Shear wave elastography: usefulness in chronic kidney disease.

Purpose: Chronic kidney disease (CKD) is recognized as a major worldwide health problem. For all CKD, intra-renal fibrosis is a final common pathway that can be correlated with disease severity. Tissue stiffness can be measured non-invasively using shear wave elastography. This study evaluates the use of Young's modulus derived by SWE as a biomarker that can distinguish normal from diseased kidneys. Also, Young's modulus was correlated with Doppler findings and estimated glomerular filtration rate (eGFR). Material and methods: This prospective study was performed in 2 phases, in which initially 50 CKD patients and 50 controls were studied to arrive at a median Young's modulus value in both the groups. In the later phase, a cross-sectional comparative study was conducted on 58 diabetic and 56 non-diabetic patients with SWE and renal Doppler, and the findings were correlated in various stages of CKD. Results: Using Young's modulus, the renal cortex elasticity of CKD patients was shown to be considerably reduced as compared to normal kidneys. There was significant correlation between Young's modulus, eGFR, and renal resistive index. Young's modulus values did not show significant differences between diabetic and non-diabetic groups, revealing its inability to arrive at the aetiopathogenesis of CKD. Conclusions: Correlation of renal tissue Young's modulus with eGFR suggests that SWE may be used as an indicator of renal tissue injuries in CKD patients. SWE can never replace the gold standard biopsy, but it can be used for staging of CKD. Even though SWE cannot predict the aetiopathogenesis of CKD, it may be a low-cost way to provide additional diagnostic information in CKD.

Predicting interval and screen-detected breast cancers from mammographic density defined by different brightness thresholds.

BACKGROUND: Case-control studies show that mammographic density is a better risk factor when defined at higher than conventional pixel-brightness thresholds. We asked if this applied to interval and/or screen-detected cancers. METHOD: We conducted a nested case-control study within the prospective Melbourne Collaborative Cohort Study including 168 women with interval and 422 with screen-detected breast cancers, and 498 and 1197 matched controls, respectively. We measured absolute and percent mammographic density using the Cumulus software at the conventional threshold (Cumulus) and two increasingly higher thresholds (Altocumulus and Cirrocumulus, respectively). Measures were transformed and adjusted for age and body mass index (BMI). Using conditional logistic regression and adjusting for BMI by age at mammogram, we estimated risk discrimination by the odds ratio per adjusted standard deviation (OPERA), calculated the area under the receiver operating characteristic curve (AUC) and compared nested models using the likelihood ratio criterion and models with the same number of parameters using the difference in Bayesian information criterion (ΔBIC). RESULTS: For interval cancer, there was very strong evidence that the association was best predicted by Cumulus as a percentage (OPERA = 2.33 (95% confidence interval (CI) 1.85-2.92); all ΔBIC > 14), and the association with BMI was independent of age at mammogram. After adjusting for percent Cumulus, no other measure was associated with risk (all P > 0.1). For screen-detected cancer, however, the associations were strongest for the absolute and percent Cirrocumulus measures (all ΔBIC > 6), and after adjusting for Cirrocumulus, no other measure was associated with risk (all P > 0.07). CONCLUSION: The amount of brighter areas is the best mammogram-based measure of screen-detected breast cancer risk, while the percentage of the breast covered by white or bright areas is the best mammogram-based measure of interval breast cancer risk, irrespective of BMI. Therefore, there are different features of mammographic images that give clinically important information about different outcomes.

Mammographic density and risk of breast cancer by tumor characteristics: a case-control study.

BACKGROUND: In a previous paper, we had assumed that the risk of screen-detected breast cancer mostly reflects inherent risk, and the risk of whether a breast cancer is interval versus screen-detected mostly reflects risk of masking. We found that inherent risk was predicted by body mass index (BMI) and dense area (DA) or percent dense area (PDA), but not by non-dense area (NDA). Masking, however, was best predicted by PDA but not BMI. In this study, we aimed to investigate if these associations vary by tumor characteristics and mode of detection. METHODS: We conducted a case-control study nested within the Melbourne Collaborative Cohort Study of 244 screen-detected cases matched to 700 controls and 148 interval cases matched to 446 controls. DA, NDA and PDA were measured using the Cumulus software. Tumor characteristics included size, grade, lymph node involvement, and ER, PR, and HER2 status. Conditional and unconditional logistic regression were applied as appropriate to estimate the Odds per Adjusted Standard Deviation (OPERA) adjusted for age and BMI, allowing the association with BMI to be a function of age at diagnosis. RESULTS: For screen-detected cancer, both DA and PDA were associated to an increased risk of tumors of large size (OPERA ~ 1.6) and positive lymph node involvement (OPERA ~ 1.8); no association was observed for BMI and NDA. For risk of interval versus screen-detected breast cancer, the association with risk for any of the three mammographic measures did not vary by tumor characteristics; an association was observed for BMI for positive lymph nodes (OPERA ~ 0.6). No associations were observed for tumor grade and ER, PR and HER2 status of tumor. CONCLUSIONS: Both DA and PDA were predictors of inherent risk of larger breast tumors and positive nodal status, whereas for each of the three mammographic density measures the association with risk of masking did not vary by tumor characteristics. This might raise the hypothesis that the risk of breast tumours with poorer prognosis, such as larger and node positive tumours, is intrinsically associated with increased mammographic density and not through delay of diagnosis due to masking.

