Brain Cancer Mortality Research Articles

Forecasting Age-Specific Brain Cancer Mortality Rates Using Functional Data Analysis Models

Incidence and mortality rates are considered as a guideline for planning public health strategies and allocating resources. We apply functional data analysis techniques to model age-specific brain cancer mortality trend and forecast entire age-specific functions using exponential smoothing state-space models. The age-specific mortality curves are decomposed using principal component analysis and fit functional time series model with basis functions. Nonparametric smoothing methods are used to mitigate the existing randomness in the observed data. We use functional time series model on age-specific brain cancer mortality rates and forecast mortality curves with prediction intervals using exponential smoothing state-space model. We also present a disparity of brain cancer mortality rates among the age groups together with the rate of change of mortality rates. The data were obtained from the Surveillance, Epidemiology and End Results (SEER) program of the United States. The brain cancer mortality rates, classified under International Classification Disease code ICD-O-3, were extracted from SEER*Stat software.

Bayesian age-stratified joinpoint regression model: an application to lung and brain cancer mortality

Joinpoint regression model identifies significant changes in the trends of the incidence, mortality, and survival of a specific disease in a given population. The purpose of the present study is to develop an age-stratified Bayesian joinpoint regression model to describe mortality trend assuming that the observed counts are probabilistically characterized by the Poisson distribution. The proposed model is based on Bayesian model selection criteria with the smallest number of joinpoints that are sufficient to explain the Annual Percentage Change. The prior probability distributions are chosen in such a way that they are automatically derived from the model index contained in the model space. The proposed model and methodology estimates the age-adjusted mortality rates in different epidemiological studies to compare the trends by accounting the confounding effects of age. In developing the subject methods, we use the cancer mortality counts of adult lung and bronchus cancer, and brain and other Central Nervous System cancer patients obtained from the Surveillance Epidemiology and End Results data base of the National Cancer Institute.

Reduced Risk of Brain Cancer Mortality from Walking and Running

This study aimed to test prospectively whether exercise is associated with lower brain cancer mortality in 111,266 runners and 42,136 walkers from the National Runners' and Walkers' Health Studies. Hazard ratios and 95% confidence intervals (95% CI) from Cox proportional hazards analyses of mortality versus metabolic equivalent hours per day of exercise (MET-hours per day, where 1 MET = 3.5 mL O2·kg·min, or approximately 1-km run). The National Death Index identified 110 brain cancer deaths during an 11.7-yr average follow-up. Runners and walkers were combined because the brain cancer risk reduction did not differ significantly between MET-hours per day run and MET-hours per day walked (P = 0.66). When adjusted for sex, age, race, education, and cohort effects, the risk for brain cancer mortality was 43.2% lower for those who exercised 1.8 to 3.5 MET·h·d (95% CI = 2.6%-66.8% lower, P = 0.04) and 39.8% lower for those who exercised ≥ 3.6 MET·h·d (95% CI = 0.0%-64.0% lower, P = 0.05) compared with <1.8 MET·h·d at baseline. Pooling the runners and walkers who expended ≥ 1.8 MET·h·d showed a 42.5% lower risk of brain cancer mortality for the entire sample (95% CI: 8.0 to 64.1, P = 0.02) and 40.0% lower risk when three deaths that occurred within 1 yr of the baseline survey were excluded (95% CI = 1.3%-62.4%, P = 0.04). The risk for fatal brain cancer decreased in association with running and walking energy expenditure. Our ability to detect an exercise-brain cancer relationship may relate to the use of cohorts specifically designed to detect exercise-health associations, and the calculation of exercise energy expenditure from kilometers per day walked and run rather than time spent exercising.

Human pontine glioma cells can induce murine tumors.

