Multi-Trait Body Shape Phenotypes and Breast Cancer Risk in Postmenopausal Women: A Causal Mediation Analysis in the UK Biobank Cohort.

Body shape phenotypes combining multiple anthropometric traits have been linked to postmenopausal breast cancer (BC). However, underlying biological pathways remain poorly understood. This study investigated to what extent the associations of body shapes with postmenopausal BC risk is mediated by biochemical markers. The study included 176,686 postmenopausal women from UK Biobank. Four body shape phenotypes were derived from principal component (PC) analysis of height, weight, body mass index, waist and hip circumferences, and waist-to-hip ratio (WHR). The four-way decomposition of the total effect was used to estimate mediation and interaction effects simultaneously as well as the mediated proportions. After 10.9 years median follow-up, 6,396 incident postmenopausal BC were diagnosed. There was strong evidence of positive associations between PC1 (general obesity) and PC2 (tall, low WHR), and BC risk. The association of PC1 with BC risk was positively mediated by testosterone and negatively by insulin-like growth factor-1 (IGF-1), with the overall proportion mediated (sum of the mediated interaction and pure indirect effect (PIE)) accounting for 11.4% (95% confidence intervals: 5.1 to 17.8%) and -12.2% (-20.5% to -4.0%) of the total effect, respectively. Small proportions of the association between PC2 and BC were mediated by IGF-1 (PIE: 2.8% (0.6 to 4.9%)), and sex hormone-binding globulin (SHBG) (PIE: -6.1% (-10.9% to -1.3%)). Our findings are consistent with differential pathways linking different body shapes with BC risk, with a suggestive mediation through testosterone and IGF-1 in the relationship of a generally obese body shape and BC risk, while IGF-1 and SHBG may mediate a tall/lean body shape-BC risk association.

Application of Metabolomics to Epidemiologic Studies of Breast Cancer: New Perspectives for Etiology and Prevention.

PURPOSE: To provide an overview on how the application of metabolomics (high-throughput characterization of metabolites from cells, organs, tissues, or biofluids) to population-based studies may inform our understanding of breast cancer etiology. METHODS: We evaluated studies that applied metabolomic analyses to prediagnostic blood samples from prospective epidemiologic studies to identify circulating metabolites associated with breast cancer risk, overall and by breast cancer subtype and menopausal status. We provide some important considerations for the application and interpretation of metabolomics approaches in this context. RESULTS: Overall, specific lipids and amino acids were indicated as the most common metabolite classes associated with breast cancer development. However, comparison of results across studies is challenging because of heterogeneity in laboratory techniques, analytical methods, sample size, and applied statistical methods. CONCLUSION: Metabolomics is being increasingly applied to population-based studies for the identification of new etiologic hypotheses and/or mechanisms related to breast cancer development. Despite its success in applications to epidemiology, studies of larger sample size with detailed information on menopausal status, breast cancer subtypes, and repeated biologic samples collected over time are needed to improve comparison of results between studies and enhance validation of results, allowing potential clinical translation of findings.

Key takeaways for knowledge expansion of early-career scientists conducting Transdisciplinary Research in Energetics and Cancer (TREC): a report from the TREC Training Workshop 2022.

The overall goal of the annual Transdisciplinary Research in Energetics and Cancer (TREC) Training Workshop is to provide transdisciplinary training for scientists in energetics and cancer and clinical care. The 2022 Workshop included 27 early-to-mid career investigators (trainees) pursuing diverse TREC research areas in basic, clinical, and population sciences. The 2022 trainees participated in a gallery walk, an interactive qualitative program evaluation method, to summarize key takeaways related to program objectives. Writing groups were formed and collaborated on this summary of the 5 key takeaways from the TREC Workshop. The 2022 TREC Workshop provided a targeted and unique networking opportunity that facilitated meaningful collaborative work addressing research and clinical needs in energetics and cancer. This report summarizes the 2022 TREC Workshop's key takeaways and future directions for innovative transdisciplinary energetics and cancer research.

Pan-cancer analysis of pre-diagnostic blood metabolite concentrations in the European Prospective Investigation into Cancer and Nutrition.

