To further quantify the association between physical activity (PA) after breast cancer diagnosis and all-cause mortality, breast cancer mortality and/or breast cancer recurrence.
PubMed was searched ...until November 2017 for observational studies investigating any type of PA in association with total mortality, breast cancer mortality and/or breast cancer recurrence among women with breast cancer diagnosis. Pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using random-effects models for highest versus lowest categories of PA. Ten studies were included in the meta-analysis. During an average follow-up ranging from 3.5 to 12.7 years there were 23,041 breast cancer survivors, 2,522 deaths from all causes, 841 deaths from breast cancer and 1,398 recurrences/remissions. Compared to women in the lowest recreational PA level (lowest quintile/quartile), women in the highest level had a lower risk of all-cause mortality (HR = 0.58, 95% CIs: 0.45–0.75; 8 studies), of death from breast cancer (HR = 0.60, 95% CIs 0.36–0.99; 5 studies) and a lower, albeit non-significant, risk of recurrence (HR = 0.79, 95% CIs 0.60–1.05; 5 studies). There was evidence of heterogeneity between the studies evaluating recreational PA and total mortality (Ι2 = 52.4%) and even higher for breast cancer mortality (Ι2 = 77.7%) or recurrence (Ι2 = 66.4%).
Highest recreational PA after breast cancer diagnosis was associated with lower all-cause and breast cancer mortality. This finding probably reflects the favorable impact of PA on cardiovascular mortality, and a possible favorable role on breast cancer survival, though reverse causation cannot be excluded.
•Physical activity was associated with survival among breast cancer survivors.•Post-diagnosis physical activity was inversely associated with all-cause mortality.•Post-diagnosis physical activity was inversely associated with breast-cancer mortality.•The inverse association with breast cancer recurrence was consistent but not significant.
A Mediterranean diet (one that is high in vegetables, legumes, fruits and nuts, and fish and low in meat and high-fat dairy products and that includes moderate intake of alcohol) is believed to have ...health benefits. In this large prospective cohort study conducted in Greece, greater adherence to a Mediterranean diet was associated with a reduction in overall mortality, and specifically in mortality due to coronary disease or cancer, after adjustment for body-mass index, physical-activity level, and other potential confounders.
In this large study in Greece, lower mortality due to coronary disease or cancer.
Many studies have evaluated the associations between food groups, foods, or nutrients and chronic diseases, and a consensus about the role of nutritional factors in the etiology of these diseases has gradually emerged.
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During the past 10 years, several groups of investigators have attempted to identify dietary patterns associated with increased longevity.
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Because these studies have used data that were collected for other purposes, they have usually not included general populations or have not had sufficient information to control for energy intake or physical activity, two variables that are crucial in studies of diet.
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Also, rather than using . . .
Assessing diet through dietary patterns has become popular in diet-disease investigations due to the appealing simplicity of expressing several dietary exposures through one variable. Current ...evidence suggests that there may exist a priori and a posteriori dietary patterns that are consistently associated with reduced all-cause, as well as site-specific cancer risk across different populations. Typical examples include the Mediterranean dietary pattern, the Healthy Eating Index, a number of "healthy" a posteriori dietary patterns, and others. Despite their apparent differences, by inspecting their components it seems that multiple dietary patterns reflect core constituents of a healthy diet. Ongoing research is targeted to: (a) identify the common features underlying the beneficial-for-cancer-prevention dietary patterns, (b) decompose the estimated associations of dietary patterns with cancer risk to the individual associations of their components, and (c) construct dietary patterns for site-specific cancer risk prediction. Results of these and other initiatives could be helpful for public health policy makers and responsible bodies to (a) better formulate relevant messages for informing people about the components of cancer-preventing diets, and (b) promote small changes in eating patterns that can lower cancer risk and improve cancer outcomes.
Osteonecrosis of the jaw (ONJ) has been associated recently with the use of pamidronate and zoledronic acid. We studied the incidence, characteristics, and risk factors for the development of ONJ ...among patients treated with bisphosphonates for bone metastases.
ONJ was assessed prospectively since July 2003. The first bisphosphonate treatment among patients with ONJ was administered in 1997. Two hundred fifty-two patients who received bisphosphonates since January 1997 were included in this analysis.
Seventeen patients (6.7%) developed ONJ: 11 of 111 (9.9%) with multiple myeloma, two of 70 (2.9%) with breast cancer, three of 46 (6.5%) with prostate cancer, and one of 25 (4%) with other neoplasms (P = .289). The median number of treatment cycles and time of exposure to bisphosphonates were 35 infusions and 39.3 months for patients with ONJ compared with 15 infusions (P < .001) and 19 months (P = .001), respectively, for patients with no ONJ. The incidence of ONJ increased with time to exposure from 1.5% among patients treated for 4 to 12 months to 7.7% for treatment of 37 to 48 months. The cumulative hazard was significantly higher with zoledronic acid compared with pamidronate alone or pamidronate and zoledronic acid sequentially (P < .001). All but two patients with ONJ had a history of dental procedures within the last year or use of dentures.