Diffuse intrinsic pontine glioma (DIPG), with a median survival of only 9 months, is the leading cause of pediatric brain cancer mortality. Dearth of tumor tissue for research has limited progress in this disease until recently. New experimental models for DIPG research are now emerging. To develop preclinical models of DIPG, two different methods were adopted: cells obtained at autopsy (1) were directly xenografted orthotopically into the pons of immunodeficient mice without an intervening cell culture step or (2) were first cultured in vitro and, upon successful expansion, injected in vivo. Both strategies resulted in pontine tumors histopathologically similar to the original human DIPG tumors. However, following the direct transplantation method all tumors proved to be composed of murine and not of human cells. This is in contrast to the indirect method that included initial in vitro culture and resulted in xenografts comprising human cells. Of note, direct injection of cells obtained postmortem from the pons and frontal lobe of human brains not affected by cancer did not give rise to neoplasms. The murine pontine tumors exhibited an immunophenotype similar to human DIPG, but were also positive for microglia/macrophage markers, such as CD45, CD68 and CD11b. Serial orthotopic injection of these murine cells results in lethal tumors in recipient mice. Direct injection of human DIPG cells in vivo can give rise to malignant murine tumors. This represents an important caveat for xenotransplantation models of DIPG. In contrast, an initial in vitro culture step can allow establishment of human orthotopic xenografts. The mechanism underlying this phenomenon observed with direct xenotransplantation remains an open question.

On fitting spatio-temporal disease mapping models using approximate Bayesian inference

Spatio-temporal disease mapping comprises a wide range of models used to describe the distribution of a disease in space and its evolution in time. These models have been commonly formulated within a hierarchical Bayesian framework with two main approaches: an empirical Bayes (EB) and a fully Bayes (FB) approach. The EB approach provides point estimates of the parameters relying on the well-known penalized quasi-likelihood (PQL) technique. The FB approach provides the posterior distribution of the target parameters. These marginal distributions are not usually available in closed form and common estimation procedures are based on Markov chain Monte Carlo (MCMC) methods. However, the spatio-temporal models used in disease mapping are often very complex and MCMC methods may lead to large Monte Carlo errors and a huge computation time if the dimension of the data at hand is large. To circumvent these potential inconveniences, a new technique called integrated nested Laplace approximations (INLA), based on nested Laplace approximations, has been proposed for Bayesian inference in latent Gaussian models. In this paper, we show how to fit different spatio-temporal models for disease mapping with INLA using the Leroux CAR prior for the spatial component, and we compare it with PQL via a simulation study. The spatio-temporal distribution of male brain cancer mortality in Spain during the period 1986-2010 is also analysed.

A Pilot Case-Cohort Study of Brain Cancer in Poultry and Control Workers

We conducted an exploratory study to investigate which exposures (including poultry oncogenic viruses) are associated with brain cancer in poultry workers. A total of 46,819 workers in poultry and nonpoultry plants from the same union were initially followed for mortality. Brain cancer was observed to be in excess among poultry workers. Here we report on a pilot case-cohort study with cases consisting of 26 (55%) of the 47 brain cancer deaths recorded in the cohort, and controls consisting of a random sample of the cohort (n = 124). Exposure information was obtained from telephone interviews, and brain cancer mortality risk estimated by odds ratios. Increased risk of brain cancer was associated with killing chickens, odds ratio (OR) = 5.8 (95% confidence interval, 1.2–28.3); working in a shell-fish farm, OR = 13.0 (95% CI, 1.9–84.2); and eating uncooked fish, OR = 8.2 (95% CI, 1.8–37.0). Decreased risks were observed for chicken pox illness, OR = 0.2 (95% CI, 0.1–0.6), and measles vaccination, OR = 0.2 (95% CI, 0.1–0.6). Killing chickens, an activity associated with the highest occupational exposure to poultry oncogenic viruses, was associated with brain cancer mortality, as were occupational and dietary shellfish exposures. These findings are novel.

Possible Effect of Implementing a National Query Program on Site-Specific Cancer Mortality Rates in Taiwan

This study aimed to examine possible effects of implementing a national query program on site-specific cancer mortality rates. A total of 2,874 query letters were sent out by the Department of Statistics, Ministry of Health and Welfare of Taiwan between January 2009 and December 2011 to medical certifiers who reported "neoplasm with uncertain nature" on the death certificate asking for more detailed information for coding. Of the 2,571 responses, in 1,398 cases (54%) medical certifiers were still unable to determine the nature of the neoplasm. There were four neoplasm sites for which more than 50% of the responses changed the category to malignant, the gastrointestinal system (73%), urinary system (60%), stomach (55%) and rectum (53%). The liver was the cancer site that showed the largest absolute increase in the number of deaths after the query; however, the brain showed the largest relative increase, at 12%. Different neoplasm sites showed different magnitudes of change in nature after the query. Brain cancer mortality rates exhibited the largest increase.