BACKGROUND: Epidemiological studies of associations between metabolites and cancer risk have typically focused on specific cancer types separately. Here, we designed a multivariate pan-cancer analysis to identify metabolites potentially associated with multiple cancer types, while also allowing the investigation of cancer type-specific associations. METHODS: We analysed targeted metabolomics data available for 5828 matched case-control pairs from cancer-specific case-control studies on breast, colorectal, endometrial, gallbladder, kidney, localized and advanced prostate cancer, and hepatocellular carcinoma nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. From pre-diagnostic blood levels of an initial set of 117 metabolites, 33 cluster representatives of strongly correlated metabolites and 17 single metabolites were derived by hierarchical clustering. The mutually adjusted associations of the resulting 50 metabolites with cancer risk were examined in penalized conditional logistic regression models adjusted for body mass index, using the data-shared lasso penalty. RESULTS: Out of the 50 studied metabolites, (i) six were inversely associated with the risk of most cancer types: glutamine, butyrylcarnitine, lysophosphatidylcholine a C18:2, and three clusters of phosphatidylcholines (PCs); (ii) three were positively associated with most cancer types: proline, decanoylcarnitine, and one cluster of PCs; and (iii) 10 were specifically associated with particular cancer types, including histidine that was inversely associated with colorectal cancer risk and one cluster of sphingomyelins that was inversely associated with risk of hepatocellular carcinoma and positively with endometrial cancer risk. CONCLUSIONS: These results could provide novel insights for the identification of pathways for cancer development, in particular those shared across different cancer types.

Diet and BMI Correlate with Metabolite Patterns Associated with Aggressive Prostate Cancer.

Three metabolite patterns have previously shown prospective inverse associations with the risk of aggressive prostate cancer within the European Prospective Investigation into Cancer and Nutrition (EPIC). Here, we investigated dietary and lifestyle correlates of these three prostate cancer-related metabolite patterns, which included: 64 phosphatidylcholines and three hydroxysphingomyelins (Pattern 1), acylcarnitines C18:1 and C18:2, glutamate, ornithine, and taurine (Pattern 2), and 8 lysophosphatidylcholines (Pattern 3). In a two-stage cross-sectional discovery (n = 2524) and validation (n = 518) design containing 3042 men free of cancer in EPIC, we estimated the associations of 24 dietary and lifestyle variables with each pattern and the contributing individual metabolites. Associations statistically significant after both correction for multiple testing (False Discovery Rate = 0.05) in the discovery set and at p < 0.05 in the validation set were considered robust. Intakes of alcohol, total fish products, and its subsets total fish and lean fish were positively associated with Pattern 1. Body mass index (BMI) was positively associated with Pattern 2, which appeared to be driven by a strong positive BMI-glutamate association. Finally, both BMI and fatty fish were inversely associated with Pattern 3. In conclusion, these results indicate associations of fish and its subtypes, alcohol, and BMI with metabolite patterns that are inversely associated with risk of aggressive prostate cancer.

Inflammatory biomarkers and risk of breast cancer among young women in Latin America: a case-control study.

BACKGROUND: Breast cancer incidence is increasing rapidly in Latin America, with a higher proportion of cases among young women than in developed countries. Studies have linked inflammation to breast cancer development, but data is limited in premenopausal women, especially in Latin America. METHODS: We investigated the associations between serum biomarkers of chronic inflammation (interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor-α (TNF-α), interferon-γ (IFN-γ), leptin, adiponectin) and risk of premenopausal breast cancer among 453 cases and 453 matched, population-based controls from Chile, Colombia, Costa Rica, and Mexico. Odds ratios (OR) were estimated using conditional logistic regression models. Analyses were stratified by size and hormonal receptor status of the tumors. RESULTS: IL-6 (ORper standard deviation (SD) = 1.33 (1.11-1.60)) and TNF-α (ORper SD = 1.32 (1.11-1.58)) were positively associated with breast cancer risk in fully adjusted models. Evidence of heterogeneity by estrogen receptor (ER) status was observed for IL-8 (P-homogeneity = 0.05), with a positive association in ER-negative tumors only. IL-8 (P-homogeneity = 0.06) and TNF-α (P-homogeneity = 0.003) were positively associated with risk in the largest tumors, while for leptin (P-homogeneity = 0.003) a positive association was observed for the smallest tumors only. CONCLUSIONS: The results of this study support the implication of chronic inflammation in breast cancer risk in young women in Latin America. Largest studies of prospective design are needed to confirm these findings in premenopausal women.

