scholarly journals Bayesian adjustment of gastric cancer mortality rate in the presence of misclassification

2017 ◽  
Vol 9 (4) ◽  
pp. 160
Author(s):  
Nastaran Hajizadeh ◽  
Mohamad Amin Pourhoseingholi ◽  
Ahmad Reza Baghestani ◽  
Alireza Abadi ◽  
Mohammad Reza Zali
Author(s):  
Diana R. Withrow ◽  
Neal D. Freedman ◽  
James T. Gibson ◽  
Mandi Yu ◽  
Anna M. Nápoles ◽  
...  

Abstract Purpose To inform prevention efforts, we sought to determine which cancer types contribute the most to cancer mortality disparities by individual-level education using national death certificate data for 2017. Methods Information on all US deaths occurring in 2017 among 25–84-year-olds was ascertained from national death certificate data, which include cause of death and educational attainment. Education was classified as high school or less (≤ 12 years), some college or diploma (13–15 years), and Bachelor's degree or higher (≥ 16 years). Cancer mortality rate differences (RD) were calculated by subtracting age-adjusted mortality rates (AMR) among those with ≥ 16 years of education from AMR among those with ≤ 12 years. Results The cancer mortality rate difference between those with a Bachelor's degree or more vs. high school or less education was 72 deaths per 100,000 person-years. Lung cancer deaths account for over half (53%) of the RD for cancer mortality by education in the US. Conclusion Efforts to reduce smoking, particularly among persons with less education, would contribute substantially to reducing educational disparities in lung cancer and overall cancer mortality.


2002 ◽  
Vol 34 (1) ◽  
pp. 22-28 ◽  
Author(s):  
B. Riecken ◽  
R. Pfeiffer ◽  
J.L. Ma ◽  
M.L. Jin ◽  
J.Y. Li ◽  
...  

2018 ◽  
Vol 23 (1) ◽  
pp. 153-160 ◽  
Author(s):  
Emílio Prado da Fonseca ◽  
Cláudia Di Lorenzo Oliveira ◽  
Francisco Chiaravalloti Neto ◽  
Antonio Carlos Pereira ◽  
Silvia Amélia Scudeler Vedovello ◽  
...  

Abstract The objective of this study was to determine of oral and oropharynx cancer mortality rate and the results were analyzed by applying the Spatial Analysis of Empirical Bayesian Model. To this end, we used the information contained in the International Classification of Diseases (ICD-10), Chapter II, Category C00 to C14 and Brazilian Mortality Information System (SIM) of Minas Gerais State. Descriptive statistics were observed and the gross rate of mortality was calculated for each municipality. Then Empirical Bayesian estimators were applied. The results showed that, in 2012, in the state of Minas Gerais, were registered 769 deaths of patients with cancer of oral and oropharynx, with 607 (78.96%) men and 162 (21.04%) women. There was a wide variation in spatial distribution of crude mortality rate and were identified agglomeration in the South, Central and North more accurately by Bayesian Estimator Global and Local Model. Through Bayesian models was possible to map the spatial clustering of deaths from oral cancer more accurately, and with the application of the method of spatial epidemiology, it was possible to obtain more accurate results and provide subsidies to reduce the number of deaths from this type of cancer.


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