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Arsenic is a bladder carcinogen though less is known regarding the specific temporal relationship between exposure and bladder cancer diagnosis. In this study, we modeled time-varying mixtures of arsenic exposures at many historic temporal windows to evaluate their association with bladder cancer risk in the New England Bladder Cancer Study. We used arsenic exposure estimates up to 60 years prior to study entry and compared the goodness of fit of models using these mixtures to those using summary measures of arsenic exposures. We used the Bayesian index low rank kriging multiple membership model (LRK-MMM) to estimate the associations of these mixtures with bladder cancer and estimate cumulative spatial risk for bladder cancer using participants' residential histories. We found consistent evidence that modeling arsenic exposures as a time-varying mixture provided better fit to the data than using a single arsenic exposure summary measure. We estimated several positive though not significant associations of the time-varying arsenic mixtures with bladder cancer having odds ratios (ORs) of 1.03-1.14 and identified many significant and positive associations for an interaction among those who consumed water from a private dug well (ORs 1.28-1.60). Arsenic exposures 40-50 years before study entry received elevated importance weights in these mixtures. Additionally, we found two small areas of elevated cumulative spatial risk for bladder cancer in southern New Hampshire and in south central Maine. These results emphasize the importance of considering time-varying mixtures of exposures for diseases with long latencies such as bladder cancer.

Background: Bladder cancer has been linked to several occupations that involve the use of solvents, including those used in the dry-cleaning industry., Objectives: We evaluated exposure to solvents and risk of bladder cancer in 1182 incident cases and 1408 controls from a population-based study., Methods: Exposure to solvents was quantitatively assessed using a job-exposure matrix (CANJEM). Exposure to benzene, toluene and xylene often co-occur. Therefore, we created two additional sets of metrics for combined benzene, toluene and xylene (BTX) exposure: (1) CANJEM-based BTX metrics and (2) hybrid BTX metrics, using an approach that integrates the CANJEM-based BTX metrics together with lifetime occupational histories and exposure-oriented modules that captured within-job, respondent-specific details about tasks and chemicals. Adjusted odds ratios (ORs) and 95% confidence intervals (95% CI) were estimated using logistic regression., Results: Bladder cancer risks were increased among those ever exposed to benzene (OR = 1.63, 95% CI: 1.14-2.32), toluene (OR = 1.60, 95% CI: 1.06-2.43), and xylene (OR = 1.67, 95% CI: 1.13-2.48) individually. We further observed a statistically significant exposure-response relationship for cumulative BTX exposure, with a stronger association using the hybrid BTX metrics (OR Q1vsUnexposed  = 1.26, 95% CI: 0.83-1.90; OR Q2vsUnexposed  = 1.52, 95% CI: 1.00-2.31; OR Q3vsUnexposed  = 1.88, 95% CI: 1.24-2.85; and OR Q4vsUnexposed  = 2.23, 95% CI: 1.35-3.69) (p-trend=0.001) than using CANJEM-based metrics (p-trend=0.02)., Impact: There is limited evidence about the role of exposure to specific organic solvents, alone or in combination on the risk of developing bladder cancer. In this study, workers with increasing exposure to benzene, toluene, and xylene as a group (BTX) had a statistically significant exposure-response relationship with bladder cancer. Future evaluation of the carcinogenicity of BTX and other organic solvents, particularly concurrent exposure, on bladder cancer development is needed., (© 2024. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

The etiology of bladder cancer among never smokers without occupational or environmental exposure to established urothelial carcinogens remains unclear. Urinary mutagenicity is an integrative measure that reflects recent exposure to genotoxic agents. Here, we investigated its potential association with bladder cancer in rural northern New England. We analyzed 156 bladder cancer cases and 247 cancer-free controls from a large population-based case-control study conducted in Maine, New Hampshire, and Vermont. Overnight urine samples were deconjugated enzymatically and the extracted organics were assessed for mutagenicity using the plate-incorporation Ames assay with the Salmonella frameshift strain YG1041 + S9. Logistic regression was used to estimate the odds ratios (OR) and 95% confidence intervals (CI) of bladder cancer in relation to having mutagenic versus nonmutagenic urine, adjusted for age, sex, and state, and stratified by smoking status (never, former, and current). We found evidence for an association between having mutagenic urine and increased bladder cancer risk among never smokers (OR = 3.8, 95% CI: 1.3-11.2) but not among former or current smokers. Risk could not be estimated among current smokers because nearly all cases and controls had mutagenic urine. Urinary mutagenicity among never-smoking controls could not be explained by recent exposure to established occupational and environmental mutagenic bladder carcinogens evaluated in our study. Our findings suggest that among never smokers, urinary mutagenicity potentially reflects genotoxic exposure profiles relevant to bladder carcinogenesis. Future studies are needed to replicate our findings and identify compounds and their sources that influence bladder cancer risk., (© 2024 The Authors. Environmental and Molecular Mutagenesis published by Wiley Periodicals LLC on behalf of Environmental Mutagenesis and Genomics Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