Consumption of industrial processed foods and risk of premenopausal breast cancer among Latin American women: the PRECAMA study.

Ultra-processed food intake has been linked to an increased risk of breast cancer in Western populations. No data are available in the Latin American population although the consumption of ultra-processed foods is increasing rapidly in this region. We evaluated the association of ultra-processed food intake to breast cancer risk in a case-control study including 525 cases (women aged 20-45 years) and 525 matched population-based controls from Chile, Colombia, Costa Rica and Mexico. The degree of processing of foods was classified according to the NOVA classification. Overall, the major contributors to ultra-processed food intake were ready-to-eat/heat foods (18.2%), cakes and desserts (16.7%), carbonated and industrial fruit juice beverages (16.7%), breakfast cereals (12.9%), sausages and reconstituted meat products (12.1%), industrial bread (6.1%), dairy products and derivatives (7.6%) and package savoury snacks (6.1%). Ultra-processed food intake was positively associated with the risk of breast cancer in adjusted models (OR T3-T1=1.93; 95% CI=1.11 to 3.35). Specifically, a higher risk was observed with oestrogen receptor positive breast cancer (ORT3-T1=2.44, (95% CI=1.01 to 5.90, P-trend=0.049), while no significant association was observed with oestrogen receptor negative breast cancer (ORT3-T1=1.87, 95% CI=0.43 to 8.13, P-trend=0.36). Our findings suggest that the consumption of ultra-processed foods might increase the risk of breast cancer in young women in Latin America. Further studies should confirm these findings and disentangle specific mechanisms relating ultra-processed food intake and carcinogenic processes in the breast.

Lifestyle correlates of eight breast cancer-related metabolites: a cross-sectional study within the EPIC cohort.

BACKGROUND: Metabolomics is a promising molecular tool for identifying novel etiological pathways leading to cancer. In an earlier prospective study among pre- and postmenopausal women not using exogenous hormones, we observed a higher risk of breast cancer associated with higher blood concentrations of one metabolite (acetylcarnitine) and a lower risk associated with higher blood concentrations of seven others (arginine, asparagine, phosphatidylcholines (PCs) aa C36:3, ae C34:2, ae C36:2, ae C36:3, and ae C38:2). METHODS: To identify determinants of these breast cancer-related metabolites, we conducted a cross-sectional analysis to identify their lifestyle and anthropometric correlates in 2358 women, who were previously included as controls in case-control studies nested within the European Prospective Investigation into Cancer and Nutrition cohort and not using exogenous hormones at blood collection. Associations of each metabolite concentration with 42 variables were assessed using linear regression models in a discovery set of 1572 participants. Significant associations were evaluated in a validation set (n = 786). RESULTS: For the metabolites previously associated with a lower risk of breast cancer, concentrations of PCs ae C34:2, C36:2, C36:3, and C38:2 were negatively associated with adiposity and positively associated with total and saturated fat intakes. PC ae C36:2 was also negatively associated with alcohol consumption and positively associated with two scores reflecting adherence to a healthy lifestyle. Asparagine concentration was negatively associated with adiposity. Arginine and PC aa C36:3 concentrations were not associated to any of the factors examined. For the metabolite previously associated with a higher risk of breast cancer, acetylcarnitine, a positive association with age was observed. CONCLUSIONS: These associations may indicate possible mechanisms underlying associations between lifestyle and anthropometric factors, and risk of breast cancer. Further research is needed to identify potential non-lifestyle correlates of the metabolites investigated.

A New Pipeline for the Normalization and Pooling of Metabolomics Data.

Pooling metabolomics data across studies is often desirable to increase the statistical power of the analysis. However, this can raise methodological challenges as several preanalytical and analytical factors could introduce differences in measured concentrations and variability between datasets. Specifically, different studies may use variable sample types (e.g., serum versus plasma) collected, treated, and stored according to different protocols, and assayed in different laboratories using different instruments. To address these issues, a new pipeline was developed to normalize and pool metabolomics data through a set of sequential steps: (i) exclusions of the least informative observations and metabolites and removal of outliers; imputation of missing data; (ii) identification of the main sources of variability through principal component partial R-square (PC-PR2) analysis; (iii) application of linear mixed models to remove unwanted variability, including samples' originating study and batch, and preserve biological variations while accounting for potential differences in the residual variances across studies. This pipeline was applied to targeted metabolomics data acquired using Biocrates AbsoluteIDQ kits in eight case-control studies nested within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Comprehensive examination of metabolomics measurements indicated that the pipeline improved the comparability of data across the studies. Our pipeline can be adapted to normalize other molecular data, including biomarkers as well as proteomics data, and could be used for pooling molecular datasets, for example in international consortia, to limit biases introduced by inter-study variability. This versatility of the pipeline makes our work of potential interest to molecular epidemiologists.

