Comparison of three frailty measures for predicting hospitalization and mortality in the Canadian Longitudinal Study on Aging.

BACKGROUND: Few studies have compared different measures of frailty for predicting adverse outcomes. It remains unknown which frailty measurement approach best predicts healthcare utilization such as hospitalization and mortality. AIMS: This study aims to compare three approaches to measuring frailty-grip strength, frailty phenotype, and frailty index-in predicting hospitalization and mortality among middle-aged and older Canadians. METHODS: We analyzed baseline and the first 3-year follow-up data for 30,097 participants aged 45 to 85 years from the comprehensive cohort of the Canadian Longitudinal Study on Aging (CLSA). Using separate logistic regression models adjusted for multimorbidity, age and biological sex, we predicted participants' risks for overnight hospitalization in the past 12 months and mortality, at the first 3-year follow-up, using each of the three frailty measurements at baseline. Model discrimination was assessed using Harrell's c-statistic and calibration assessed using calibration plots. RESULTS: The predictive performance of all three measures of frailty were roughly similar when predicting overnight hospitalization and mortality risk among CLSA participants. Model discrimination measured using c-statistics ranged from 0.67 to 0.69 for hospitalization and 0.79 to 0.80 for mortality. All measures of frailty yielded strong model calibration. DISCUSSION AND CONCLUSION: All three measures of frailty had similar predictive performance. Discrimination was modest for predicting hospitalization and superior in predicting mortality. This likely reflects the objective nature of mortality as an outcome and the challenges in reducing the complex concept of healthcare utilization to a single variable such as any overnight hospitalization.

The Influence of Smoking and Occupational Risk Factors on DNA Methylation in the AHRR and F2RL3 Genes.

BACKGROUND: AHRR and F2RL3 hypomethylation has been associated with lung cancer. In this study, we investigated the cross-sectional association between smoking and occupational exposures, and AHRR and F2RL3 methylation. METHODS: A case-control study was nested in CARTaGENE to examine the association between AHRR and F2RL3 methylation and lung cancer risk (200 cases; 400 controls). A secondary analysis was conducted using the data collected from this nested study; namely, baseline information on participants' smoking behavior and longest-held job was obtained. A cumulative smoking index summarized information on the number of cigarettes smoked, duration of smoking, and time since cessation. Exposure to 13 occupational agents was estimated using the Canadian Job Exposure Matrix. In baseline blood samples, methylation ratios of 40 CpG sites in the AHRR and F2RL3 genes were measured using Sequenom EpiTYPER. Separate least squares regression models were used to estimate the associations between smoking and occupational exposures, and average AHRR and F2RL3 methylation levels, while adjusting for confounders identified from directed acyclic graphs. RESULTS: In both genes, smoking was associated with lower average methylation levels. Occupational exposure to aromatic amines, cadmium, and formaldehyde were associated with lower AHRR methylation while, only benzene was associated with F2RL3 hypomethylation; these associations were stronger among ever smokers. CONCLUSIONS: Our findings support that smoking and occupational exposures to some agents are associated with AHRR and F2RL3 hypomethylation. IMPACT: Our results inform on mechanisms underlying environmental exposures in lung cancer etiology; future studies should prioritize studying joint exposures.

Occupational Exposures and Lung Cancer Risk-An Analysis of the CARTaGENE Study.

OBJECTIVE: To determine the associations between prevalent occupational agents and lung cancer risk. METHODS: A case-cohort design (ncases= 147; nsub-cohort= 1,032) was nested within the CARTaGENE prospective cohort study. The Canadian Job Exposure Matrix was used to determine the probability of exposure to 27 agents in participants' longest-held jobs. Multivariable logistic regression with robust variance estimators was used to determine the associations between each agent and lung cancer risk while adjusting for established lung cancer risk factors. RESULTS: Increased lung cancer risk was observed among those exposed to ashes, calcium sulfate, formaldehyde, cooking fumes, alkanes, aliphatic aldehydes, and cleaning agents. Lower lung cancer risk was found among participants exposed to carbon monoxide and polycyclic aromatic hydrocarbons from petroleum. CONCLUSION: Our findings support the role of several occupational agents, for which we have limited knowledge, in contributing to lung cancer risk.