FGFR3 and PIK3CA are among the most frequently mutated genes in bladder tumors. We hypothesized that recurrent mutations in these genes might be caused by common carcinogenic exposures such as smoking and other factors. We analyzed 2,816 bladder tumors with available data on FGFR3 and/or PIK3CA mutations, focusing on the most recurrent mutations detected in ≥10% of tumors. Compared to tumors with other FGFR3/PIK3CA mutations, FGFR3-Y375C was more common in tumors from smokers than never-smokers (P = 0.009), while several APOBEC-type driver mutations were enriched in never-smokers: FGFR3-S249C (P = 0.013) and PIK3CA-E542K/PIK3CA-E545K (P = 0.009). To explore possible causes of these APOBEC-type mutations, we analyzed RNA sequencing (RNA-seq) data from 798 bladder tumors and detected several viruses, with BK polyomavirus (BKPyV) being the most common. We then performed IHC staining for polyomavirus (PyV) Large T-antigen (LTAg) in an independent set of 211 bladder tumors. Overall, by RNA-seq or IHC-LTAg, we detected PyV in 26 out of 1,010 bladder tumors with significantly higher detection (P = 4.4 × 10-5), 25 of 554 (4.5%) in non-muscle-invasive bladder cancers (NMIBC) versus 1 of 456 (0.2%) of muscle-invasive bladder cancers (MIBC). In the NMIBC subset, the FGFR3/PIK3CA APOBEC-type driver mutations were detected in 94.7% (18/19) of PyV-positive versus 68.3% (259/379) of PyV-negative tumors (P = 0.011). BKPyV tumor positivity in the NMIBC subset with FGFR3- or PIK3CA-mutated tumors was also associated with a higher risk of progression to MIBC (P = 0.019). In conclusion, our results support smoking and BKPyV infection as risk factors contributing to bladder tumorigenesis in the general patient population through distinct molecular mechanisms., Prevention Relevance: Tobacco smoking likely causes one of the most common mutations in bladder tumors (FGFR3-Y375C), while viral infections might contribute to three others (FGFR3-S249C, PIK3CA-E542K, and PIK3CA-E545K). Understanding the causes of these mutations may lead to new prevention and treatment strategies, such as viral screening and vaccination., (©2023 American Association for Cancer Research.)

Background: Acidic urine pH is associated with rapid hydrolysis of N-glucuronide conjugates of aromatic amines into metabolites that may undergo metabolism in the bladder lumen to form mutagenic DNA adducts. We previously reported that consistently acidic urine was associated with increased bladder cancer risk in a hospital-based case-control study in Spain. Here, we conducted a separate study in northern New England to replicate these findings., Methods: In a large, population-based case-control study conducted in Maine, New Hampshire, and Vermont, we examined bladder cancer risk in relation to consistent urine pH, measured twice daily by participants over 4 consecutive days using dipsticks. In parallel, we collected spot urine samples and conducted laboratory measurements of urinary acidity using a pH meter. Unconditional logistic regression was used to estimate associations, adjusting for age, gender, race, Hispanic status, and state. Analyses were further stratified by smoking status., Results: Among 616 urothelial carcinoma cases and 897 controls, urine pH consistently ≤ 6.0 was associated with increased bladder cancer risk (OR = 1.27; 95% confidence interval, 1.02-1.57), with the effect limited to ever-smokers. These findings were supported by analyses of a spot urine, with statistically significant exposure-response relationships for bladder cancer risk overall (Ptrend = 5.1×10-3) and among ever-smokers (Ptrend = 1.2×10-3)., Conclusions: Consistent with a previous study in Spain, our findings suggest that acidic urine pH is associated with increased bladder cancer risk., Impact: Our findings align with experimental results showing that acidic urine pH, which is partly modifiable by lifestyle factors, is linked to hydrolysis of acid-labile conjugates of carcinogenic aromatic amines., (©2023 American Association for Cancer Research.)

Background: Genomic regions identified by genome-wide association studies (GWAS) for bladder cancer risk provide new insights into etiology., Objective: To identify new susceptibility variants for bladder cancer in a meta-analysis of new and existing genome-wide genotype data., Design, Setting, and Participants: Data from 32 studies that includes 13,790 bladder cancer cases and 343,502 controls of European ancestry were used for meta-analysis., Outcome Measurements and Statistical Analyses: Log-additive associations of genetic variants were assessed using logistic regression models. A fixed-effects model was used for meta-analysis of the results. Stratified analyses were conducted to evaluate effect modification by sex and smoking status. A polygenic risk score (PRS) was generated on the basis of known and novel susceptibility variants and tested for interaction with smoking., Results and Limitations: Multiple novel bladder cancer susceptibility loci (6p.22.3, 7q36.3, 8q21.13, 9p21.3, 10q22.1, 19q13.33) as well as improved signals in three known regions (4p16.3, 5p15.33, 11p15.5) were identified, bringing the number of independent markers at genome-wide significance (p < 5 × 10 -8 ) to 24. The 4p16.3 (FGFR3/TACC3) locus was associated with a stronger risk for women than for men (p-interaction = 0.002). Bladder cancer risk was increased by interactions between smoking status and genetic variants at 8p22 (NAT2; multiplicative p value for interaction [p M-I ] = 0.004), 8q21.13 (PAG1; p M-I  = 0.01), and 9p21.3 (LOC107987026/MTAP/CDKN2A; p M-I  = 0.02). The PRS based on the 24 independent GWAS markers (odds ratio per standard deviation increase 1.49, 95% confidence interval 1.44-1.53), which also showed comparable results in two prospective cohorts (UK Biobank, PLCO trial), revealed an approximately fourfold difference in the lifetime risk of bladder cancer according to the PRS (e.g., 1st vs 10th decile) for both smokers and nonsmokers., Conclusions: We report novel loci associated with risk of bladder cancer that provide clues to its biological underpinnings. Using 24 independent markers, we constructed a PRS to stratify lifetime risk. The PRS combined with smoking history, and other established risk factors, has the potential to inform future screening efforts for bladder cancer., Patient Summary: We identified new genetic markers that provide biological insights into the genetic causes of bladder cancer. These genetic risk factors combined with lifestyle risk factors, such as smoking, may inform future preventive and screening strategies for bladder cancer., (Published by Elsevier B.V.)