Biomarkers of mammographic density in premenopausal women.

BACKGROUND: While mammographic density is one of the strongest risk factors for breast cancer, little is known about its determinants, especially in young women. We applied targeted metabolomics to identify circulating metabolites specifically associated with mammographic density in premenopausal women. Then, we aimed to identify potential correlates of these biomarkers to guide future research on potential modifiable determinants of mammographic density. METHODS: A total of 132 metabolites (acylcarnitines, amino acids, biogenic amines, glycerophospholipids, sphingolipids, hexose) were measured by tandem liquid chromatography/mass spectrometry in plasma samples from 573 premenopausal participants in the Mexican Teachers' Cohort. Associations between metabolites and percent mammographic density were assessed using linear regression models, adjusting for breast cancer risk factors and accounting for multiple tests. Mean concentrations of metabolites associated with percent mammographic density were estimated across levels of several lifestyle and metabolic factors. RESULTS: Sphingomyelin (SM) C16:1 and phosphatidylcholine (PC) ae C30:2 were inversely associated with percent mammographic density after correction for multiple tests. Linear trends with percent mammographic density were observed for SM C16:1 only in women with body mass index (BMI) below the median (27.4) and for PC ae C30:2 in women with a BMI over the median. SM C16:1 and PC ae C30:2 concentrations were positively associated with cholesterol (total and HDL) and inversely associated with number of metabolic syndrome components. CONCLUSIONS: We identified new biomarkers associated with mammographic density in young women. The association of these biomarkers with mammographic density and metabolic parameters may provide new perspectives to support future preventive actions for breast cancer.

Body size, silhouette trajectory and the risk of breast cancer in a Moroccan case-control study.

BACKGROUND: There is convincing evidence demonstrating that body size characteristics such as adiposity and height are associated with breast cancer in westernized countries. However, little is known about this relationship in North African countries currently undergoing nutritional transition and industrialization. The aim of this study was to explore associations between various body size characteristics, silhouette trajectories and the risk of breast cancer among Moroccan women. METHODS: In this case-control study conducted in the Fez region (2016-2017), detailed measures of body size were collected for 300 cases of breast cancer and 300 matched controls. Unconditional logistic regression was used to assess the association between body size and breast cancer risk adjusting for confounding factors. RESULTS: Higher waist circumference and hip circumference were positively associated with breast cancer risk in pre- (highest [T3] vs. lowest tertile [T1]: OR = 2.92, 95% confidence intervals [CI]: 1.33-6.42; OR = 3.00, 95% CI: 1.42-6.33, respectively) and post-menopausal women (T3 vs. T1: OR = 4.46, 95% CI: 1.86-10.66; OR = 4.08, 95% CI: 1.76-9.42, respectively). Body shape at younger ages (6-11 years) was inversely associated with the risk of breast cancer in premenopausal women (large vs. lean silhouette: OR = 0.31, 95% CI: 0.12-0.80). Women with the greatest increase in body shape trajectory had higher risk for both pre- and post-menopausal breast cancer (T3 vs. T1: OR = 2.74, 95% CI: 1.03-7.26; OR = 3.56, 95% CI: 1.34-9.44, respectively). CONCLUSION: Our findings suggest that adiposity, body shape at younger ages, and silhouette trajectory may play a role in the development of pre- and post-menopausal breast cancer among Moroccan women. Larger-scale prospective studies are needed to confirm our findings and to explore these associations with breast cancer subtypes.

Anthropometry, body shape in early-life and risk of premenopausal breast cancer among Latin American women: results from the PRECAMA study.

