The performance of functional methods for correcting non-Gaussian measurement error within Poisson regression: corrected excess risk of lung cancer mortality in relation to radon exposure among French uranium miners.

A broad variety of methods for measurement error (ME) correction have been developed, but these methods have rarely been applied possibly because their ability to correct ME is poorly understood. We carried out a simulation study to assess the performance of three error-correction methods: two variants of regression calibration (the substitution method and the estimation calibration method) and the simulation extrapolation (SIMEX) method. Features of the simulated cohorts were borrowed from the French Uranium Miners' Cohort in which exposure to radon had been documented from 1946 to 1999. In the absence of ME correction, we observed a severe attenuation of the true effect of radon exposure, with a negative relative bias of the order of 60% on the excess relative risk of lung cancer death. In the main scenario considered, that is, when ME characteristics previously determined as most plausible from the French Uranium Miners' Cohort were used both to generate exposure data and to correct for ME at the analysis stage, all three error-correction methods showed a noticeable but partial reduction of the attenuation bias, with a slight advantage for the SIMEX method. However, the performance of the three correction methods highly depended on the accurate determination of the characteristics of ME. In particular, we encountered severe overestimation in some scenarios with the SIMEX method, and we observed lack of correction with the three methods in some other scenarios. For illustration, we also applied and compared the proposed methods on the real data set from the French Uranium Miners' Cohort study.

Impact of measurement error in radon exposure on the estimated excess relative risk of lung cancer death in a simulated study based on the French Uranium Miners' Cohort.

Measurement error (ME) can lead to bias in the analysis of epidemiologic studies. Here a simulation study is described that is based on data from the French Uranium Miners' Cohort and that was conducted to assess the effect of ME on the estimated excess relative risk (ERR) of lung cancer death associated with radon exposure. Starting from a scenario without any ME, data were generated containing successively Berkson or classical ME depending on time periods, to reflect changes in the measurement of exposure to radon ((222)Rn) and its decay products over time in this cohort. Results indicate that ME attenuated the level of association with radon exposure, with a negative bias percentage on the order of 60% on the ERR estimate. Sensitivity analyses showed the consequences of specific ME characteristics (type, size, structure, and distribution) on the ERR estimates. In the future, it appears important to correct for ME upon analyzing cohorts such as this one to decrease bias in estimates of the ERR of adverse events associated with exposure to ionizing radiation.

Dietary intakes of omega-6 and omega-3 polyunsaturated fatty acids and the risk of breast cancer.

Experimental studies suggest detrimental effects of omega-6 polyunsaturated fatty acids (PUFA), and beneficial effects of omega-3 PUFAs on mammary carcinogenesis, possibly in interaction with antioxidants. However, PUFA food sources are diverse in human diets and few epidemiologic studies have examined whether associations between dietary PUFAs and breast cancer risk vary according to food sources or antioxidant intakes. The relationship between individual PUFA intakes estimated from diet history questionnaires and breast cancer risk was examined among 56,007 French women. During 8 years of follow-up, 1,650 women developed invasive breast cancer. Breast cancer risk was not related to any dietary PUFA overall; however, opposite associations were seen according to food sources, suggesting other potential effects than PUFA per se. Breast cancer risk was inversely associated with alpha-linolenic acid (ALA) intake from fruit and vegetables [highest vs. lowest quintile, hazard ratio (HR) 0.74; 95% confidence interval (CI) 0.63, 0.88; p trend < 0.0001], and from vegetable oils (HR 0.83; 95% CI 0.71, 0.97; p trend 0.017). Conversely, breast cancer risk was positively related to ALA intake from nut mixes (p trend 0.004) and processed foods (p trend 0.068), as was total ALA intake among women in the highest quintile of dietary vitamin E (p trend 0.036). A significant interaction was also found between omega-6 and long-chain omega-3 PUFAs, with breast cancer risk inversely related to long-chain omega-3 PUFAs in women belonging to the highest quintile of omega-6 PUFAs (p interaction 0.042). These results emphasize the need to consider food sources, as well as interactions between fatty acids and with antioxidants, when evaluating associations between PUFA intakes and breast cancer risk.

[Unsaturated fatty acids intake and breast cancer risk: epidemiological data review]. / Apport en acides gras insaturés et risque de cancer du sein: revue des études épidémiologiques.

The relationship between fatty acids and breast cancer has been debated for long, because of the high frequency of breast cancer and the contradictory results from the numerous studies devoted to this issue. The present review includes case-control and prospective studies, according to specified methodological criteria, which estimated the exposure to monounsaturated fatty acids (MUFA) and n-6 and n-3 polyunsaturated fatty acids (PUFA) using dietary questionnaires or markers (plasma, erythrocytes, adipose tissue). The relationship between MUFA intake and breast cancer risk seems to depend on the contributing food : neutral or beneficial for vegetable oil, rather deleterious for animal products. Contrary to data from animal experiments, human studies do not show an increase of breast cancer risk with n-6 PUFA intake. Estimating the risk associated with alpha-linolenic acid appears difficult due to the incompleteness of food composition tables and studies on biomarkers remain few. The same applies to long-chain n-3 PUFA despite the suggestion of a decrease in risk, in agreement with animal studies. However, it is difficult in human to disentangle the effect of nutrient intake from that of contributing foods or even nutritional profile.