Background: Diesel exhaust is a complex mixture, including polycyclic aromatic hydrocarbons (PAH) and nitrated PAHs (nitro-PAH), many of which are potent mutagens and possible bladder carcinogens. To explore the association between diesel exposure and bladder carcinogenesis, we examined the relationship between exposure and somatic mutations and mutational signatures in bladder tumors., Methods: Targeted sequencing was conducted in bladder tumors from the New England Bladder Cancer Study. Using data on 797 cases and 1,418 controls, two-stage polytomous logistic regression was used to evaluate etiologic heterogeneity between bladder cancer subtypes and quantitative, lifetime estimates of respirable elemental carbon (REC), a surrogate for diesel exposure. Poisson regression was used to evaluate associations between REC and mutational signatures., Results: We observed significant heterogeneity in the diesel-bladder cancer risk relationship, with a strong positive association among cases with high-grade, nonmuscle invasive TP53-mutated tumors compared with controls [ORTop Tertile vs.Unexposed, 4.8; 95% confidence interval (CI), 2.2-10.5; Ptrend < 0.001; Pheterogeneity = 0.002]. In muscle-invasive tumors, we observed a positive association between diesel exposure and the nitro-PAH signatures of 1,6-dintropyrene (RR, 1.93; 95% CI, 1.28-2.92) and 3-nitrobenzoic acid (RR, 1.97; 95% CI, 1.33-2.92)., Conclusions: The relationship between diesel exhaust and bladder cancer was heterogeneous based on the presence of TP53 mutations in tumors, further supporting the link between PAH exposure and TP53 mutations in carcinogenesis. Future studies that can identify nitro-PAH signatures in exposed tumors are warranted to add human data supporting the link between diesel and bladder cancer., Impact: This study provides additional insight into the etiology and possible mechanisms related to diesel exhaust-induced bladder cancer., (©2023 American Association for Cancer Research.)

Purpose: We examined the interaction between common genetic bladder cancer variants, diet quality, and bladder cancer risk in a population-based case-control study conducted in New England., Methods: At the time of enrollment, 806 bladder cancer cases and 974 controls provided a DNA sample and completed a diet history questionnaire. Diet quality was assessed using the 2010 Alternate Healthy Eating Index (AHEI-2010) score. Single nucleotide polymorphisms (SNPs) reported in genome-wide association studies to be associated with bladder cancer risk were combined into a polygenic risk score and also examined individually for interaction with the AHEI-2010. Adjusted odds ratios (OR) and 95% confidence intervals (CI) were calculated using logistic regression., Results: A 1-standard deviation increase in polygenic risk score was associated with higher bladder cancer risk (OR, 1.34; 95% CI 1.21-1.49). Adherence to the AHEI-2010 was not associated with bladder cancer risk (OR, 0.99; 95% CI 0.98-1.00) and the polygenic risk score did not appear to modify the association between the AHEI-2010 and bladder cancer risk. In single-SNP analyses, rs8102137 (bladder cancer risk allele, C) modified the association between the AHEI-2010 total score and bladder cancer risk, with the strongest evidence for the AHEI-2010 long chain fat guideline (OR for TT, 0.92; 95% CI 0.87-0.98; OR for CT, 1.02; 95% CI 0.96-1.08; OR for CC, 1.03; 95% CI 0.93-1.14; p for interaction, 0.02)., Conclusions: In conclusion, rs8102137 near the cyclin E1 gene ( CCNE1 ) may be involved in gene-diet interactions for bladder cancer risk., (© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.)

Many health outcomes result from accumulated exposures to one or more environmental factors. Accordingly, spatial risk studies have begun to consider multiple residential locations of participants, acknowledging that participants move and thus are exposed to environmental factors in several places. However, novel methods are needed to estimate cumulative spatial risk for disease while accounting for other risk factors. To this end, we propose a Bayesian model (LRK-MMM) that embeds a multiple membership model (MMM) into a low-rank kriging (LRK) model in order to estimate cumulative spatial risk at the point level while allowing for multiple residential locations per subject. The LRK approach offers a more computationally efficient means to analyze spatial risk in case-control study data at the point level compared with a Bayesian generalized additive model, and as increased precision in spatial risk estimates by analyzing point locations instead of administrative areas. Through a simulation study, we demonstrate the efficacy of the model and its improvement upon an existing multiple membership model that uses area-level spatial random effects to estimate risk. The results show that our proposed method provides greater spatial sensitivity (improvements ranging from 0.12 to 0.54) and power (improvements ranging from 0.02 to 0.94) to detect regions of elevated risk for disease across a range of exposure scenarios. Finally, we apply our model to case-control data from the New England bladder cancer study to estimate cumulative spatial risk while adjusting for many covariates., (© 2022 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.)

Background: By-products are formed when disinfectants react with organic matter in source water. The most common class of disinfection by-products, trihalomethanes (THMs), have been linked to bladder cancer. Several studies have shown exposure-response associations with THMs in drinking water and bladder cancer risk. Few epidemiologic studies have evaluated gene-environment interactions for total THMs (TTHMs) with known bladder cancer susceptibility variants., Objectives: In this study, we investigated the combined effect on bladder cancer risk contributed by TTHMs, bladder cancer susceptibility variants identified through genome-wide association studies, and variants in several candidate genes., Methods: We analyzed data from two large case-control studies-the New England Bladder Cancer Study ( n / n = 989 cases/1,162 controls), a population-based study, and the Spanish Bladder Cancer Study ( n / n = 706 cases/772 controls), a hospital-based study. Because of differences in exposure distributions and metrics, we estimated effects of THMs and genetic variants within each study separately using adjusted logistic regression models to calculate odds ratios (ORs) and 95% confidence intervals (CI) with and without interaction terms, and then combined the results using meta-analysis., Results: Of the 16 loci showing strong evidence of association with bladder cancer, rs907611 at 11p15.5 [leukocyte-specific protein 1 ( LSP1 region)] showed the strongest associations in the highest exposure category in each study, with evidence of interaction in both studies and in meta-analysis. In the highest exposure category, we observed OR = 1.66 (95% CI: 1.17, 2.34, p -trend = 0.005 ) for those with the rs907611-GG genotype and p -interaction = 0.02 . No other genetic variants tested showed consistent evidence of interaction., Discussion: We found novel suggestive evidence for a multiplicative interaction between a putative bladder carcinogen, TTHMs, and genotypes of rs907611. Given the ubiquitous exposure to THMs, further work is needed to replicate and extend this finding and to understand potential molecular mechanisms. https://doi.org/10.1289/EHP9895.