Cumulating evidence in Caucasian women suggests a positive association between height and premenopausal breast cancer risk and a negative association with overall adiposity; however data from Latin America are scarce. We investigated the associations between excess adiposity, body shape evolution across life, and risk of premenopausal breast cancer among 406 cases (women aged 20-45) and 406 matched population-based controls from Chile, Colombia, Costa Rica, and Mexico. Negative associations between adult adiposity and breast cancer risk were observed in adjusted models (body mass index (BMI): Odds ratio (OR) per 1 kg/m2 = 0.93; 95% confidence interval = 0.89-0.96; waist circumference (WC): OR per 10 cm = 0.81 (0.69-0.96); hip circumference (HC): OR per 10 cm = 0.80 (0.67-0.95)). Height and leg length were not associated with risk. In normal weight women (18.5 ≤ BMI < 25), women with central obesity (WC > 88 cm) had an increased risk compared to women with normal WC (OR = 3.60(1.47-8.79)). Residuals of WC over BMI showed positive associations when adjusted for BMI (OR per 10 cm = 1.38 (0.98-1.94)). Body shape at younger ages and body shape evolution were not associated with risk. No heterogeneity was observed by receptor status. In this population of Latin American premenopausal women, different fat distributions in adulthood were differentially associated with risk of breast cancer.

Nutrient-wide association study of 92 foods and nutrients and breast cancer risk.

BACKGROUND: Several dietary factors have been reported to be associated with risk of breast cancer, but to date, unequivocal evidence only exists for alcohol consumption. We sought to systematically assess the association between intake of 92 foods and nutrients and breast cancer risk using a nutrient-wide association study. METHODS: Using data from 272,098 women participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) study, we assessed dietary intake of 92 foods and nutrients estimated by dietary questionnaires. Cox regression was used to quantify the association between each food/nutrient and risk of breast cancer. A false discovery rate (FDR) of 0.05 was used to select the set of foods and nutrients to be replicated in the independent Netherlands Cohort Study (NLCS). RESULTS: Six foods and nutrients were identified as associated with risk of breast cancer in the EPIC study (10,979 cases). Higher intake of alcohol overall was associated with a higher risk of breast cancer (hazard ratio (HR) for a 1 SD increment in intake = 1.05, 95% CI 1.03-1.07), as was beer/cider intake and wine intake (HRs per 1 SD increment = 1.05, 95% CI 1.03-1.06 and 1.04, 95% CI 1.02-1.06, respectively), whereas higher intakes of fibre, apple/pear, and carbohydrates were associated with a lower risk of breast cancer (HRs per 1 SD increment = 0.96, 95% CI 0.94-0.98; 0.96, 95% CI 0.94-0.99; and 0.96, 95% CI 0.95-0.98, respectively). When evaluated in the NLCS (2368 cases), estimates for each of these foods and nutrients were similar in magnitude and direction, with the exception of beer/cider intake, which was not associated with risk in the NLCS. CONCLUSIONS: Our findings confirm a positive association of alcohol consumption and suggest an inverse association of dietary fibre and possibly fruit intake with breast cancer risk.

Prospective analysis of circulating metabolites and breast cancer in EPIC.

BACKGROUND: Metabolomics is a promising molecular tool to identify novel etiologic pathways leading to cancer. Using a targeted approach, we prospectively investigated the associations between metabolite concentrations in plasma and breast cancer risk. METHODS: A nested case-control study was established within the European Prospective Investigation into Cancer cohort, which included 1624 first primary incident invasive breast cancer cases (with known estrogen and progesterone receptor and HER2 status) and 1624 matched controls. Metabolites (n = 127, acylcarnitines, amino acids, biogenic amines, glycerophospholipids, hexose, sphingolipids) were measured by mass spectrometry in pre-diagnostic plasma samples and tested for associations with breast cancer incidence using multivariable conditional logistic regression. RESULTS: Among women not using hormones at baseline (n = 2248), and after control for multiple tests, concentrations of arginine (odds ratio [OR] per SD = 0.79, 95% confidence interval [CI] = 0.70-0.90), asparagine (OR = 0.83 (0.74-0.92)), and phosphatidylcholines (PCs) ae C36:3 (OR = 0.83 (0.76-0.90)), aa C36:3 (OR = 0.84 (0.77-0.93)), ae C34:2 (OR = 0.85 (0.78-0.94)), ae C36:2 (OR = 0.85 (0.78-0.88)), and ae C38:2 (OR = 0.84 (0.76-0.93)) were inversely associated with breast cancer risk, while the acylcarnitine C2 (OR = 1.23 (1.11-1.35)) was positively associated with disease risk. In the overall population, C2 (OR = 1.15 (1.06-1.24)) and PC ae C36:3 (OR = 0.88 (0.82-0.95)) were associated with risk of breast cancer, and these relationships did not differ by breast cancer subtype, age at diagnosis, fasting status, menopausal status, or adiposity. CONCLUSIONS: These findings point to potentially novel pathways and biomarkers of breast cancer development. Results warrant replication in other epidemiological studies.

