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- Johansson, Mattias, et al.
(författare)
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Circulating Biomarkers of One-Carbon Metabolism in Relation to Renal Cell Carcinoma Incidence and Survival
- 2014
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 106:12
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Tidskriftsartikel (refereegranskat)abstract
- Background: The etiology of renal cell carcinoma (RCC) is only partially understood, but a metabolic component appears likely. We investigated biomarkers of one-carbon metabolism and RCC onset and survival. Methods: The European Prospective Investigation into Cancer and Nutrition (EPIC) recruited 385 747 participants with blood samples between 1992 and 2000, and this analysis included 556 RCC case-control pairs. A subsequent replication study included 144 case-control pairs nested within the Melbourne Collaborative Cohort Study (MCCS). Plasma concentrations of vitamin B2, vitamin B6, folate, vitamin B12, methionine and homocysteine were measured in prediagnostic samples and evaluated with respect to RCC risk using conditional and unconditional logistic regression models, and to all-cause mortality in RCC cases using Cox regression models. All statistical tests were two-sided. Results: EPIC participants with higher plasma concentrations of vitamin B6 had lower risk of RCC, the odds ratio comparing the 4th and 1st quartiles (OR4vs1) being 0.40 95% confidence interval [CI] = 0.28 to 0.57, P-trend < .001. We found similar results after adjusting for potential confounders (adjusted P-trend < .001). In survival analysis, the hazard ratio for all-cause mortality in RCC cases when comparing the 4th and 1st quartiles (HR4vs1) of vitamin B6 was 0.57 (95% CI = 0.37 to 0.87, P-trend < .001). Subsequent replication of these associations within the MCCS yielded very similar results for both RCC risk (OR4vs1 = 0.47, 95% CI = 0.23 to 0.99, P-trend = .07) and all-cause mortality (HR4vs1 = 0.56, 95% CI = 0.27 to 1.17, P-trend = .02). No association was evident for the other measured biomarkers. Conclusion: Study participants with higher circulating concentrations of vitamin B6 had lower risk of RCC and improved survival following diagnosis in two independent cohorts.
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- Muller, David C., et al.
(författare)
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Circulating 25-Hydroxyvitamin D-3 in Relation to Renal Cell Carcinoma Incidence and Survival in the EPIC Cohort
- 2014
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Ingår i: American Journal of Epidemiology. - : Oxford University Press (OUP). - 0002-9262 .- 1476-6256. ; 180:8, s. 810-820
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Tidskriftsartikel (refereegranskat)abstract
- Normal renal function is essential for vitamin D metabolism, but it is unclear whether circulating vitamin D is associated with risk of renal cell carcinoma (RCC). We assessed whether 25-hydroxyvitamin D-3 (25(OH)D-3) was associated with risk of RCC and death after RCC diagnosis in the European Prospective Investigation into Cancer and Nutrition (EPIC). EPIC recruited 385,747 participants with blood samples between 1992 and 2000. The current study included 560 RCC cases, 557 individually matched controls, and 553 additional controls. Circulating 25(OH)D-3 was assessed by mass spectrometry. Conditional and unconditional logistic regression models were used to calculate odds ratios and 95% confidence intervals. Death after RCC diagnosis was assessed using Cox proportional hazards models and flexible parametric survival models. A doubling of 25(OH)D-3 was associated with 28% lower odds of RCC after adjustment for season of and age at blood collection, sex, and country of recruitment (odds ratio = 0.72, 95% confidence interval: 0.60, 0.86; P = 0.0004). This estimatewas attenuated somewhat after additional adjustment for smoking status at baseline, circulating cotinine, body mass index (weight (kg)/height (m)(2)), and alcohol intake (odds ratio = 0.82, 95% confidence interval: 0.68, 0.99; P = 0.038). There was also some indication that both low and high 25(OH)D-3 levels were associated with higher risk of death from any cause among RCC cases.
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- Agogo, George O., et al.
(författare)
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Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design : EPIC Case Study
- 2014
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 9:11, s. e113160-
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Tidskriftsartikel (refereegranskat)abstract
- In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted twopart regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.
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