Bayesian Joinpoint Regression Model for Childhood Brain Cancer Mortality

The Bayesian approach of joinpoint regression is widely used to analyze trends in cancer mortality, incidence and survival data. The Bayesian joinpoint regression model was used to study the childhood brain cancer mortality rate and its average percentage change (APC) per year. Annual observed mortality counts of children ages 0-19 from 1969-2009 obtained from Surveillance Epidemiology and End Results (SEER) database of National Cancer Institute (NCI) were analyzed. It was assumed that death counts are probabilistically characterized by the Poisson distribution and they were modeled using log link function. Results were compared with the mortality trend obtained using joinpoint software of NCI.

Brain Cancer in Workers Employed at a Specialty Chemical Research Facility

ABSTRACT This study evaluated unique exposures and their relationship to brain cancer mortality in employees of a specialty chemical research facility. Following an exposure assessment that concerned compounds distinct to this facility, the authors conducted a cohort mortality study of 5,284 workers to assess mortality in reference to the general population and a nested case-control study to evaluate brain cancer risk associated with specific jobs and unique chemical exposures. Four hundred eighty-six deaths, including 14 brain cancer deaths, were identified. Overall mortality was lower than expected. Brain cancer mortality was elevated (standardized mortality ratio [SMR] = 2.02, 95% confidence interval [CI] = 1.11–3.40). Exposures to 5 specific chemical categories were assessed. Exploration of work history and the specific chemical exposures did not explain the brain cancer cases. No clear occupational etiology was identified.

BRAIN CANCER MORTALITY IN AN AGRICULTURAL REGION, RIO DE JANEIRO STATE, BRAZIL: A POPULATION-BASED AGE-PERIOD-COHORT STUDY

Background: Brain cancer etiology has been poorly understood. Several studies indicate that residents in agricultural regions have an increased mortality risk. Aims: To explore an age-period-cohort effect study on brain cancer mortality in Serrana Region, an agricultural area in Rio de Janeiro State, Brazil. Methods: This was a descriptive epidemiologic study of mortality brain cancer in residents &gt; 19 yr. either performed at an agricultural (Serrana Region) or a non-agricultural one (Metropolitan Region) during 1996 -2010. Trend analysis was carried out using Joinpoint regression, and the age-period-cohort effects ascertained using log-linear Poisson regression. Results: The estimated brain cancer mortality annual percentage change in Serrana Region was 3.8% (95% C.I. 0.8 and 5.6), while - 0.2 (95% C.I. -1.2 -0.7) at the Metropolitan Region. In the former, a cohort effect was observed with increased mortality risk ratios, MRR: comparatively to those born in 1945-49, men born in 1980-84 presented a MRR= 4.07 (95% C.I. 1.83-9.04), and those born in 1985-89, a MRR = 4.17 (CI95% 1.79 – 9.74). Increased risk ratios were not observed in the Metropolitan Region, while an age effect was observed in both areas. Conclusion: These findings support the hypothesis that residents in agricultural regions may have experienced an increased exposure to brain cancer risk factors. The observed cohort effect is suggestive that environmental exposures, such as pesticides and biological agents, among others related to rural activities, may represent important risk exposures involved in brain carcinogenesis.

Brain Cancer Incidence and Mortality: Differences in Geographic Region and Human Development Index

Brain Cancer Incidence and Mortality: Differences in Geographic Region and Human Development Index

LEUKEMIA MORTALITY AMONG AGRICULTURAL WORKERS, RIO DE JANEIRO, BRAZIL: AN ECOLOGICAL POPULATION-BASED CASE-CONTROL STUDY, 2006 - 2010

