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Träfflista för sökning "swepub ;lar1:(umu);pers:(Riboli Elio);pers:(Chirlaque Maria Dolores);pers:(Peeters Petra H M);pers:(Khaw Kay Tee);srt2:(2012)"

Sökning: swepub > Umeå universitet > Riboli Elio > Chirlaque Maria Dolores > Peeters Petra H M > Khaw Kay Tee > (2012)

  • Resultat 1-3 av 3
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1.
  • Grote, Verena A., et al. (författare)
  • The association of circulating adiponectin levels with pancreatic cancer risk: A study within the prospective EPIC cohort
  • 2012
  • Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 130, s. 2428-2437
  • Tidskriftsartikel (refereegranskat)abstract
    • Excess body weight and type 2 diabetes mellitus, risk factors of pancreatic cancer, are characterized by decreased levels of adiponectin. In addition to anti-inflammatory and anti-proliferative actions, adiponectin has an important role in regulating glucose metabolism, i.e., decreasing circulating blood glucose levels. Prospectively, hyperglycemia has been associated with risk of pancreatic cancer. The aim of this study was to investigate the association of pre-diagnostic adiponectin levels with pancreatic cancer risk. We conducted a case-control study nested within European Prospective Investigation into Cancer and Nutrition. Blood samples of 452 pancreatic cancer cases and 452 individually matched controls were analyzed by immunoassays. Multivariate conditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI). Overall, adiponectin showed no association with pancreas cancer risk; however, among never smokers, higher circulating levels of adiponectin were associated with a reduction in pancreatic cancer risk (OR = 0.44 [95% CI 0.23-0.82] for highest vs. lowest quartile), whereas among current smokers there was no significant association (OR = 1.59 [95% CI 0.67-3.76] for highest vs. lowest quartile; p-trend = 0.530; p-interaction = 0.309). In our study, lower adiponectin concentrations may be associated with the development of pancreatic cancer among never smokers, whereas the only other prospective study being conducted so far showed a decrease in risk among male smokers. Therefore, further studies are needed to clarify the role of adiponectin in pancreatic cancer development. © 2011 UICC.
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2.
  • Braem, Marieke G. M., et al. (författare)
  • Multiple Miscarriages Are Associated with the Risk of Ovarian Cancer: Results from the European Prospective Investigation into Cancer and Nutrition
  • 2012
  • Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 7:5
  • Tidskriftsartikel (refereegranskat)abstract
    • While the risk of ovarian cancer clearly reduces with each full-term pregnancy, the effect of incomplete pregnancies is unclear. We investigated whether incomplete pregnancies (miscarriages and induced abortions) are associated with risk of epithelial ovarian cancer. This observational study was carried out in female participants of the European Prospective Investigation into Cancer and Nutrition (EPIC). A total of 274,442 women were followed from 1992 until 2010. The baseline questionnaire elicited information on miscarriages and induced abortions, reproductive history, and lifestyle-related factors. During a median follow-up of 11.5 years, 1,035 women were diagnosed with incident epithelial ovarian cancer. Despite the lack of an overall association (ever vs. never), risk of ovarian cancer was higher among women with multiple incomplete pregnancies (HR >= 4vs.0: 1.74, 95% CI: 1.20-2.70; number of cases in this category: n = 23). This association was particularly evident for multiple miscarriages (HR >= 4vs.0: 1.99, 95% CI: 1.06-3.73; number of cases in this category: n = 10), with no significant association for multiple induced abortions (HR >= 4vs.0: 1.46, 95% CI: 0.68-3.14; number of cases in this category: n = 7). Our findings suggest that multiple miscarriages are associated with an increased risk of epithelial ovarian cancer, possibly through a shared cluster of etiological factors or a common underlying pathology. These findings should be interpreted with caution as this is the first study to show this association and given the small number of cases in the highest exposure categories.
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3.
  • Hoggart, Clive, et al. (författare)
  • A Risk Model for Lung Cancer Incidence
  • 2012
  • Ingår i: Cancer Prevention Research. - Philadelphia : American Association for Cancer Research. - 1940-6207 .- 1940-6215. ; 5:6, s. 834-846
  • Tidskriftsartikel (refereegranskat)abstract
    • Risk models for lung cancer incidence would be useful for prioritising individuals for screening and participation in clinical trials of chemoprevention. We present a risk model for lung cancer built using prospective cohort data from a general population which predicts individual incidence in a given time period.We build separate risk models for current and former smokers utilising 169,035 ever smokers from the multicentre European Prospective Investigation into Cancer and Nutrition (EPIC) and considered a model for never smokers. The data set was split into independent training and test sets. Lung cancer incidence was modelled using survival analysis, stratifying by age started smoking, and for former smokers, also smoking duration. Other risk factors considered were smoking intensity, ten occupational/environmental exposures previously implicated with lung cancer, and SNPs at two loci identified by genome-wide association studies of lung cancer. Individual risk in the test set was measured by the predicted probability of lung cancer incidence in the year preceding last follow-up time, predictive accuracy was measured by the area under the receiver operator characteristic curve (AUC).Utilising smoking information alone gave good predictive accuracy: the AUC and 95% confidence interval in ever smokers was 0.843 (0.810, 0.875), the Bach model applied to the same data gave an AUC of 0.775 (0.737, 0.813). Other risk factors had negligible effect on the AUC, including never smokers for whom prediction was poor.Our model is generalisable and straightforward to implement. Its accuracy can be attributed to its modelling of lifetime exposure to smoking.
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