Objectives We adapted previously developed decision rules from the New England Bladder Cancer Study (NEBCS) to assign occupational exposure to straight, soluble, and synthetic metalworking fluids (MWFs) to participants of the Spanish Bladder Cancer Study (SBCS).
Methods The SBCS and NEBCS are case–control studies that used the same lifetime occupational history and job module questionnaires. We adapted published decision rules from the NEBCS that linked questionnaire responses to estimates of the probability (<5, ≥5 to <50, ≥50 to <100, and 100%), frequency (in h week−1), and intensity (in mg m−3) of exposure to each of the three broad classes of MWFs to assign exposure to 10 182 reported jobs in the SBCS. The decision rules used the participant's module responses to MWF questions wherever possible. We then used these SBCS module responses to calculate job-, industry-, and time-specific patterns in the prevalence and frequency of MWF exposure. These estimates replaced the NEBCS-specific estimates in decision rules applied to jobs without MWF module responses. Intensity estimates were predicted using a previously developed statistical model that used the decade, industry (three categories), operation (grinding versus machining), and MWF type extracted from the SBCS questionnaire responses. We also developed new decision rules to assess mineral oil exposure from non-machining sources (possibly exposed versus not exposed). The decision rules for MWF and mineral oil identified questionnaire response patterns that required job-by-job expert review.
Results To assign MWF exposure, we applied decision rules that incorporated participant's responses and job group patterns for 99% of the jobs and conducted expert review of the remaining 1% (145) jobs. Overall, 14% of the jobs were assessed as having ≥5% probability of exposure to at least one of the three MWFs. Probability of exposure of ≥50% to soluble, straight, and synthetic MWFs was identified in 2.5, 1.7, and 0.5% of the jobs, respectively. To assign mineral oil from non-machining sources, we used module responses for 49% of jobs, a job-exposure matrix for 41% of jobs, and expert review for the remaining 10%. We identified 24% of jobs as possibly exposed to mineral oil from non-machining sources.
Conclusions We demonstrated that we could adapt existing decision rules to assess exposure in a new population by deriving population-specific job group patterns.
Objectives Computer-assisted coding of job descriptions to standardized occupational classification codes facilitates evaluating occupational risk factors in epidemiologic studies by reducing the number of jobs needing expert coding. We evaluated the performance of the 2nd version of SOCcer, a computerized algorithm designed to code free-text job descriptions to US SOC-2010 system based on free-text job titles and work tasks, to evaluate its accuracy.
Methods SOCcer v2 was updated by expanding the training data to include jobs from several epidemiologic studies and revising the algorithm to account for nonlinearity and incorporate interactions. We evaluated the agreement between codes assigned by experts and the highest scoring code (a measure of confidence in the algorithm-predicted assignment) from SOCcer v1 and v2 in 14,714 jobs from three epidemiology studies. We also linked exposure estimates for 258 agents in the job-exposure matrix CANJEM to the expert and SOCcer v2-assigned codes and compared those estimates using kappa and intraclass correlation coefficients. Analyses were stratified by SOCcer score, score distance between the top two scoring codes from SOCcer, and features from CANJEM.
Results SOCcer's v2 agreement at the 6-digit level was 50%, compared to 44% in v1, and was similar for the three studies (38%–45%). Overall agreement for v2 at the 2-, 3-, and 5-digit was 73%, 63%, and 56%, respectively. For v2, median ICCs for the probability and intensity metrics were 0.67 (IQR 0.59–0.74) and 0.56 (IQR 0.50–0.60), respectively. The agreement between the expert and SOCcer assigned codes linearly increased with SOCcer score. The agreement also improved when the top two scoring codes had larger differences in score.
Conclusions Overall agreement with SOCcer v2 applied to job descriptions from North American epidemiologic studies was similar to the agreement usually observed between two experts. SOCcer's score predicted agreement with experts and can be used to prioritize jobs for expert review.