Mammographic density and risk of breast cancer by mode of detection and tumor size: a case-control study.

BACKGROUND: Risk of screen-detected breast cancer mostly reflects inherent risk, while risk of interval cancer reflects inherent risk and risk of masking (risk of the tumor not being detected due to increased dense tissue). Therefore the predictors of whether a breast cancer is interval or screen-detected include those that predict masking. Our aim was to investigate the associations between mammographic measures and (1) inherent risk, and (2) masking. METHODS: We conducted a case-control study nested within the Melbourne collaborative cohort study of 244 screen-detected cases (192 small tumors (<2 cm)) matched to 700 controls and 148 interval cases (76 small tumors) matched to 446 controls. Dense area (DA), percent dense area (PDA), and non-dense area (NDA) were measured using the Cumulus software. Conditional and unconditional logistic regression were applied as appropriate to estimate the odds per adjusted standard deviation (OPERA) adjusted for age and body mass index (BMI), allowing for the association with BMI to be a function of age at diagnosis. Tests of fit were performed using the Bayesian information criterion (BIC) and the area under the receiver operating characteristic curve. RESULTS: For screen-detected cancer, the association with BMI had a marginally significant dependence on age at diagnosis, and after adjustment both DA and PDA were associated with risk (OPERA approximately 1.2) and gave a similar fit. NDA was not associated with risk. For interval cancer, the BMI risk association was not dependent on age at diagnosis and the best fitting model was PDA alone (OPERA = 2.24, 95 % confidence interval 1.75, 2.86). Prediction of interval versus screen-detected cancer was best achieved by PDA alone (OPERA = 1.76, 95 % confidence interval 1.39, 2.22) with no association with BMI. When the analysis was restricted to small tumors to reduce the influence of tumor growth, we obtained similar results. CONCLUSIONS: Inherent breast cancer risk is predicted by BMI and DA or PDA, but not NDA. Masking is predicted by PDA, and not by BMI. Understanding risk and masking could help tailor mammographic screening.

Associations of mammographic dense and nondense areas and body mass index with risk of breast cancer.

Mammographic density measurements are associated with risk of breast cancer. Few studies have investigated the concurrent associations of mammographic dense and nondense areas, body mass index (weight (kg)/height (m)(2)), and ages at mammogram and diagnosis with breast cancer risk. We conducted a matched, case-control study nested within the Melbourne Collaborative Cohort Study (cohort recruitment in 1990-1994 and follow-up until 2007) to estimate the associations between these factors and breast cancer risk under alternative causal models. Mammographic dense area was positively associated with risk, and the strength of this association was only slightly influenced by the choice of the causal model (relative risk per 1 standard deviation = 1.50, 95% confidence interval: 1.32, 1.70). Mammographic nondense area was inversely associated with risk under the assumption that fat in the body and fat in the breast cause breast cancer through independent mechanisms (relative risk per 1 standard deviation = 0.75, 95% confidence interval: 0.65, 0.86), whereas it was not associated with risk under the assumption that they are both proxies of adiposity. Knowledge about the biological mechanisms regulating the role played by mammographic nondense area and body fat on breast cancer risk is essential to better estimate their impacts on individual risk.

Pregnancy in a woman with congenital adrenal hyperplasia with 11-beta-hydroxylase deficiency: A case report.

Background: Successful pregnancy with congenital adrenal hyperplasia due to 11-beta-hydroxylase deficiency is an extremely rare condition. Only two cases have been reported in the literature. Methods and results: Described here is a 30-year-old woman diagnosed as a neonate with congenital adrenal hyperplasia related to 11-beta-hydroxylase deficiency classic type, who subsequently underwent clitoral resection and vaginoplasty. She was started on lifelong steroid therapy after surgery. She developed hypertension at 11 years of age and was on antihypertensive therapy from then on. In later life, she underwent division of vaginal scar tissue and perineal refashioning. She spontaneously conceived but her pregnancy was complicated by severe pre-eclampsia and delivery was required at 33 weeks of gestation by cesarean section. A healthy male infant was delivered. Conclusion: Management of these women is similar to those with more common causes of congenital adrenal hyperplasia, with careful monitoring throughout pregnancy for complications such as gestational diabetes, gestational hypertension, and intrauterine growth restriction.