Purpose: Previous studies have shown an approximately two-fold elevation in the relative risk of urinary bladder cancer (UBC) among people with a family history that could not be entirely explained by shared environmental exposures, thus suggesting a genetic component in its predisposition. Multiple genome-wide association studies and recent gene panel sequencing studies identified several genetic loci that are associated with UBC risk; however, the list of UBC-associated variants and genes is incomplete., Materials and Methods: We exome sequenced eight patients from three multiplex UBC pedigrees and a group of 77 unrelated familial UBC cases matched to 241 cancer-free controls. In addition, we examined pathogenic germline variation in 444 candidate genes in 392 The Cancer Genome Atlas UBC cases., Results: In the pedigrees, segregating variants were family-specific although the identified genes clustered in common pathways, most notably DNA repair ( MLH1 and MSH2 ) and cellular metabolism ( IDH1 and ME1 ). In the familial UBC group, the proportion of pathogenic and likely pathogenic variants was significantly higher in cases compared with controls ( P = .003). Pathogenic and likely pathogenic variant load was also significantly increased in genes involved in cilia biogenesis ( P = .001). In addition, a pathogenic variant in CHEK2 (NM&#95;007194.4:c.1100del; p.T367Mfs*15) was over-represented in cases (variant frequency = 2.6%; 95% CI, 0.71 to 6.52) compared with controls (variant frequency = 0.21%; 95% CI, 0.01 to 1.15), but was not statistically significant., Conclusion: These results point to a complex polygenic predisposition to UBC. Despite heterogeneity, the genes cluster in several biologically relevant pathways and processes, for example, DNA repair, cilia biogenesis, and cellular metabolism. Larger studies are required to determine the importance of CHEK2 in UBC etiology., Competing Interests: Talia Wegman-Ostrosky Travel, Accommodations, Expenses: Pfizer Bin Zhu Employment: GeneDx BioReference Douglas R. Stewart Employment: Genome Medical No other potential conflicts of interest were reported. Talia Wegman-Ostrosky Travel, Accommodations, Expenses: Pfizer Bin Zhu Employment: GeneDx BioReference Douglas R. Stewart Employment: Genome Medical No other potential conflicts of interest were reported., (© 2021 by American Society of Clinical Oncology.)

Background: N-nitroso compounds are hypothesized human bladder carcinogens. We investigated ingestion of N-nitroso compound precursors nitrate and nitrite from drinking water and diet and bladder cancer in the New England Bladder Cancer Study., Methods: Using historical nitrate measurements for public water supplies and measured and modeled values for private wells, as well as self-reported water intake, we estimated average nitrate concentrations (mg/L NO3-N) and average daily nitrate intake (mg/d) from 1970 to diagnosis/reference date (987 cases and 1,180 controls). We estimated overall and source-specific dietary nitrate and nitrite intakes using a food frequency questionnaire (1,037 cases and 1,225 controls). We used unconditional logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI). We evaluated interactions with factors that may affect N-nitroso compound formation (i.e., red meat, vitamin C, smoking), and with water intake., Results: Average drinking water nitrate concentration above the 95th percentile (>2.07 mg/L) compared with the lowest quartile (≤0.21 mg/L) was associated with bladder cancer (OR = 1.5, 95% CI = 0.97, 2.3; P trend = 0.01); the association was similar for average daily drinking water nitrate intake. We observed positive associations for dietary nitrate and nitrite intakes from processed meat (highest versus lowest quintile OR for nitrate = 1.4, 95% CI = 1.0, 2.0; P trend = 0.04; OR for nitrite = 1.5, 95% CI = 1.0, 2.1; P trend = 0.04, respectively), but not other dietary sources. We observed positive interactions between drinking water nitrate and red meat (P-interaction 0.05) and processed red meat (0.07)., Conclusions: Our results suggest the importance of both drinking water and dietary nitrate sources as risk factors for bladder cancer.