5 pages, 1 figure, 2 tables.-- PMID: 16556748 [PubMed]. ; [Objetives] To evaluate lifetime exposure to trihalomethanes (THM) through ingestion, inhalation, and dermal absorption in a hospital based case‐control study of bladder cancer conducted between 1998 and 2001 in five areas of Spain. The study base was comprised of subjects living in the catchment areas of the participating hospitals. ; [Methods] Individual information on water related habits was obtained from personal interviews of 1219 cases and 1271 controls: residential and occupational history, drinking water source at each residence and job, amount of water consumption, frequency and duration of showering, bathing, and swimming pool attendance. THM levels, water source history, and year when chlorination started in study areas were ascertained through measurements in drinking water samples and questionnaires to water companies and local authorities. Estimates of THM levels covered 79% of the subjects' person‐years of exposure. ; [Result] Current and historical average THM levels in water were correlated. Control subjects reported that drinking water source in the last residence was municipal for 63%, bottled for 22%, private well for 2%, and other sources for 13%. For the time window between age 15 and the time of interview, average residential THM level was 32.2 μg/l. THM exposure through ingestion was 23.7 μg/day on average, and was correlated with the ingestion THM level in the workplace. Overall, 79% usually took showers, 16% usually took baths, and 13% had ever attended a swimming pool. Between 21% and 45% of controls unexposed to THM through ingestion were evaluated as moderately or highly exposed through showering or bathing, and 5–10% were exposed through swimming in pools. ; [Conclusion] The importance of evaluating different routes is underscored by findings from experimental studies showing substantial differences in THM uptake and internal distribution by route. ; This project was funded by the Spanish Ministry of Health (FIS 2001–2002), the EPICUR-red (ISIII-GO3/174), the Intramural Research Program of the NIH, National Cancer Institute, Division of Cancer Epidemiology and Genetics (NCI Contract No. NO2-CP-11015), and the European Union (Environment and genetic factors in bladder cancer: a multicentric case-control study in Europe. BIOMED. 1998–2001). ; Peer reviewed
Objectives Daily driving of diesel-powered tractors has been linked to increased lung cancer risk in farmers, yet few studies have quantified exposure levels to diesel exhaust during tractor driving or during other farm activities. We expanded an earlier task-based descriptive investigation of factors associated with real-time exposure levels to black carbon (BC, a surrogate of diesel exhaust) in Iowa farmers by increasing the sample size, collecting repeated measurements, and applying statistical models adapted to continuous measurements.
Methods The expanded study added 43 days of sampling, for a total of 63 sample days conducted in 2015 and 2016 on 31 Iowa farmers. Real-time, continuous monitoring (30-s intervals) of personal BC concentrations was performed using a MicroAeth AE51 microaethelometer affixed with a micro-cyclone. A field researcher recorded information on tasks, fuel type, farmer location, and proximity to burning biomass. We evaluated the influence of these variables on log-transformed BC concentrations using a linear mixed-effect model with random effects for farmer and day and a first-order autoregressive structure for within-day correlation.
Results Proximity to diesel-powered equipment was observed for 42.5% of the overall sampling time and on 61 of the 63 sample days. Predicted geometric mean BC concentrations were highest during grain bin work, loading, and harvesting, and lower for soil preparation and planting. A 68% increase in BC concentrations was predicted for close proximity to a diesel-powered vehicle, relative to far proximity, while BC concentrations were 44% higher in diesel vehicles with open cabins compared with closed cabins. Task, farmer location, fuel type, and proximity to burning biomass explained 8% of within-day variance in BC concentrations, 2% of between-day variance, and no between-farmer variance.
Conclusion Our findings showed that farmers worked frequently near diesel equipment and that BC concentrations varied between tasks and by fuel type, farmer location, and proximity to burning biomass. These results could support the development of exposure models applicable to investigations of health effects in farmers associated with exposure to diesel engine exhaust.