[Obesity and Cancer]. / Obésité et cancer.

In the past decades, obesity and overweight prevalence has been rising worldwide, in both men and women. In France, the prevalence of overweight in adults was 49% in 2015 (54% among men and 44% among women), including 17% of obese adults. According to the last evaluation performed by IARC in 2017, overweight and obesity are established risk factors for 13 cancer sites with risk estimates per 5kg/m2 varying largely depending on the cancer site. In 2015 in France, 5.4% of cancer cases could be attributed to excess weight, corresponding to 18,600 cases, including 3400 colon cancers, 2600 kidney cancers, 4500 breast cancers and 2500 endometrial cancers. Obesity is also related to worse prognosis for some cancers, in particular breast and colon cancers. Obesity in children and adolescents, also rising in many countries, has also been associated to an increase in adult cancer risk. A major cause of obesity is a disequilibrium in energy balance favoured by a diet rich in processed food, red meat, trans and saturated fatty acids, sweetened foods and beverages and poor in fruits and vegetables, legumes and whole grains. Main national and international recommendations to reduce the prevalence of obesity are to have a balanced diet and regular physical activity.

Receptor activator of nuclear factor kB ligand, osteoprotegerin, and risk of death following a breast cancer diagnosis: results from the EPIC cohort.

BACKGROUND: Receptor activator of nuclear factor kappa-B (RANK)-signaling is involved in tumor growth and spread in experimental models. Binding of RANK ligand (RANKL) to RANK activates signaling, which is inhibited by osteoprotegerin (OPG). We have previously shown that circulating soluble RANKL (sRANKL) and OPG are associated with breast cancer risk. Here we extend these findings to provide the first data on pre-diagnosis concentrations of sRANKL and OPG and risk of breast cancer-specific and overall mortality after a breast cancer diagnosis. METHODS: Two thousand six pre- and postmenopausal women with incident invasive breast cancer (1620 (81%) with ER+ disease) participating in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort were followed-up for mortality. Pre-diagnosis concentrations of sRANKL and OPG were quantified in baseline serum samples using an enzyme-linked immunosorbent assay and electrochemiluminescent assay, respectively. Hazard ratios (HRs) and 95% confidence intervals (CIs) for breast cancer-specific and overall mortality were calculated using Cox proportional hazards regression models. RESULTS: Especially in women with ER+ disease, higher circulating OPG concentrations were associated with higher risk of breast cancer-specific (quintile 5 vs 1 HR 1.77 [CI 1.03, 3.04]; ptrend 0.10) and overall mortality (q5 vs 1 HR 1.39 [CI 0.94, 2.05]; ptrend 0.02). sRANKL and the sRANKL/OPG ratio were not associated with mortality following a breast cancer diagnosis. CONCLUSIONS: High pre-diagnosis endogenous concentrations of OPG, the decoy receptor for RANKL, were associated with increased risk of death after a breast cancer diagnosis, especially in those with ER+ disease. These results need to be confirmed in well-characterized patient cohorts.

Reproductive factors and molecular subtypes of breast cancer among premenopausal women in Latin America: the PRECAMA study.