Objectives: The validity of surrogate measures of retrospective occupational exposure in population-based epidemiological studies has rarely been evaluated. Using toenail samples as bioindicators of exposure, we assessed whether work tasks and expert assessments of occupational metal exposure obtained from personal interviews were associated with lead and manganese concentrations., Methods: We selected 609 controls from a case-control study of bladder cancer in New England who had held a job for ≥1 year 8-24 months prior to toenail collection. We evaluated associations between toenail metal concentrations and five tasks extracted from occupational questionnaires (grinding, painting, soldering, welding, working near engines) using linear regression models. For 139 subjects, we also evaluated associations between the toenail concentrations and exposure estimates from three experts., Results: We observed a 1.9-fold increase (95% CI 1.4 to 2.5) in toenail lead concentrations with painting and 1.4-fold increase (95% CI 1.1 to 1.7) in manganese concentrations with working around engines and handling fuel. We observed significant trends with increasing frequency of both activities. For lead, significant trends were observed with the ratings from all three experts. Their average ratings showed the strongest association, with subjects rated as possibly or probably exposed to lead having concentrations that were 2.0 and 2.5 times higher, respectively, than in unexposed subjects (p trend <0.001). Expert estimates were only weakly associated with manganese toenail concentrations., Conclusions: Our findings support the ability of experts to identify broad contrasts in previous occupational exposure to lead. The stronger associations with task frequency and expert assessments support using refined exposure characterisation whenever possible., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Little is known whether genetic variants identified in genome-wide association studies interact to increase bladder cancer risk. Recently, we identified two- and three-variant combinations associated with a particular increase of bladder cancer risk in a urinary bladder cancer case-control series (Leibniz Research Centre for Working Environment and Human Factors at TU Dortmund (IfADo), 1501 cases, 1565 controls). In an independent case-control series (Nijmegen Bladder Cancer Study, NBCS, 1468 cases, 1720 controls) we confirmed these two- and three-variant combinations. Pooled analysis of the two studies as discovery group (IfADo-NBCS) resulted in sufficient statistical power to test up to four-variant combinations by a logistic regression approach. The New England and Spanish Bladder Cancer Studies (2080 cases and 2167 controls) were used as a replication series. Twelve previously identified risk variants were considered. The strongest four-variant combination was obtained in never smokers. The combination of rs1014971[AA] near apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3A (APOBEC3A) and chromobox homolog 6 (CBX6), solute carrier family 1s4 (urea transporter), member 1 (Kidd blood group) (SLC14A1) exon single nucleotide polymorphism (SNP) rs1058396[AG, GG], UDP glucuronosyltransferase 1 family, polypeptide A complex locus (UGT1A) intron SNP rs11892031[AA] and rs8102137[CC, CT] near cyclin E1 (CCNE1) resulted in an unadjusted odds ratio (OR) of 2.59 (95% CI = 1.93-3.47; P = 1.87 × 10-10), while the individual variant ORs ranged only between 1.11 and 1.30. The combination replicated in the New England and Spanish Bladder Cancer Studies (ORunadjusted = 1.60, 95% CI = 1.10-2.33; P = 0.013). The four-variant combination is relatively frequent, with 25% in never smoking cases and 11% in never smoking controls (total study group: 19% cases, 14% controls). In conclusion, we show that four high-risk variants can statistically interact to confer increased bladder cancer risk particularly in never smokers., (© The Author 2017. Published by Oxford University Press.)

Background: Mapping job titles to standardised occupation classification (SOC) codes is an important step in identifying occupational risk factors in epidemiological studies. Because manual coding is time-consuming and has moderate reliability, we developed an algorithm called SOCcer (Standardized Occupation Coding for Computer-assisted Epidemiologic Research) to assign SOC-2010 codes based on free-text job description components., Methods: Job title and task-based classifiers were developed by comparing job descriptions to multiple sources linking job and task descriptions to SOC codes. An industry-based classifier was developed based on the SOC prevalence within an industry. These classifiers were used in a logistic model trained using 14 983 jobs with expert-assigned SOC codes to obtain empirical weights for an algorithm that scored each SOC/job description. We assigned the highest scoring SOC code to each job. SOCcer was validated in 2 occupational data sources by comparing SOC codes obtained from SOCcer to expert assigned SOC codes and lead exposure estimates obtained by linking SOC codes to a job-exposure matrix., Results: For 11 991 case-control study jobs, SOCcer-assigned codes agreed with 44.5% and 76.3% of manually assigned codes at the 6-digit and 2-digit level, respectively. Agreement increased with the score, providing a mechanism to identify assignments needing review. Good agreement was observed between lead estimates based on SOCcer and manual SOC assignments (κ 0.6-0.8). Poorer performance was observed for inspection job descriptions, which included abbreviations and worksite-specific terminology., Conclusions: Although some manual coding will remain necessary, using SOCcer may improve the efficiency of incorporating occupation into large-scale epidemiological studies., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/)

Background: Bladder cancer mortality rates have been elevated in northern New England for at least five decades. Incidence rates in Maine, New Hampshire, and Vermont are about 20% higher than the United States overall. We explored reasons for this excess, focusing on arsenic in drinking water from private wells, which are particularly prevalent in the region., Methods: In a population-based case-control study in these three states, 1213 bladder cancer case patients and 1418 control subjects provided information on suspected risk factors. Log transformed arsenic concentrations were estimated by linear regression based on measurements in water samples from current and past homes. All statistical tests were two-sided., Results: Bladder cancer risk increased with increasing water intake (Ptrend = .003). This trend was statistically significant among participants with a history of private well use (Ptrend = .01). Among private well users, this trend was apparent if well water was derived exclusively from shallow dug wells (which are vulnerable to contamination from manmade sources, Ptrend = .002) but not if well water was supplied only by deeper drilled wells (Ptrend = .48). If dug wells were used pre-1960, when arsenical pesticides were widely used in the region, heavier water consumers (>2.2 L/day) had double the risk of light users (<1.1 L/day, Ptrend = .01). Among all participants, cumulative arsenic exposure from all water sources, lagged 40 years, yielded a positive risk gradient (Ptrend = .004); among the highest-exposed participants (97.5th percentile), risk was twice that of the lowest-exposure quartile (odds ratio = 2.24, 95% confidence interval = 1.29 to 3.89)., Conclusions: Our findings support an association between low-to-moderate levels of arsenic in drinking water and bladder cancer risk in New England. In addition, historical consumption of water from private wells, particularly dug wells in an era when arsenical pesticides were widely used, was associated with increased bladder cancer risk and may have contributed to the New England excess., (Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the United States.)