DNA methylation changes contribute to bladder carcinogenesis. Trihalomethanes (THM), a class of disinfection by-products, are associated with increased urothelial bladder cancer (UBC) risk. THM exposure in animal models produces DNA hypomethylation. We evaluated the relationship of LINE-1 5-methylcytosine levels (LINE-1%5mC) as outcome of long-term THM exposure among controls and as an effect modifier in the association between THM exposure and UBC risk. We used a case-control study of UBC conducted in Spain. We obtained personal lifetime residential THM levels and measured LINE-1%5mC by pyrosequencing in granulocyte DNA from blood samples in 548 incident cases and 559 hospital controls. Two LINE-1%5mC clusters (above and below 64%) were identified through unsupervised hierarchical cluster analysis. The association between THM levels and LINE-1%5mC was evaluated with β regression analyses and logistic regression was used to estimate odds ratios (OR) adjusting for covariables. LINE-1%5mC change between percentiles 75(th) and 25(th) of THM levels was 1.8% (95% confidence interval (CI): 0.1, 3.4%) among controls. THM levels above vs. below the median (26 μg/L) were associated with increased UBC risk, OR = 1.86 (95% CI: 1.25, 2.75), overall and among subjects with low levels of LINE-1%5mC (n = 975), OR = 2.14 (95% CI: 1.39, 3.30), but not associated with UBC risk among subjects' high levels of LINE-1%5mC (n = 162), interaction P = 0.03. Results suggest a positive association between LINE-1%5mC and THM levels among controls, and LINE-1%5mC status may modify the association between UBC risk and THM exposure. Because reverse causation and chance cannot be ruled out, confirmation studies are warranted. ; This study was partially supported by the Intramural Research Program of the National Institutes of Health, National Cancer Institute, Division of Cancer Epidemiology and Genetics (Contract NCI NO2-CP-11015); the Spanish Health Ministry (Fondo de Investigaciones Sanitarias–FIS, Instituto de Salud Carlos III, Spain 00/0745, ISIII-GO3/174, PI080533, PI051436, PI061614, PI09–02102, and PI11/00226) and the European Union (BMH4–98–3243); Red Temática de Investigación Cooperativa en Cáncer- RD12/0036/0050-RTICC; USA-NIH-RO1-CA089715; a postdoctoral fellowship awarded to AFSA from the Fundación Científica de la AECC; Fundació Marató TV3. The work was partially supported by the Association for International Cancer Research (AICR, #09–0780, including a PhD scholarship awarded to S.M.T.). The current analyses were supported by a Colciencias PhD Scholarship, Colombia (Grant: 529/2011 to L.A.S.). This work was also supported by grants from the Instituto de Salud Carlos III FEDER, (PI11/00226)
In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Here, we find significant evidence of a novel association at rs78417682 (7p12/TNS3, P = 4.35 × 10-8). Replication of 10 promising signals in up to 2737 patients and 4752 controls from the PANcreatic Disease ReseArch (PANDoRA) consortium yields new genome-wide significant loci: rs13303010 at 1p36.33 (NOC2L, P = 8.36 × 10-14), rs2941471 at 8q21.11 (HNF4G, P = 6.60 × 10-10), rs4795218 at 17q12 (HNF1B, P = 1.32 × 10-8), and rs1517037 at 18q21.32 (GRP, P = 3.28 × 10-8). rs78417682 is not statistically significantly associated with pancreatic cancer in PANDoRA. Expression quantitative trait locus analysis in three independent pancreatic data sets provides molecular support of NOC2L as a pancreatic cancer susceptibility gene. ; This work was supported by RO1 CA154823, the Lustgarten Foundation, and federal funds from the NCI, US NIH under contract number HHSN261200800001E. The content of this publication does not necessarily reflect the views or policies of the US Department of Health and Human Services, and mention of trade names, commercial products, or organizations does not imply endorsement by the US government. Geno-typing Services were provided by the CIDR and the NCIs CGR. CIDR is fully funded through a federal contract from the NIH to the Johns Hopkins