Background: Several studies have shown that agricultural workers have at greater risk to develop cancer, including leukemias. Occupational exposure to pesticides and biological agents have been reported as possible associated risk factors. Aims: To estimate the magnitude of association between leukemia mortality and agricultural activities after controlling for selected confounders such as ethnicity, education, and place of residence. Methods: A death certificate-based case-control study was performed with 566 leukemia deaths (cases) and 1,132 deaths (controls) with other than cancer causes of death. All data were retrieved from death certificates occurred in Rio de Janeiro State, Brazil, during 1996-2010 among male &gt; 17 yr. residents. Results: Agricultural workers were at higher risk to die by leukemia, when compared to non-agricultural workers (crude OR= 1.75; CI99%: 0.91-3.38). Adjustment by age, ethnicity, and residence showed and adjusted OR= 3.52; CI99%: 1.50-8.25). In addition, brain cancer mortality risk was higher among those individuals of higher education and white residing in selected counties. Conclusions:This study suggests an associationamong agricultural work and leukemia mortality inRio de Janeiro state. Our results reinforce the hypothesis that environmental exposures experienced by this group of workers may play a role in the development of leukemia.

Progress of the Mechanism on Cancer Induced by Pesticides

Pesticides poisoning is a clinical and social problem the whole world concerning about. There is an association between agricultural work and brain cancer mortality in the world. It also suggests that pesticide exposure may play a role in such risk. We made a review on pesticides cause cancer of the mechanisms, including mechanisms of pesticides on cytotoxicity, inflammatory cytokines, and so on.

Brain cancer mortality rates increase with Toxoplasma gondii seroprevalence in France

The incidence of adult brain cancer was previously shown to be higher in countries where the parasite Toxoplasma gondii is common, suggesting that this brain protozoan could potentially increase the risk of tumor formation. Using countries as replicates has, however, several potential confounding factors, particularly because detection rates vary with country wealth. Using an independent dataset entirely within France, we further establish the significance of the association between T. gondii and brain cancer and find additional demographic resolution. In adult age classes 55years and older, regional mortality rates due to brain cancer correlated positively with the local seroprevalence of T. gondii. This effect was particularly strong for men. While this novel evidence of a significant statistical association between T. gondii infection and brain cancer does not demonstrate causation, these results suggest that investigations at the scale of the individual are merited.

Brain cancer mortality among farm workers of the State of Rio de Janeiro, Brazil: A population-based case–control study, 1996–2005

Farm workers seem to be at an increased risk of developing some cancers, notably in the brain. One of the hypotheses rose to explain such elevated risk is the intense exposure to pesticides. To estimate the brain cancer mortality risk among agricultural workers exposed to pesticides in the State of Rio de Janeiro, Brazil. A case-control study based on death certificates of males, 18 years or older, resident in the State Rio de Janeiro who died between 1996 and 2005. Cases (n=2040) were defined as individuals with brain cancer as the underlying cause of death. For each case two controls (n=4140) were randomly selected in the same database, matched for age group and region of residence. Besides the descriptive analysis, crude and adjusted odds ratios and mortality odds ratio (MOR) according to quartiles of potential exposure to pesticides, were calculated. Agricultural workers showed higher brain cancer mortality risk estimates when compared with non-farm workers (aOR: 1.82, 95% CI 1.21-2.71). In addition, the magnitude of this association was higher among white patients, with higher education, and residence in an agricultural region. This study suggests an association between agricultural work and brain cancer mortality in Rio de Janeiro state. It also suggests that pesticide exposure may play a role in such risk.

BRAIN CANCER AMONG AGRICULTURAL WORKERS FROM RIO DE JANEIRO, BRAZIL: A DEATH CERTIFICATE-BASED CASE-CONTROL STUDY

Background: Several studies indicate that agricultural workers are at greater risk to develop some specific types of cancer, such as brain cancer. The underline hypothesis for such increased risk is the intense exposure to pesticides experienced by these workers. Objectives: To estimate the magnitude of the association between brain cancer mortality and agricultural activities, as well as ethnicity, education, and place of residence. Methods: In this death certificate-based case-control study, cases were defined as any resident of Rio de Janeiro State, 18 years or older, male, whose basic cause of death was registered as brain cancer. For each case, 2 controls were randomly chosen among any male individual, 18 years or older, whose basic cause of death was registered as any disease different from neoplasms and diseases of the Nervous System. Results: Agricultural workers were at higher risk to die by brain cancer, when compared to non-agricultural workers (OR: 1.41; CI95%: 1.09-1.85). Adjustment by age, ethnicity, and residence, increased the magnitude of this risk (OR: 1.83; CI95%: 1.26-2.65). In addition, the brain cancer mortality risk was higher among those individuals of higher education, white, and residents of Nova Friburgo region. Conclusions: In agreement with international evidences, the present study suggests an association between brain cancer mortality and agricultural activity in the State of Rio de Janeiro, Brazil. Our results reinforce the hypothesis that environmental exposures experienced by this group of workers may play a role in the development of type of cancer.

