the individual raters (κw = 0.24-0.61). CART models identified patterns in the questionnaire responses that predicted a fair-to-moderate (33-89%) proportion of the disagreements between the raters' and the algorithm estimates.Discussion: The agreement between any two raters was similar to the agreement between an algorithm-based approach and individual raters, providing additional support for using the more efficient and transparent algorithm-based approach. CART models identified some patterns in disagreements between the first rater and the algorithm. Given the absence of a gold standard for estimating exposure, these patterns can be reviewed by a team of exposure assessors to determine whether the algorithm should be revised for future studies. © 2012 The Author. Source
Koutros S.,U.S. National Cancer Institute |
Silverman D.T.,U.S. National Cancer Institute |
Baris D.,U.S. National Cancer Institute |
Zahm S.H.,U.S. National Cancer Institute |
And 8 more authors.
International Journal of Cancer | Year: 2011
Aromatic amine components in hair dyes and polymorphisms in genes that encode enzymes responsible for hair dye metabolism may be related to bladder cancer risk. We evaluated the association between hair dye use and bladder cancer risk and effect modification by N-acetyltransferase-1 (NAT1), NAT2, glutathione S-transferase Mu-1 (GSTM1) and glutathione S-transferase theta-1 (GSTT1) genotypes in a population-based case-control study of 1193 incident cases and 1418 controls from Maine, Vermont and New Hampshire enrolled between 2001 and 2004. Individuals were interviewed in person using a computer-assisted personal interview to assess hair dye use and information on potential confounders and effect modifiers. No overall association between age at first use, year of first use, type of product, color, duration or number of applications of hair dyes and bladder cancer among women or men was apparent, but increased risks were observed in certain subgroups. Women who used permanent dyes and had a college degree, a marker of socioeconomic status, had an increased risk of bladder cancer [odds ratio (OR) = 3.3, 95% confidence interval (CI): 1.2-8.9]. Among these women, we found an increased risk of bladder cancer among exclusive users of permanent hair dyes who had NAT2 slow acetylation phenotype (OR = 7.3, 95% CI: 1.6-32.6) compared to never users of dye with NAT2 rapid/intermediate acetylation phenotype. Although we found no relation between hair dye use and bladder cancer risk in women overall, we detected evidence of associations and gene-environment interaction with permanent hair dye use; however, this was limited to educated women. These results need confirmation with larger numbers, requiring pooling data from multiple studies. Copyright © 2011 UICC. Source
Moore L.E.,U.S. National Institutes of Health |
Baris D.R.,U.S. National Institutes of Health |
Figueroa J.D.,U.S. National Institutes of Health |
Garcia-Closas M.,U.S. National Institutes of Health |
And 14 more authors.
Carcinogenesis | Year: 2011
Associations between bladder cancer risk and NAT2 and GSTM1 polymorphisms have emerged as some of the most consistent findings in the genetic epidemiology of common metabolic polymorphisms and cancer, but their interaction with tobacco use, intensity and duration remain unclear. In a New England population-based case-control study of urothelial carcinoma, we collected mouthwash samples from 1088 of 1171 cases (92.9%) and 1282 of 1418 controls (91.2%) for genotype analysis of GSTM1, GSTT1 and NAT2 polymorphisms. Odds ratios and 95% confidence intervals of bladder cancer among New England Bladder Cancer Study subjects with one or two inactive GSTM1 alleles (i.e. the 'null' genotype) were 1.26 (0.85-1.88) and 1.54 (1.05-2.25), respectively (P-trend = 0.008), compared with those with two active copies. GSTT1 inactive alleles were not associated with risk. NAT2 slow acetylation status was not associated with risk among never (1.04; 0.71-1.51), former (0.95; 0.75-1.20) or current smokers (1.33; 0.91-1.95); however, a relationship emerged when smoking intensity was evaluated. Among slow acetylators who ever smoked at least 40 cigarettes/day, risk was elevated among ever (1.82; 1.14-2.91, P-interaction = 0.07) and current heavy smokers (3.16; 1.22-8.19, P-interaction = 0.03) compared with rapid acetylators in each category; but was not observed at lower intensities. In contrast, the effect of GSTM1-null genotype was not greater among smokers, regardless of intensity. Meta-analysis of the NAT2 associations with bladder cancer showed a highly significant relationship. Findings from this large USA population-based study provided evidence that the NAT2 slow acetylation genotype interacts with tobacco smoking as a function of exposure intensity. Published by Oxford University Press 2010. Source