University, contract number HHSN268201100011I. The IARC/Central Europe study was supported by a grant from the US NCI at the NIH (R03 CA123546-02) and grants from the Ministry of Health of the Czech Republic (NR 9029-4/2006, NR9422-3, NR9998-3, and MH CZ- DRO-MMCI 00209805). The work at Johns Hopkins University was supported by the NCI Grants P50CA062924 and R01CA97075. Additional support was provided by, Susan Wojcicki, and Dennis Troper, and the Sol Goldman Pancreas Cancer Research Center. The Mayo Clinic Biospecimen Resource for Pancreas Research study is supported by the Mayo Clinic SPORE in Pancreatic Cancer (P50 CA102701). The Memorial Sloan Ket- tering Cancer Center Pancreatic Tumor Registry is supported by P30CA008748, the Geoffrey Beene Foundation, the Arnold and Arlene Goldstein Family, Foundation, and the Society of MSKCC. The PACIFIC Study was supported by RO1CA102765, Kaiser Permanente, and Group Health Cooperative. The Queensland Pancreatic Cancer Study was supported by a grant from the National Health and Medical Research Council of Australia (NHMRC; Grant number 442302). R.E.N. is supported by a NHMRC Senior Research Fellowship (#1060183). The UCSF pancreas study was supported by NIH-NCI grants (R01CA1009767, R01CA109767-S1, and R0CA059706) and the Joan Rombauer Pancreatic Cancer Fund. Collection of cancer incidence data was supported by the California Department of Public Health as part of the statewide cancer reporting pro- gram; the NCIs SEER Program under contract HSN261201000140C awarded to CPIC; and the CDCs National Program of Cancer Registries, under agreement #U58DP003862-01 awarded to the California Department of Public Health. The Yale (CT) pancreas cancer study is supported by NCI at the U.S. NIH, grant 5R01CA098870. The cooperation of 30 Connecticut hospitals, including Stamford Hospital, in allowing patient access is gratefully acknowledged. The Connecticut Pancreas Cancer Study was approved by the State of Connecticut Department of Public Health Human Investigation Committee. Certain data used in that study were obtained from the Connecticut Tumor Registry in the Connecticut Department of Public Health. The authors assume full responsibility for analyses and interpretation of these data. Studies included in PAN- DoRA were partly funded by the Czech Science Foundation (No. P301/12/1734), the Internal Grant Agency of the Czech Ministry of Health (IGA NT 13 263); the Baden- Württemberg State Ministry of Research, Science and Arts (Professor H. Brenner), the Heidelberger EPZ-Pancobank (Professor M.W. Büchler and team: Professor T. Hackert, Dr. N. A. Giese, Dr. Ch. Tjaden, E. Soyka, M. Meinhardt; Heidelberger. Stiftung Chir- urgie and BMBF grant 01GS08114), the BMBH (Professor P. Schirmacher; BMBF grant 01EY1101), the " 5 × 1000 " voluntary contribution of the Italian Government, the Italian Ministry of Health (RC1203GA57, RC1303GA53, RC1303GA54, and RC1303GA50), the Italian Association for Research on Cancer (Professor A. Scarpa; AIRC n. 12182), the Italian Ministry of Research (Professor A. Scarpa; FIRB - RBAP10AHJB), the Italian FIMP-Ministry of Health (Professor A. Scarpa; 12 CUP_J33G13000210001), and by the National Institute for Health Research Liverpool Pancreas Biomedical Research Unit, UK. We would like to acknowledge the contribution of Dr. Frederike Dijk and Professor Oliver Busch (Academic Medical Center, Amsterdam, the Netherlands). Assistance with genotype data quality control was provided by Cecelia Laurie and Cathy Laurie at the University of Washington Genetic Analysis Center. The American Cancer Society (ACS) funds the creation, maintenance, and updating of the Cancer Prevention Study II cohort. Cancer incidence data for CLUE were provided by the Maryland Cancer Registry, Center for Cancer Surveillance and Control, Department of Health and Mental Hygiene, 201 W. Preston Street, Room 400, Baltimore, MD 21201, http://phpa.dhmh.maryland.gov/ cancer , 410-767-4055. We acknowledge the State of Maryland, the Maryland Cigarette Restitution