Background Cardiovascular disease (CVD) is of increasing concern among breast cancer survivors. However the burden of this comorbidity in this group relative to the general population, and its temporal pattern, remains unknown. Methods We compared deaths due to CVD in a population-based sample of 1,413 women with incident breast cancer diagnosed in 1996-1997, and 1,411 age-matched women without breast cancer. Date and cause of death through December 31, 2009 were assessed through the National Death Index and covariate data was gathered through structured interviews and medical record abstraction. Hazard ratios and 95% confidence intervals (CI) were calculated using Cox regression for overall mortality (HR) and CVD-specific death (cause-specific HR). Subdistribution hazard ratios (sHR) for CVD death were estimated from the Fine-Gray model. Results Risk of death was greater among breast cancer survivors compared to women without breast cancer [HR: 1.8 (1.5, 2.1)]. An increase in CVD-related death among breast cancer survivors was evident only 7 years after diagnosis [years 0-7, cause-specific HR: 0.80 (0.53, 1.2), subdistribution HR: 0.59 (0.40, 0.87)]; years 7+, cause-specific HR: 1.8 (1.3, 2.5), subdistribution HR: 1.9 (1.4, 2.7); p-interaction: 0.001]. An increase in CVD-related mortality was observed among breast cancer survivors receiving chemotherapy. Conclusions Breast cancer survivors are at greater risk for CVD-related mortality compared to women without breast cancer and this increase in risk is manifest approximately 7 years after diagnosis. Efforts should be made to identify risk factors and interventions that can be employed during this brief window to reduce the excess burden of CVD in this vulnerable population.
Background In addition to the established association between general obesity and breast cancer risk, central obesity and circulating fasting insulin and glucose have been linked to the development of this common malignancy. Findings from previous studies, however, have been inconsistent, and the nature of the associations is unclear. Methods We conducted Mendelian randomization analyses to evaluate the association of breast cancer risk, using genetic instruments, with fasting insulin, fasting glucose, 2-h glucose, body mass index (BMI) and BMI-adjusted waist-hip-ratio (WHRadj BMI). We first confirmed the association of these instruments with type 2 diabetes risk in a large diabetes genome-wide association study consortium. We then investigated their associations with breast cancer risk using individual-level data obtained from 98 842 cases and 83 464 controls of European descent in the Breast Cancer Association Consortium. Results All sets of instruments were associated with risk of type 2 diabetes. Associations with breast cancer risk were found for genetically predicted fasting insulin [odds ratio (OR) = 1.71 per standard deviation (SD) increase, 95% confidence interval (CI) = 1.26-2.31, p = 5.09 × 10–4], 2-h glucose (OR = 1.80 per SD increase, 95% CI = 1.3 0-2.49, p = 4.02 × 10–4), BMI (OR = 0.70 per 5-unit increase, 95% CI = 0.65-0.76, p = 5.05 × 10–19) and WHRadj BMI (OR = 0.85, 95% CI = 0.79-0.91, p = 9.22 × 10–6). Stratified analyses showed that genetically predicted fasting insulin was more closely related to risk of estrogen-receptor [ER]-positive cancer, whereas the associations with instruments of 2-h glucose, BMI and WHRadj BMI were consistent regardless of age, menopausal status, estrogen receptor status and family history of breast cancer. Conclusions We confirmed the previously reported inverse association of genetically predicted BMI with breast cancer risk, and showed a positive association of genetically predicted fasting insulin and 2-h glucose and an inverse association of WHRadj BMI with breast cancer risk. Our study suggests that genetically determined obesity and glucose/insulin-related traits have an important role in the aetiology of breast cancer.