Objectives: To efficiently and reproducibly assess occupational diesel exhaust exposure in a Spanish case-control study, we examined the utility of applying decision rules that had been extracted from expert estimates and questionnaire response patterns using classification tree (CT) models from a similar US study., Methods: First, previously extracted CT decision rules were used to obtain initial ordinal (0-3) estimates of the probability, intensity, and frequency of occupational exposure to diesel exhaust for the 10 182 jobs reported in a Spanish case-control study of bladder cancer. Second, two experts reviewed the CT estimates for 350 jobs randomly selected from strata based on each CT rule's agreement with the expert ratings in the original study [agreement rate, from 0 (no agreement) to 1 (perfect agreement)]. Their agreement with each other and with the CT estimates was calculated using weighted kappa (κ w) and guided our choice of jobs for subsequent expert review. Third, an expert review comprised all jobs with lower confidence (low-to-moderate agreement rates or discordant assignments, n = 931) and a subset of jobs with a moderate to high CT probability rating and with moderately high agreement rates (n = 511). Logistic regression was used to examine the likelihood that an expert provided a different estimate than the CT estimate based on the CT rule agreement rates, the CT ordinal rating, and the availability of a module with diesel-related questions., Results: Agreement between estimates made by two experts and between estimates made by each of the experts and the CT estimates was very high for jobs with estimates that were determined by rules with high CT agreement rates (κ w: 0.81-0.90). For jobs with estimates based on rules with lower agreement rates, moderate agreement was observed between the two experts (κ w: 0.42-0.67) and poor-to-moderate agreement was observed between the experts and the CT estimates (κ w: 0.09-0.57). In total, the expert review of 1442 jobs changed 156 probability estimates, 128 intensity estimates, and 614 frequency estimates. The expert was more likely to provide a different estimate when the CT rule agreement rate was <0.8, when the CT ordinal ratings were low to moderate, or when a module with diesel questions was available., Conclusions: Our reliability assessment provided important insight into where to prioritize additional expert review; as a result, only 14% of the jobs underwent expert review, substantially reducing the exposure assessment burden. Overall, we found that we could efficiently, reproducibly, and reliably apply CT decision rules from one study to assess exposure in another study., (Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2016.)

Few studies have demonstrated gene/environment interactions in cancer research. Using data on high-risk occupations for 2258 case patients and 2410 control patients from two bladder cancer studies, we observed that three of 16 known or candidate bladder cancer susceptibility variants displayed statistically significant and consistent evidence of additive interactions; specifically, the GSTM1 deletion polymorphism (P interaction ≤ .001), rs11892031 (UGT1A, P interaction = .01), and rs798766 (TMEM129-TACC3-FGFR3, P interaction = .03). There was limited evidence for multiplicative interactions. When we examined detailed data on a prevalent occupational exposure associated with increased bladder cancer risk, straight metalworking fluids, we also observed statistically significant additive interaction for rs798766 (TMEM129-TACC3-FGFR3, P interaction = .02), with the interaction more apparent in patients with tumors positive for FGFR3 expression. All statistical tests were two-sided. The interaction we observed for rs798766 (TMEM129-TACC3-FGFR3) with specific exposure to straight metalworking fluids illustrates the value of integrating germline genetic variation, environmental exposures, and tumor marker data to provide insight into the mechanisms of bladder carcinogenesis., (Published by Oxford University Press 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.)

Objectives: Rule-based expert exposure assessment based on questionnaire response patterns in population-based studies improves the transparency of the decisions. The number of unique response patterns, however, can be nearly equal to the number of jobs. An expert may reduce the number of patterns that need assessment using expert opinion, but each expert may identify different patterns of responses that identify an exposure scenario. Here, hierarchical clustering methods are proposed as a systematic data reduction step to reproducibly identify similar questionnaire response patterns prior to obtaining expert estimates. As a proof-of-concept, we used hierarchical clustering methods to identify groups of jobs (clusters) with similar responses to diesel exhaust-related questions and then evaluated whether the jobs within a cluster had similar (previously assessed) estimates of occupational diesel exhaust exposure., Methods: Using the New England Bladder Cancer Study as a case study, we applied hierarchical cluster models to the diesel-related variables extracted from the occupational history and job- and industry-specific questionnaires (modules). Cluster models were separately developed for two subsets: (i) 5395 jobs with ≥1 variable extracted from the occupational history indicating a potential diesel exposure scenario, but without a module with diesel-related questions; and (ii) 5929 jobs with both occupational history and module responses to diesel-relevant questions. For each subset, we varied the numbers of clusters extracted from the cluster tree developed for each model from 100 to 1000 groups of jobs. Using previously made estimates of the probability (ordinal), intensity (µg m(-3) respirable elemental carbon), and frequency (hours per week) of occupational exposure to diesel exhaust, we examined the similarity of the exposure estimates for jobs within the same cluster in two ways. First, the clusters' homogeneity (defined as >75% with the same estimate) was examined compared to a dichotomized probability estimate (<5 versus ≥5%; <50 versus ≥50%). Second, for the ordinal probability metric and continuous intensity and frequency metrics, we calculated the intraclass correlation coefficients (ICCs) between each job's estimate and the mean estimate for all jobs within the cluster., Results: Within-cluster homogeneity increased when more clusters were used. For example, ≥80% of the clusters were homogeneous when 500 clusters were used. Similarly, ICCs were generally above 0.7 when ≥200 clusters were used, indicating minimal within-cluster variability. The most within-cluster variability was observed for the frequency metric (ICCs from 0.4 to 0.8). We estimated that using an expert to assign exposure at the cluster-level assignment and then to review each job in non-homogeneous clusters would require ~2000 decisions per expert, in contrast to evaluating 4255 unique questionnaire patterns or 14983 individual jobs., Conclusions: This proof-of-concept shows that using cluster models as a data reduction step to identify jobs with similar response patterns prior to obtaining expert ratings has the potential to aid rule-based assessment by systematically reducing the number of exposure decisions needed. While promising, additional research is needed to quantify the actual reduction in exposure decisions and the resulting homogeneity of exposure estimates within clusters for an exposure assessment effort that obtains cluster-level expert assessments as part of the assessment process., (Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2014.)

