RESUMO
At present, analysis of diet and bladder cancer (BC) is mostly based on the intake of individual foods. The examination of food combinations provides a scope to deal with the complexity and unpredictability of the diet and aims to overcome the limitations of the study of nutrients and foods in isolation. This article aims to demonstrate the usability of supervised data mining methods to extract the food groups related to BC. In order to derive key food groups associated with BC risk, we applied the data mining technique C5.0 with 10-fold cross-validation in the BLadder cancer Epidemiology and Nutritional Determinants study, including data from eighteen case-control and one nested case-cohort study, compromising 8320 BC cases out of 31 551 participants. Dietary data, on the eleven main food groups of the Eurocode 2 Core classification codebook, and relevant non-diet data (i.e. sex, age and smoking status) were available. Primarily, five key food groups were extracted; in order of importance, beverages (non-milk); grains and grain products; vegetables and vegetable products; fats, oils and their products; meats and meat products were associated with BC risk. Since these food groups are corresponded with previously proposed BC-related dietary factors, data mining seems to be a promising technique in the field of nutritional epidemiology and deserves further examination.
Assuntos
Mineração de Dados , Alimentos , Neoplasias da Bexiga Urinária/epidemiologia , Algoritmos , Estudos de Casos e Controles , Dieta , Feminino , Humanos , Incidência , Internacionalidade , Masculino , Fatores de RiscoRESUMO
BACKGROUND: Inconsistent results for coffee consumption and bladder cancer (BC) risk have been shown in epidemiological studies. This research aims to increase the understanding of the association between coffee consumption and BC risk by bringing together worldwide case-control studies on this topic. METHODS: Data were collected from 13 case-control comprising of 5,911 cases and 16,172 controls. Pooled multivariate odds ratios (ORs), with corresponding 95% confidence intervals (CIs), were obtained using multilevel logistic regression models. Furthermore, linear dose-response relationships were examined using fractional polynomial models. RESULTS: No association of BC risk was observed with coffee consumption among smokers. However, after adjustment for age, gender, and smoking, the risk was significantly increased for never smokers (ever vs. never coffee consumers: ORmodel2 1.30, 95% CI 1.06-1.59; heavy (> 4 cups/day) coffee consumers vs. never coffee consumers: ORmodel2 1.52, 95% CI 1.18-1.97, p trend = 0.23). In addition, dose-response analyses, in both the overall population and among never smokers, also showed a significant increased BC risk for coffee consumption of more than four cups per day. Among smokers, a significant increased BC risk was shown only after consumption of more than six cups per day. CONCLUSION: This research suggests that positive associations between coffee consumption and BC among never smokers but not smokers.
Assuntos
Café , Fumar/epidemiologia , Neoplasias da Bexiga Urinária/epidemiologia , Idoso , Estudos de Casos e Controles , Feminino , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Razão de Chances , Fatores de RiscoRESUMO
Prostate cancer remains the second most prevalent cancer in men. Its incidence, progression and mortality profiles vary significantly by race and ethnicity, with African-American men having the highest incidence rate and mortality rate in the world. Although these disparities can be partially explained by socioeconomic factors, the underlying molecular causes are complex and require careful research. A considerable amount of literature exists, supporting the association between mitochondrial health and the incidence, aggression and risk of prostate cancer. Genetic alterations in mitochondrial DNA are frequent in prostate cancer; therefore, the resulting mitochondrial dysfunction and metabolic dysregulation may contribute to or indicate oncogenesis. Many of the prominent features of cancer cells are also closely related to mitochondrial functions, such as resistance to apoptosis, excess reactive oxygen species production and altered oxidative phosphorylation. In addition, prostate cancer ethnic disparity is influenced by environmental and lifestyle factors, which involves differences in mitochondrial metabolism and retrograde signaling events.