BackgroundObservational studies examining associations between adult height and risk of colorectal, prostate, and lung cancers have generated mixed results. We conducted meta-analyses using data from prospective cohort studies and further carried out Mendelian randomization analyses, using height-associated genetic variants identified in a genome-wide association study (GWAS), to evaluate the association of adult height with these cancers.Methods and FindingsA systematic review of prospective studies was conducted using the PubMed, Embase, and Web of Science databases. Using meta-analyses, results obtained from 62 studies were summarized for the association of a 10-cm increase in height with cancer risk. Mendelian randomization analyses were conducted using summary statistics obtained for 423 genetic variants identified from a recent GWAS of adult height and from a cancer genetics consortium study of multiple cancers that included 47,800 cases and 81,353 controls. For a 10-cm increase in height, the summary relative risks derived from the meta-analyses of prospective studies were 1.12 (95% CI 1.10, 1.15), 1.07 (95% CI 1.05, 1.10), and 1.06 (95% CI 1.02, 1.11) for colorectal, prostate, and lung cancers, respectively. Mendelian randomization analyses showed increased risks of colorectal (odds ratio [OR] = 1.58, 95% CI 1.14, 2.18) and lung cancer (OR = 1.10, 95% CI 1.00, 1.22) associated with each 10-cm increase in genetically predicted height. No association was observed for prostate cancer (OR = 1.03, 95% CI 0.92, 1.15). Our meta-analysis was limited to published studies. The sample size for the Mendelian randomization analysis of colorectal cancer was relatively small, thus affecting the precision of the point estimate.ConclusionsOur study provides evidence for a potential causal association of adult height with the risk of colorectal and lung cancers and suggests that certain genetic factors and biological pathways affecting adult height may also affect the risk of these cancers.
Physical activity (PA) is associated with physiological responses thought to beneficially affect survival after breast cancer diagnosis, yet few studies have considered the entire survivorship experience. Effects of post-diagnosis activity on survival were examined in a cohort of 1,423 women diagnosed with in situ or invasive breast cancer in 1996–1997. Subjects were interviewed soon after diagnosis and again after approximately 5 years to assess breast cancer-related factors, including recreational PA before and after diagnosis. Date and cause of death through 2009 were determined from the National Death Index. Adjusted estimates were obtained using proportional hazards regression and a selection model to account for missing data. Survival was improved among women who were highly active after diagnosis (>9.0 MET h/week) compared to inactive women (0 MET h/week) for all-cause [hazard ratio (HR) (95 % credible interval): 0.33 (0.22, 0.48)] and breast cancer-specific mortality [HR: 0.27 (0.15, 0.46)]. The association of PA with overall mortality appeared stronger in the first 2 years after diagnosis [HR: 0.14 (0.03, 0.44)] compared to 2+ years since diagnosis [HR: 0.37 (0.25, 0.55)]. These findings show that postdiagnosis PA is associated with improved survival among women with breast cancer.
Background Conventional epidemiologic studies have evaluated associations between circulating lipid levels and breast cancer risk, but results have been inconsistent. As Mendelian randomization analyses may provide evidence for causal inference, we sought to evaluate potentially unbiased associations between breast cancer risk and four genetically predicted lipid traits. Methods Previous genome-wide association studies (GWAS) have identified 164 discrete variants associated with high density lipoprotein-cholesterol (HDL-C), low density lipoprotein-cholesterol (LDL-C), triglycerides and total cholesterol. We used 162 of these unique variants to construct weighted genetic scores (wGSs) for a total of 101 424 breast cancer cases and 80 253 controls of European ancestry from the Breast Cancer Association Consortium (BCAC). Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) for associations between per standard deviation increase in genetically predicted lipid traits and breast cancer risk. Additional Mendelian randomization analysis approaches and sensitivity analyses were conducted to assess pleiotropy and instrument validity. Results Corresponding to approximately 15 mg/dL, one standard deviation increase in genetically predicted HDL-C was associated with a 12% increased breast cancer risk (OR: 1.12, 95% CI: 1.08–1.16). Findings were consistent after adjustment for breast cancer risk factors and were robust in several sensitivity analyses. Associations with genetically predicted triglycerides and total cholesterol were inconsistent, and no association for genetically predicted LDL-C was observed. Conclusions This study provides strong evidence that circulating HDL-C may be associated with an increased risk of breast cancer, whereas LDL-C may not be related to breast cancer risk.
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