Objectives: To evaluate occupational exposures in case-control studies, exposure assessors typically review each job individually to assign exposure estimates. This process lacks transparency and does not provide a mechanism for recreating the decision rules in other studies. In our previous work, nominal (unordered categorical) classification trees (CTs) generally successfully predicted expert-assessed ordinal exposure estimates (i.e. none, low, medium, high) derived from occupational questionnaire responses, but room for improvement remained. Our objective was to determine if using recently developed ordinal CTs would improve the performance of nominal trees in predicting ordinal occupational diesel exhaust exposure estimates in a case-control study., Methods: We used one nominal and four ordinal CT methods to predict expert-assessed probability, intensity, and frequency estimates of occupational diesel exhaust exposure (each categorized as none, low, medium, or high) derived from questionnaire responses for the 14983 jobs in the New England Bladder Cancer Study. To replicate the common use of a single tree, we applied each method to a single sample of 70% of the jobs, using 15% to test and 15% to validate each method. To characterize variability in performance, we conducted a resampling analysis that repeated the sample draws 100 times. We evaluated agreement between the tree predictions and expert estimates using Somers' d, which measures differences in terms of ordinal association between predicted and observed scores and can be interpreted similarly to a correlation coefficient., Results: From the resampling analysis, compared with the nominal tree, an ordinal CT method that used a quadratic misclassification function and controlled tree size based on total misclassification cost had a slightly better predictive performance that was statistically significant for the frequency metric (Somers' d: nominal tree = 0.61; ordinal tree = 0.63) and similar performance for the probability (nominal = 0.65; ordinal = 0.66) and intensity (nominal = 0.65; ordinal = 0.65) metrics. The best ordinal CT predicted fewer cases of large disagreement with the expert assessments (i.e. no exposure predicted for a job with high exposure and vice versa) compared with the nominal tree across all of the exposure metrics. For example, the percent of jobs with expert-assigned high intensity of exposure that the model predicted as no exposure was 29% for the nominal tree and 22% for the best ordinal tree., Conclusions: The overall agreements were similar across CT models; however, the use of ordinal models reduced the magnitude of the discrepancy when disagreements occurred. As the best performing model can vary by situation, researchers should consider evaluating multiple CT methods to maximize the predictive performance within their data., (© The Author 2014. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

Objectives: Growing evidence suggests that gender-blind assessment of exposure may introduce exposure misclassification, but few studies have characterised gender differences across occupations and industries. We pooled control responses to job-specific, industry-specific and exposure-specific questionnaires (modules) that asked detailed questions about work activities from three US population-based case-control studies to examine gender differences in work tasks and their frequencies., Methods: We calculated the ratio of female-to-male controls that completed each module. For four job modules (assembly worker, machinist, health professional, janitor/cleaner) and for subgroups of jobs that completed those modules, we evaluated gender differences in task prevalence and frequency using χ(2) and Mann-Whitney U tests, respectively., Results: The 1360 female and 2245 male controls reported 6033 and 12 083 jobs, respectively. Gender differences in female:male module completion ratios were observed for 39 of 45 modules completed by ≥20 controls. Gender differences in task prevalence varied in direction and magnitude. For example, female janitors were significantly more likely to polish furniture (79% vs 44%), while male janitors were more likely to strip floors (73% vs 50%). Women usually reported more time spent on tasks than men. For example, the median hours per week spent degreasing for production workers in product manufacturing industries was 6.3 for women and 3.0 for men., Conclusions: Observed gender differences may reflect actual differences in tasks performed or differences in recall, reporting or perception, all of which contribute to exposure misclassification and impact relative risk estimates. Our findings reinforce the need to capture subject-specific information on work tasks., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Objectives: Metalworking has been associated with an excess risk of bladder cancer in over 20 studies. Metalworking fluids (MWFs) are suspected as the responsible exposure, but epidemiological data are limited. We investigated this association among men in the New England Bladder Cancer Study using state-of-the-art, quantitative exposure assessment methods., Methods: Cases (n=895) and population controls (n=1031) provided occupational histories during personal interviews. For selected jobs, exposure-oriented modules were administered to collect information on use of three MWF types: (1) straight (mineral oil, additives), (2) soluble (mineral oil, water, additives) and (3) synthetic (water, organics, additives) or semisynthetic (hybrid of soluble and synthetic). We computed ORs and 95% CIs relating bladder cancer risk to a variety of exposure metrics, adjusting for smoking and other factors. Non-metalworkers who had held jobs with possible exposure to mineral oil were analysed separately., Results: Bladder cancer risk was elevated among men who reported using straight MWFs (OR=1.7, 95% CI 1.1 to 2.8); risk increased monotonically with increasing cumulative exposure (p=0.041). Use of soluble MWFs was associated with a 50% increased risk (95% CI 0.96 to 2.5). ORs were non-significantly elevated for synthetic/semisynthetic MWFs based on a small number of exposed men. Non-metalworkers holding jobs with possible exposure to mineral oil had a 40% increased risk (95% CI 1.1 to 1.8)., Conclusions: Exposure to straight MWFs was associated with a significantly increased bladder cancer risk, as was employment in non-metalworking jobs with possible exposure to mineral oil. These findings strengthen prior evidence for mineral oil as a bladder carcinogen., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.)