Variation in the UGT2B17 genotype, exemestane metabolism and menopause-related toxicities in the CCTG MAP.3 trial.

PURPOSE: To examine associations between the UGT2B17 gene deletion and exemestane metabolites, and commonly reported side effects (fatigue, hot flashes, and joint pain) among postmenopausal women participating in the MAP.3 chemoprevention trial. METHODS: The analytical samples for the UGT2B17 analysis comprised 1752 women on exemestane and 1721 women on placebo; the exemestane metabolite analysis included 1360 women on exemestane with one-year serum samples. Both the UGT2B17 gene deletion and metabolites were measured in blood. The metabolites were conceptualized as a ratio (17-DHE-Gluc:17-DHE). Symptoms were assessed using the CTCAE v4.0 at approximately 1-year intervals. Log-binomial regression was used to examine the associations between UGT2B17 deletion, exemestane metabolites and each side effect at 1 and up to 5-year follow-up, adjusting for potential confounders. RESULTS: Among individuals on exemestane with the UGT2B17 gene deletion (i.e., lower detoxification), a higher risk of severe fatigue (RR = 2.59 95% CI: 1.14-5.89) was observed at up to 5-year follow-up. Among individuals on placebo, those with the UGT2B17 gene deletion had a higher risk of any fatigue (RR = 1.39, 95% CI: 1.02-1.89) at year 1. A lower metabolite ratio (poor detoxification) was associated with a higher risk of any fatigue, hot flashes and joint pain at year 1 (fatigue: RR = 1.89, 95% CI: 1.16-3.09; hot flashes: RR = 1.77, 95% CI: 1.40-2.24; joint pain: RR = 2.05, 95% CI: 1.35-3.12); similar associations were observed at 5-year follow-up. CONCLUSION: Variation in the metabolism of exemestane through the UGT2B17-mediated pathway is associated with subsequent risk of commonly reported symptoms in MAP.3.

Baseline estrogen levels in postmenopausal women participating in the MAP.3 breast cancer chemoprevention trial.

OBJECTIVE: The aim of the study was to quantify baseline estradiol (E2) and estrone (E1) concentrations according to selected patient characteristics in a substudy nested within the MAP.3 chemoprevention trial. METHODS: E2 and E1 levels were measured in 4,068 postmenopausal women using liquid chromatography-tandem mass spectrometry. Distributions were described by age, years since menopause, race, body mass index (BMI), smoking status, and use and duration of hormone therapy using the Kruskal-Wallis test. Multivariable linear regression was also used to identify characteristics associated with estrogen levels. RESULTS: After truncation at the 97.5th percentile, the mean (SD)/median (IQR) values for E2 and E1 were 5.41 (4.67)/4.0 (2.4-6.7) pg/mL and 24.7 (14.1)/21 (15-31) pg/mL, respectively. E2 and E1 were strongly correlated (Pearson correlation [r] = 0.8, P < 0.01). The largest variation in E2 and E1 levels was by BMI; mean E2 and E1 levels were 3.5 and 19.1 pg/mL, respectively for women with BMI less than 25 and 7.5 and 30.6 pg/mL, respectively, for women with BMI greater than 30. E2 and E1 varied by age, BMI, smoking status, and prior hormone therapy in multivariable models (P < 0.01). CONCLUSIONS: There was large interindividual variability observed for E2 and E1 that varied significantly by participant characteristics, but with small absolute differences except in the case of BMI. Although the majority of participant characteristics were independently associated with E1 and E2, together, these factors only explained about 20% of the variation in E1 and E2 levels.

Development of and Selected Performance Characteristics of CANJEM, a General Population Job-Exposure Matrix Based on Past Expert Assessments of Exposure.