Fund, and the National Program of Cancer Registries of the Centers for Disease Control and Prevention for the funds that support the collection and availability of the cancer registry data. We thank all the CLUE participants. The Melbourne Col- laborative Cohort Study (MCCS) recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057 and 396414 and by the infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry and the Australian Institute of Health and Welfare, including the National Death Index and the Australian Cancer Database. The NYU study (AZJ and AAA) was funded by NIH R01 CA098661, UM1 CA182934 and center grants P30 CA016087 and P30 ES000260. The PANKRAS II Study in Spain was supported by research grants from Instituto de Salud Carlos III-FEDER, Spain: Fondo de Investigaciones Sanitarias (FIS; #PI13/00082 and #PI15/01573) and Red Temática de Investigación Cooperativa en Cáncer, Spain (#RD12/ 0036/0050); and European Cooperation in Science and Technology (COST Action #BM1204: EU_Pancreas), Ministerio de Ciencia y Tecnología (CICYT SAF 2000-0097), Fondo de Investigación Sanitaria (95/0017), Madrid, Spain; Generalitat de Catalunya(CIRIT—SGR);"Red temática de investigación cooperativa de centros en Cáncer (C03/10),"Red temática de investigación cooperativa de centros en Epidemiología y salud pública(C03/09), and CIBER de Epidemiología (CIBERESP), Madrid. The Physicians 'Health Study was supported by research grants CA-097193, CA-34944, CA-40360, HL- 26490, and HL-34595 from the NIH, Bethesda, MD, USA. The Womens Health Study was supported by research grants CA-047988, HL-043851, HL-080467, and HL-099355 from the NIH, Bethesda, MD, USA. Health Professionals Follow-up Study is supported by NIH grant UM1 CA167552 from the NCI, Bethesda, MD, USA. Nurses ' Health Study is supported by NIH grants UM1 CA186107, P01 CA87969, and R01 CA49449 from the NCI, Bethesda, MD, USA. Additional support from the Hale Center for Pancreatic Cancer Research, U01 CA21017 from the NCI, Bethesda, MD, USA, and the United States Department of Defense CA130288, Lustgarten Foundation, Pancreatic Cancer Action Network, Noble Effort Fund, Peter R. Leavitt Family Fund, Wexler Family Fund, and Promises for Purple to B.M. Wolpin is acknowledged. The WHI program is funded by the National Heart, Lung, and Blood Institute, NIH, U.S. Department of Health and Human Services through contracts HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C. The authors thank the WHI investigators and staff for their dedication, and the study participants for making the program possible. A full listing of WHI investigators can be found at http://www.whi.org/researchers/Documents%20%20Write%20a%20Paper/WHI%20Investigator%20Long%20List.pdf . We thank Laurie Burdett, Aurelie Vogt, BelyndaHicks, Amy Hutchinson, Meredith Yeager, and other staff at the NCI's Division ofEpidemiology and Genetics (DECG) CGR for GWAS genotyping. We also thank Bao Tran, Jyoti Shetty, and other members of the NCI Center for Cancer Research (CCR) Sequencing Facility for sequencing RNA from histologically normal pancreatic tissue samples (LTG samples). This study utilized the high-performance computational cap- abilities of the Biowulf Linux cluster at the NIH, Bethesda, MD, USA (http://biowulf.nih.gov). The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the NIH, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The data used for the analyses described in this manuscript were obtained from the pancreatic tissue data from the GTEx Portal on 05/04/17. The results published here are in part based upon data generated by The Cancer Genome Atlas (TCGA) managed by the NCI and NHGRI. Information about TCGA can be found at http://cancergenome.nih.gov/. We acknowledge the clinical contributors that provided PDAC samples and the data producers of RNA-seq and GWAS genotype data from TCGA Research Network. The data set used for the analyses described in this manuscript was obtained by formal permission through the TCGA Data Access Committee (DAC) ; Sí