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Sökning: WFRF:(Price Alkes L.) > (2012) > Medicin och hälsovetenskap

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1.
  • Epstein, Mara M, et al. (författare)
  • Dietary fatty acid intake and prostate cancer survival in Örebro county, Sweden
  • 2012
  • Ingår i: American Journal of Epidemiology. - : Oxford University Press (OUP). - 0002-9262 .- 1476-6256. ; 176:3, s. 240-252
  • Tidskriftsartikel (refereegranskat)abstract
    • Although dietary fat has been associated with prostate cancer risk, the association between specific fatty acids and prostate cancer survival remains unclear. Dietary intake of 14 fatty acids was analyzed in a population-based cohort of 525 Swedish men with prostate cancer in Örebro County (1989-1994). Multivariable hazard ratios and 95% confidence intervals for time to prostate cancer death by quartile and per standard deviation increase in intake were estimated by Cox proportional hazards regression. Additional models examined the association by stage at diagnosis (localized: T0-T2/M0; advanced: T0-T4/M1, T3-T4/M0). Among all men, those with the highest omega-3 docosahexaenoic acid and total marine fatty acid intakes were 40% less likely to die from prostate cancer (P(trend) = 0.05 and 0.04, respectively). Among men with localized prostate cancer, hazard ratios of 2.07 (95% confidence interval: 0.93, 4.59; P(trend) = 0.03) for elevated total fat, 2.39 (95% confidence interval: 1.06, 5.38) for saturated myristic acid, and 2.88 (95% confidence interval: 1.24, 6.67) for shorter chain (C4-C10) fatty acid intakes demonstrated increased risk for disease-specific mortality for the highest quartile compared with the lowest quartile. This study suggests that high intake of total fat and certain saturated fatty acids may worsen prostate cancer survival, particularly among men with localized disease. In contrast, high marine omega-3 fatty acid intake may improve disease-specific survival for all men.
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2.
  • Zaitlen, Noah, et al. (författare)
  • Informed Conditioning on Clinical Covariates Increases Power in Case-Control Association Studies
  • 2012
  • Ingår i: PLoS Genetics. - : Public Library of Science (PLoS). - 1553-7404. ; 8:11
  • Tidskriftsartikel (refereegranskat)abstract
    • Genetic case-control association studies often include data on clinical covariates, such as body mass index (BMI), smoking status, or age, that may modify the underlying genetic risk of case or control samples. For example, in type 2 diabetes, odds ratios for established variants estimated from low-BMI cases are larger than those estimated from high-BMI cases. An unanswered question is how to use this information to maximize statistical power in case-control studies that ascertain individuals on the basis of phenotype (case-control ascertainment) or phenotype and clinical covariates (case-controlcovariate ascertainment). While current approaches improve power in studies with random ascertainment, they often lose power under case-control ascertainment and fail to capture available power increases under case-control-covariate ascertainment. We show that an informed conditioning approach, based on the liability threshold model with parameters informed by external epidemiological information, fully accounts for disease prevalence and non-random ascertainment of phenotype as well as covariates and provides a substantial increase in power while maintaining a properly controlled falsepositive rate. Our method outperforms standard case-control association tests with or without covariates, tests of gene x covariate interaction, and previously proposed tests for dealing with covariates in ascertained data, with especially large improvements in the case of case-control-covariate ascertainment. We investigate empirical case-control studies of type 2 diabetes, prostate cancer, lung cancer, breast cancer, rheumatoid arthritis, age-related macular degeneration, and end-stage kidney disease over a total of 89,726 samples. In these datasets, informed conditioning outperforms logistic regression for 115 of the 157 known associated variants investigated (P-value = 1x10(-9)). The improvement varied across diseases with a 16% median increase in chi(2) test statistics and a commensurate increase in power. This suggests that applying our method to existing and future association studies of these diseases may identify novel disease loci.
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