Etiological differences among breast cancer (BC) subtypes have not been clearly established, especially among young women in Latin America. This study examined the relationship between reproductive factors and BC subtypes among 288 BC cases (20-45 years) and population-based matched controls in four Latin American countries. Immunohistochemistry was determined centrally. Associations between BC and reproductive factors were determined. Older age at first full-term pregnancy (FFTP) (Odds Ratio (OR) = 1.11; 95% Confidence Interval (CI), 1.04-1.19 per year), longer time between menarche and FFTP (OR = 1.12; 95%CI: 1.04-1.20 per year), and older age at last pregnancy (OR = 1.10; 95%CI, 1.02-1.19 per year) were associated with an increased risk of estrogen receptor positive (ER+) tumors (n = 122). Ever pregnant (OR = 0.35; 95%CI, 0.13-0.96), number of childbirths (OR = 0.64; 95%CI, 0.47-0.87 per child), time since last birth (OR = 0.92; 95%CI, 0.85-0.99 per year), and history of breastfeeding (OR = 0.23; 95%CI, 0.09-0.58) were inversely associated with the risk of ER+ tumor. Older age at menarche (OR = 0.63; 95%CI, 0.45-0.89 per year) and longer duration of breastfeeding (OR = 0.97; 95%CI, 0.94-1.01 per month) were inversely associated with estrogen receptor negative (ER-) tumors (n = 48). Reproductive factors may be differentially associated with BC subtypes in young Latin American women.

Influence of a cancer diagnosis on changes in fruit and vegetable consumption according to cancer site, stage at diagnosis and socioeconomic factors: Results from the large E3N-EPIC study.

Many studies have demonstrated that lifestyle factors, including diet, may influence cancer survival. The number of cancer survivors is increasing worldwide and little is known about long-term diet changes in people who had cancer. We studied 53,981 women from the prospective E3N-EPIC cohort study with available dietary data in 1993 and 2005, among whom 4,619 had a cancer diagnosis inbetween (including n = 2,699 breast cancers). We evaluated the potential impact of a cancer diagnosis (comparing women with cancer to women with no cancer) on changes in FV consumption using multivariable linear regression models considering cancer site, stage at diagnosis and socioeconomic factors. Compared to women with no cancer, a statistically significant increase in FV consumption (ß=+2.65%, [1.22-4.09]) was observed in women who had cancer, and this association appeared to be driven by breast cancer exclusively. The increase in FV consumption was larger in women who had an advanced stage of breast cancer (stages II-IV) (ß=+7.23%, [3.92-10.5]) than in women with stages 0-I (ß=+2.03%, [-0.20 to 4.26]). Women with no partner and no children were those having the highest increase in FV consumption (ß=+18.71%, [6.51-30.91]). These changes were only observed in specific SE groups. When considering adherence to guidelines, the proportion of women who consumed less than 7.5 portions a day in 1993 and more in 2005 was greater in women with advanced breast cancer. More research is now needed to understand how the inequities we observed impact the long-term health after cancer.

Factors associated with breast cancer recurrences or mortality and dynamic prediction of death using history of cancer recurrences: the French E3N cohort.

BACKGROUND: In addition to tumor characteristics and lifestyle factors, cancer relapses are often related to the risk of death but have not been jointly studied. We investigate the prognostic factors of recurrent events and death after a diagnosis of breast cancer and predict individual deaths including a history of recurrences. METHODS: The E3N (Etude Epidémiologique auprès de Femmes de la Mutuelle Générale de l'Education Nationale) study is a prospective cohort study that was initiated in 1990 to investigate factors associated with the most common types of cancer. Overall survival and three types of recurrent events were considered: locoregional recurrence, metastasis, and second primary breast cancer. Recurrent events and death were analyzed using a joint frailty model. RESULTS: The analysis included 4926 women from the E3N cohort diagnosed with a first primary invasive breast cancer between June 1990 and June 2008; during the follow-up, 1334 cases had a recurrence (median time of follow-up is 7.2 years) and 469 women died. Cases with high grade, large tumor size, axillary nodal involvement, and negative estrogen and progesterone receptors had a higher risk of recurrence or death. Furthermore, smoking increased the risk of relapse. For cases with a medium risk profile in terms of tumor characteristics and lifestyle factors, the probability of dying between 5 and 10 years after diagnosis was 6, 20 and 36% for 0, 1 or 2 recurrences within the first 5 years after diagnosis, respectively. CONCLUSIONS: Our study showed the importance of considering baseline lifestyle characteristics and history of relapses to dynamically predict the risk of death in breast cancer cases. Medical experience coupled with an estimate of a patient's survival probability that considers all available information for this patient would enable physicians to make better informed decisions regarding their actions and thus improve clinical output.