Objectives: Evaluating occupational exposures in population-based case-control studies often requires exposure assessors to review each study participant's reported occupational information job-by-job to derive exposure estimates. Although such assessments likely have underlying decision rules, they usually lack transparency, are time consuming and have uncertain reliability and validity. We aimed to identify the underlying rules to enable documentation, review and future use of these expert-based exposure decisions., Methods: Classification and regression trees (CART, predictions from a single tree) and random forests (predictions from many trees) were used to identify the underlying rules from the questionnaire responses, and an expert's exposure assignments for occupational diesel exhaust exposure for several metrics: binary exposure probability and ordinal exposure probability, intensity and frequency. Data were split into training (n=10 488 jobs), testing (n=2247) and validation (n=2248) datasets., Results: The CART and random forest models' predictions agreed with 92-94% of the expert's binary probability assignments. For ordinal probability, intensity and frequency metrics, the two models extracted decision rules more successfully for unexposed and highly exposed jobs (86-90% and 57-85%, respectively) than for low or medium exposed jobs (7-71%)., Conclusions: CART and random forest models extracted decision rules and accurately predicted an expert's exposure decisions for the majority of jobs, and identified questionnaire response patterns that would require further expert review if the rules were applied to other jobs in the same or different study. This approach makes the exposure assessment process in case-control studies more transparent, and creates a mechanism to efficiently replicate exposure decisions in future studies.

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 (κ(w)=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.

Genome-wide association studies have identified a SNP, rs2294008, on 8q24.3 within the prostate stem cell antigen (PSCA) gene, as a risk factor for bladder cancer. To fine-map this region, we imputed 642 SNPs within 100 Kb of rs2294008 in addition to 33 markers genotyped in one of the reported genome-wide association study in 8,652 subjects. A multivariable logistic regression model adjusted for rs2294008 revealed a unique signal, rs2978974 (r(2) = 0.02, D' = 0.19 with rs2294008). In the combined analysis of 5,393 cases and 7,324 controls, we detected a per-allele odds ratio (OR) = 1.11 [95% confidence interval (CI) = 1.06-1.17, P = 5.8 × 10(-5)] for rs2294008 and OR = 1.07 (95% CI = 1.02-1.13, P = 9.7 × 10(-3)) for rs2978974. The effect was stronger in carriers of both risk variants (OR = 1.24, 95% CI = 1.08-1.41, P = 1.8 × 10(-3)) and there was a significant multiplicative interaction (P = 0.035) between these two SNPs, which requires replication in future studies. The T risk allele of rs2294008 was associated with increased PSCA mRNA expression in two sets of bladder tumor samples (n = 36, P = 0.0007 and n = 34, P = 0.0054) and in normal bladder samples (n = 35, P = 0.0155), but rs2978974 was not associated with PSCA expression. SNP rs2978974 is located 10 Kb upstream of rs2294008, within an alternative untranslated first exon of PSCA. The non-risk allele G of rs2978974 showed strong interaction with nuclear proteins from five cell lines tested, implying a regulatory function. In conclusion, a joint effect of two PSCA SNPs, rs2294008 and rs2978974, suggests that both variants may be important for bladder cancer susceptibility, possibly through different mechanisms that influence the control of mRNA expression and interaction with regulatory factors.

Objectives: We used data from a large, population-based case-control study in Maine, New Hampshire, and Vermont to examine relationships between occupation, industry and bladder cancer risk., Methods: Lifetime occupational histories were obtained by personal interview from 1158 patients newly diagnosed with urothelial carcinoma of the bladder in 2001-2004, and from 1402 population controls. Unconditional logistic regression was used to calculate ORs and 95% CIs, adjusted for demographic factors, smoking and employment in other high-risk occupations., Results: Male precision metalworkers and metalworking/plasticworking machine operators had significantly elevated risks and significant trends in risk with duration of employment (precision metalworkers: OR 2.2, 95% CI 1.4 to 3.4, p(trend) = 0.0065; metalworking/plasticworking machine operators: OR 1.6, 95% CI 1.01 to 2.6, p(trend) = 0.047). Other occupations/industries for which risk increased significantly with duration of employment included: for men, textile machine operators, mechanics/repairers, automobile mechanics, plumbers, computer systems analysts, information clerks, and landscape industry workers; for women, service occupations, health services, cleaning and building services, management-related occupations, electronic components manufacturing and transportation equipment manufacturing. Men reporting use of metalworking fluids (MWF) had a significantly elevated bladder cancer risk (OR 1.7, 95% CI 1.1 to 2.5)., Conclusions: Our findings support the hypothesis that some component(s) of MWF may be carcinogenic to the bladder. Our results also corroborate many other previously reported associations between bladder cancer risk and various occupations. More detailed analyses using information from the study's job-specific questionnaires may help to identify MWF components that may be carcinogenic, and other bladder carcinogens associated with a variety of occupations.

Pathology reports represent a rich data source for cancer registries. The College of American Pathologists (CAP) Cancer Checklists present pathology reports in synoptic form and allow registries to be updated electronically. To assess the challenge of employing the CAP Cancer Checklists in pathology laboratories and transmitting that information to cancer registries, we conducted a pilot project: the Reporting Pathology Protocols project (RPP2). The RPP2 project was a multi-year, "proof of concept" demonstration that assessed pathology report-generated data for 3 CAP Cancer Checklists (breast, prostate, and melanoma) in several different cancer registry-pathology laboratory combinations in 3 states. Collaborating pathology laboratories and state cancer registries in California, Maine, and Pennsylvania identified key questions (queries) to address in the course of the project, developed and tested standardized HL7 messaging specifications to link senders and recipients, and then assessed the actual process results using either parallel reporting or retrospective-prospective cases for each tumor type. Successful electronic transfer and capture of pertinent data elements for numerous examples of each tumor type was accomplished in each participating cancer registry/reporting laboratory/information system combination. We noted shortcomings in the electronically encoded CAP Checklists as opposed to text-based reports, particularly for breast cancers. We uncovered opportunities to improve Checklists and the information systems that incorporate them. Workflow, productivity, and timeliness of reporting are areas where electronically encoded reports may enhance cancer registry processes. The accuracy and completeness of electronically encoded data appears largely comparable to text-based data, but subject to the degree of synchrony between the formats of text-based and electronic reports.