The use of bisphosphonates seems to be associated with the development of ONJ. Length of exposure seems to be the most important risk factor for this complication. The type of bisphosphonate may play a role and previous dental procedures may be a precipitating factor.
Many studies have focused on investigating deviations from additive interaction of two dichotomous risk factors on a binary outcome. There is, however, a gap in the literature with respect to ...interactions on the additive scale of >2 risk factors. In this paper, we present an approach for examining deviations from additive interaction among three or more binary exposures. The relative excess risk due to interaction (RERI) is used as measure of additive interaction. First, we concentrate on three risk factors - we propose to decompose the total RERI to: the RERI owned to the joint presence of all three risk factors and the RERI of any two risk factors, given that the third is absent. We then extend this approach, to >3 binary risk factors. For illustration, we use a sample from data from the Greek EPIC cohort and we investigate the association with overall mortality of Mediterranean diet, body mass index , and smoking. Our formulae enable better interpretability of any evidence for deviations from additivity owned to more than two risk factors and provide simple ways of communicating such results from a public health perspective by attributing any excess relative risk to specific combinations of these factors.
Abbreviations: BMI: Body Mass Index; ERR: excess relative risk; EPIC: European Prospective Investigation into Cancer and nutrition; MD: Mediterranean diet; RERI: relative excess risk due to interaction; RR: relative risk; TotRERI: total relative excess risk due to interaction
Metabolomics is a potentially powerful tool for identification of biomarkers associated with lifestyle exposures and risk of various diseases. This is the rationale of the 'meeting-in-the-middle' ...concept, for which an analytical framework was developed in this study. In a nested case-control study on hepatocellular carcinoma (HCC) within the European Prospective Investigation into Cancer and nutrition (EPIC), serum (1)H nuclear magnetic resonance (NMR) spectra (800 MHz) were acquired for 114 cases and 222 matched controls. Through partial least square (PLS) analysis, 21 lifestyle variables (the 'predictors', including information on diet, anthropometry and clinical characteristics) were linked to a set of 285 metabolic variables (the 'responses'). The three resulting scores were related to HCC risk by means of conditional logistic regressions. The first PLS factor was not associated with HCC risk. The second PLS metabolomic factor was positively associated with tyrosine and glucose, and was related to a significantly increased HCC risk with OR = 1.11 (95% CI: 1.02, 1.22, P = 0.02) for a 1SD change in the responses score, and a similar association was found for the corresponding lifestyle component of the factor. The third PLS lifestyle factor was associated with lifetime alcohol consumption, hepatitis and smoking, and had negative loadings on vegetables intake. Its metabolomic counterpart displayed positive loadings on ethanol, glutamate and phenylalanine. These factors were positively and statistically significantly associated with HCC risk, with 1.37 (1.05, 1.79, P = 0.02) and 1.22 (1.04, 1.44, P = 0.01), respectively. Evidence of mediation was found in both the second and third PLS factors, where the metabolomic signals mediated the relation between the lifestyle component and HCC outcome. This study devised a way to bridge lifestyle variables to HCC risk through NMR metabolomics data. This implementation of the 'meeting-in-the-middle' approach finds natural applications in settings characterised by high-dimensional data, increasingly frequent in the omics generation.
Methylation measures quantified by microarray techniques can be affected by systematic variation due to the technical processing of samples, which may compromise the accuracy of the measurement ...process and contribute to bias the estimate of the association under investigation. The quantification of the contribution of the systematic source of variation is challenging in datasets characterized by hundreds of thousands of features.In this study, we introduce a method previously developed for the analysis of metabolomics data to evaluate the performance of existing normalizing techniques to correct for unwanted variation. Illumina Infinium HumanMethylation450K was used to acquire methylation levels in over 421,000 CpG sites for 902 study participants of a case-control study on breast cancer nested within the EPIC cohort. The principal component partial R-square (PC-PR2) analysis was used to identify and quantify the variability attributable to potential systematic sources of variation. Three correcting techniques, namely ComBat, surrogate variables analysis (SVA) and a linear regression model to compute residuals were applied. The impact of each correcting method on the association between smoking status and DNA methylation levels was evaluated, and results were compared with findings from a large meta-analysis.
A sizeable proportion of systematic variability due to variables expressing 'batch' and 'sample position' within 'chip' was identified, with values of the partial R
statistics equal to 9.5 and 11.4% of total variation, respectively. After application of ComBat or the residuals' methods, the contribution was 1.3 and 0.2%, respectively. The SVA technique resulted in a reduced variability due to 'batch' (1.3%) and 'sample position' (0.6%), and in a diminished variability attributable to 'chip' within a batch (0.9%). After ComBat or the residuals' corrections, a larger number of significant sites (
= 600 and
= 427, respectively) were associated to smoking status than the SVA correction (
= 96).
The three correction methods removed systematic variation in DNA methylation data, as assessed by the PC-PR2, which lent itself as a useful tool to explore variability in large dimension data. SVA produced more conservative findings than ComBat in the association between smoking and DNA methylation.
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 two-part 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.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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