Quantitative Assessment of Prewriting Skills in Children: The Development and Validation of a Tablet Assessment Tool.

Our purpose in this study was to determine the feasibility of assessing children's prewriting with a new tablet tool, the Quantitative Assessment of Prewriting Skills (QAPS), while determining the validity of the QAPS for identifying visual motor skill differences. We recruited 10 children who were receiving occupational therapy (OT) services for visual motor deficits from a local OT clinic and 10 age-matched typically developing (TD) children from the local community. The QAPS assesses the accuracy of copying patterns on a tablet that records the child's finger position on the tablet, and the data are then analyzed for different dimensions of pattern copying. We found a large effect size difference in the QAPS total score between our two participant groups, with the OT group showing poorer performance than TD children; and, among nine assessment dimensions, roundness of a drawn circle showed the largest effect size difference between groups. The QAPS appears to be a promising tool for assessing visual motor skills, and it warrants additional testing in larger participant samples.

Co-substrate-mediated utilization of high concentration of phenol by Aspergillus niger FP7 and reduction of its phytotoxicity on Vigna radiata L.

Phenol and its derivatives behave as mutagens, teratogens and carcinogens inducing adverse physiological effects and are considered environmental hazards. The present study focuses on high concentration phenol utilization by Aspergillus niger FP7 under various physicochemical parameters. The soil remediation potential of the culture for reducing phenol toxicity against Vigna radiata L. seed germination was also evaluated along with the extent of phenol utilization using high-performance liquid chromatography. Aspergillus niger FP7 showed phenol tolerance up to 1000 mg/l, beyond which there was a sharp reduction in phenol utilization. Supplementation of the mineral salt medium with glucose and peptone and application of a 100 rpm agitation rate enhanced phenol utilization (up to 88.3%). Phenol utilization efficiency decreased (up to 29.6%) when cadmium and mercury salts were present, but the same improved (59.4-75.5%) by the incorporation of cobalt, copper and zinc salts. Vigna radiata L. seeds sown in the non-augmented soil revealed a 3.27% germination index, and with fungal augmentation, the germination index improved (97.3%). The non-augmented soil demonstrated 3.1% phenol utilization, while for the augmented soil, the utilization was 79.3%. Based on the phytotoxicity study and chromatographic analysis, it could be inferred that Aspergillus niger FP7 significantly enhanced phenol utilization in soil. In the future, Aspergillus niger FP7 could be of potential use in bioremediation of sites polluted with high concentrations of phenol.

Physical activity, body size and composition, and risk of ovarian cancer.

OBJECTIVES: We examined the association between risk of ovarian cancer and physical activity and anthropometry (body mass index, height, waist, fat, and fat-free mass) in the Melbourne Collaborative Cohort Study. METHODS: This prospective cohort study included 18,700 women aged 26-76 years old at recruitment between 1990 and 1994. Participants were interviewed about their physical activity, including frequency and intensity. Body measurements were taken directly; fat mass and fat-free mass were calculated from bioelectrical impedance analysis. During an average of 10.2 years of follow-up, 113 ovarian cancers were ascertained. Cox regression was used to estimate hazard ratios. RESULTS: After adjusting for potential confounders, compared with no physical activity, the hazard ratios for levels of total physical activity were 1.56 (95% CI: 0.81, 3.00) for low level, 1.92 (1.07, 3.45) for medium level, and 2.21 (1.16, 4.24) for high level (test for trend, p = 0.01). The hazard ratio for ovarian cancer in relation to BMI was 1.22 (95% CI: 1.00, 1.48; p-trend, 0.06) per 5 kg/m(2) increment, and for fat mass, 1.23 (95% CI: 1.01, 1.49; p-trend, 0.04) per 10 kg increment. CONCLUSIONS: This study found some evidence for a possible relationship between higher levels of physical activity and body size and increased ovarian cancer risk.

Circulating steroid hormone concentrations in postmenopausal women in relation to body size and composition.