Testing for space–time interaction in conditional autoregressive models

Data on disease incidence or mortality over a set of contiguous regions have been commonly used to describe geographic patterns of disease, helping epidemiologists and public health researchers to identify possible etiologic factors. Nowadays, the availability of historical mortality registers offers the possibility of going further, describing the spatio‐temporal distribution of risks. The literature on spatio‐temporal modeling of risks is very rich, and it is mainly focused on the use of conditional autoregressive models from a fully Bayesian perspective. The complexity of the estimation procedure makes the Empirical Bayes approach a plausible alternative. In this context, it is of interest to test for interaction between space and time, as an absence of space–time interactions simplifies modeling and interpretation. In this work, a score test is derived as well as a bootstrap approximation of its null distribution. A parametric bootstrap test is also provided for comparison purposes. Results are illustrated using brain cancer mortality data from Spain in the period 1996–2005. Copyright © 2011 John Wiley &amp; Sons, Ltd.

Comparison of Time Trends in Brain and Central Nervous System Cancer Mortality (1990-2006) Between Countries Based on the WHO Mortality Database

Comparison of Time Trends in Brain and Central Nervous System Cancer Mortality (1990-2006) Between Countries Based on the WHO Mortality Database

Do brain cancer rates correlate with ambient exposure levels of criteria air pollutants or hazardous air pollutants (HAPs)?

Age-adjusted brain cancer rates vary more than fourfold among US counties, but risk factors underlying this variation have not been identified. The only known risk factor for brain cancer is ionizing radiation at therapeutic dose levels. Lifestyle factors are not known to affect brain cancer risk; hypothetical risks from environmental or occupational exposures to numerous chemicals have been suggested, but no consistent results have emerged in populations exposed to chemicals via oral intake or inhalation. We investigated whether county-by-county brain cancer incidence rates and mortality rates were correlated with patterns of local ambient air pollution. We utilized central-site ambient measurement data for criteria air pollutants, and inhalation exposure concentrations of hazardous air pollutants (HAPs) as predicted by the US EPA National Air Toxics Assessment. We selected 30 HAPs that had been variously hypothesized in the context of a link to brain cancer risk. We also included a regression on density of domestic cattle populations given that viruses have been implicated in brain cancer and cattle are a well-known reservoir for a variety of viruses. The analyses yielded correlations that were mostly null or negative, with similar results obtained for brain cancer incidence and mortality rates. The cattle density correlations were slightly positive and statistically significant. Given the limitations of this exploratory analysis, further research is needed to investigate the role of environmental chemical exposures in brain cancer risk. Our findings suggest that county-by-county differences in air pollution exposure concentrations are not likely to be explanatory factors for variations in brain cancer rates.

Ambient air pollution and brain cancer mortality

Growing evidence that ultrafine particles in ambient air can cause brain lesions in animals led us to investigate whether particulate components of air pollution may be associated with brain cancer risk in humans. Air pollution has been associated with respiratory disorders and cardiovascular morbidity and mortality, but associations between air pollutants and brain cancer have not been investigated in adults. The analyses included 1,284 deaths due to brain cancer from the Cancer Prevention Study-II, an ongoing prospective mortality study of adults in the United States and Puerto Rico conducted by the American Cancer Society. Air pollution data from national databases for metropolitan areas were combined with residential history and vital status data to estimate exposure to particulate and gaseous air pollution. We found no elevated risk for estimated measures of air pollutants, an unanticipated reduction in risk was found between gaseous air pollutants and brain cancer mortality. The findings do not provide evidence of increased risk of brain cancer mortality due to air pollutants.