Objectives: We developed a job-exposure matrix called CANJEM using data generated in population-based case-control studies of cancer. This article describes some of the decisions in developing CANJEM, and some of its performance characteristics. Methods: CANJEM is built from exposure information from 31673 jobs held by study subjects included in our past case-control studies. For each job, experts had evaluated the intensity, frequency, and likelihood of exposure to a predefined list of agents based on jobs histories and descriptions of tasks and workplaces. The creation of CANJEM involved a host of decisions regarding the structure of CANJEM, and operational decisions regarding which parameters to present. The goal was to produce an instrument that would provide great flexibility to the user. In addition to describing these decisions, we conducted analyses to assess how well CANJEM covered the range of occupations found in Canada. Results: Even at quite a high level of resolution of the occupation classifications and time periods, over 90% of the recent Canadian working population would be covered by CANJEM. Prevalence of exposure of specific agents in specific occupations ranges from 0% to nearly 100%, thereby providing the user with basic information to discriminate exposed from unexposed workers. Furthermore, among exposed workers there is information that can be used to discriminate those with high exposure from those with low exposure. Conclusions: CANJEM provides good coverage of the Canadian working population and possibly that of several other countries. Available in several occupation classification systems and including 258 agents, CANJEM can be used to support exposure assessment efforts in epidemiology and prevention of occupational diseases.

Occupational exposures to leaded and unleaded gasoline engine emissions and lung cancer risk.

OBJECTIVES: To determine whether occupational exposure to gasoline engine emissions (GEE) increased the risk of lung cancer and more specifically whether leaded or unleaded GEE increased the risk. METHODS: Two population-based case-control studies were conducted in Montreal, Canada. The first was conducted in the early 1980s and included many types of cancer including lung cancer. The second was conducted in the late 1990s and focused on lung cancer. Population controls were used in both studies. Altogether, there were 1595 cases and 1432 population controls. A comprehensive expert-based exposure assessment procedure was implemented and exposure was assessed for 294 agents, including unleaded GEE, leaded GEE and diesel engine emissions (DEE). Logistic regression analyses were conducted to estimate ORs between various metrics of GEE exposure and lung cancer, adjusting for smoking, DEE and other potential confounders. RESULTS: About half of all controls were occupationally exposed to GEE. Irrespective of the metrics of exposure (any exposure, duration of exposure and cumulative exposure) and the type of lung cancer, and the covariates included in models, none of the point estimates of the ORs between occupational exposure to leaded or unleaded GEE and lung cancer were above 1.0. Pooling two studies, the OR for any exposure to leaded GEE was 0.82 (0.68-1.00). CONCLUSIONS: Our results do not support the hypothesis that occupational exposure to GEE increases the risk of lung cancer.

The consumption of coffee and black tea and the risk of lung cancer.

PURPOSE: Coffee and black tea are among the most consumed beverages worldwide. Although their potential role in lung cancer occurrence has been investigated in several studies, results have been inconclusive. We investigated the associations between intake of coffee and black tea with lung cancer in a population-based case-control study in Montreal, Canada. METHODS: These analyses included 1130 cases and 1483 controls. Adjusted odds ratios (ORs) were estimated between four metrics of coffee and black tea consumption (frequency, average daily amount, duration, and cumulative amount) and lung cancer, using unconditional logistic regression. RESULTS: The adjusted ORs (95% confidence intervals) for lung cancer comparing daily to never consumers were 0.73 (0.49-1.10) for coffee and 1.05 (0.85-1.31) for black tea. Analyses of other metrics did not reveal any clear patterns of increasing or decreasing risk with increasing amounts or duration of consumption. There was no strong evidence of OR modification by sex or smoking level. The OR estimates did not materially differ by histological subtype for either of the beverages. CONCLUSION: Our results do not provide strong support for associations between consumption of coffee and black tea and lung cancer.

A simulation model of waterborne gastro-intestinal disease outbreaks: description and initial evaluation.

We present an agent-based simulation model for generating realistic multivariable outbreak signals. The model defines a synthetic population and simulates the dissemination of pathogenic organisms through a municipal water distribution system, the mobility of individuals between geographic locations, their exposure to pathogens through water consumption, and disease progression in infected individuals. We present the results of an initial evaluation of the model - a simulation study replicating the historical outbreak of cryptosporidiosis in Milwaukee in 1993.