Steroid hormones are associated with the risk of postmenopausal breast cancer and evidence suggests that increased concentrations of oestrogens from peripheral aromatisation in adipose tissue partly explains the association between body mass index (BMI) and risk of postmenopausal breast cancer. This study examined the associations between circulating concentrations of steroid hormones and anthropometric measurements in a sample of naturally postmenopausal women from the Melbourne Collaborative Cohort Study, not using hormone replacement therapy. We measured plasma concentration of total oestradiol, oestrone sulphate, dehydroepiandrosterone sulphate, androstenedione, testosterone and sex hormone binding globulin (SHBG) and calculated concentration of free oestradiol. Body measurements included height, weight, BMI, waist circumference, fat mass and fat-free mass, the last two estimated by bioelectrical impedance analysis. BMI was positively associated with both oestrogens and androgens and negatively with SHBG. Fat mass was the principal measure responsible for the association observed between body size and total oestradiol. The associations between oestrone sulphate and androgens and body size were mainly with waist circumference. The associations between oestrogens and body size were close to null for the first 6 years since menopause and became positive thereafter. Our results are compatible with the hypothesis that after the menopause excess fat mass increases oestrogen concentrations through the peripheral aromatisation of androgens in adipose tissue. This effect requires around 6 years to be detectable by way of circulating steroid hormone levels.

Longitudinal Study of Mammographic Density Measures That Predict Breast Cancer Risk.

Background: After adjusting for age and body mass index (BMI), mammographic measures-dense area (DA), percent dense area (PDA), and nondense area (NDA)-are associated with breast cancer risk. Our aim was to use longitudinal data to estimate the extent to which these risk-predicting measures track over time.Methods: We collected 4,320 mammograms (age range, 24-83 years) from 970 women in the Melbourne Collaborative Cohort Study and the Australian Breast Cancer Family Registry. Women had on average 4.5 mammograms (range, 1-14). DA, PDA, and NDA were measured using the Cumulus software and normalized using the Box-Cox method. Correlations in the normalized risk-predicting measures over time intervals of different lengths were estimated using nonlinear mixed-effects modeling of Gompertz curves.Results: Mean normalized DA and PDA were constant with age to the early 40s, decreased over the next two decades, and were almost constant from the mid-60s onward. Mean normalized NDA increased nonlinearly with age. After adjusting for age and BMI, the within-woman correlation estimates for normalized DA were 0.94, 0.93, 0.91, 0.91, and 0.91 for mammograms taken 2, 4, 6, 8, and 10 years apart, respectively. Similar correlations were estimated for the age- and BMI-adjusted normalized PDA and NDA.Conclusions: The mammographic measures that predict breast cancer risk are highly correlated over time.Impact: This has implications for etiologic research and clinical management whereby women at increased risk could be identified at a young age (e.g., early 40s or even younger) and recommended appropriate screening and prevention strategies. Cancer Epidemiol Biomarkers Prev; 26(4); 651-60. ©2017 AACR.

Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures.

Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10(-5)). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk.

Role of Ca2+ in induction of neurotransmitter-related gene expression by butyrate.

We examined the effect of butyrate on neurotransmitter-related gene expression and calcium homeostasis in PC12 cells. Pretreatment with Ca2+ chelators (EGTA or BAPTA-AM) attenuated the butyrate-triggered accumulation of TH and ppEnk mRNA indicating that Ca2+ plays a role in butyrate-induced regulation of neuronal genes. Butyrate alone did not alter intracellular Ca2+ levels as determined by Fura-PE3 fluorescence; however, pretreatment with butyrate (18-24 h) reduced the first Ca2+ peak and prevented the second sustained rise in [Ca2+]i as induced by nicotine or ryanodine. In contrast, butyrate had no effect on Ca2+ transients when added shortly before or during nicotine or ryanodine stimulation. These results suggest that chronic butyrate exposure can modulate cell responses by affecting intracellular Ca2+ signaling.

Mammographic density phenotypes and risk of breast cancer: a meta-analysis.

BACKGROUND: Fibroglandular breast tissue appears dense on mammogram, whereas fat appears nondense. It is unclear whether absolute or percentage dense area more strongly predicts breast cancer risk and whether absolute nondense area is independently associated with risk. METHODS: We conducted a meta-analysis of 13 case-control studies providing results from logistic regressions for associations between one standard deviation (SD) increments in mammographic density phenotypes and breast cancer risk. We used random-effects models to calculate pooled odds ratios and 95% confidence intervals (CIs). All tests were two-sided with P less than .05 considered to be statistically significant. RESULTS: Among premenopausal women (n = 1776 case patients; n = 2834 control subjects), summary odds ratios were 1.37 (95% CI = 1.29 to 1.47) for absolute dense area, 0.78 (95% CI = 0.71 to 0.86) for absolute nondense area, and 1.52 (95% CI = 1.39 to 1.66) for percentage dense area when pooling estimates adjusted for age, body mass index, and parity. Corresponding odds ratios among postmenopausal women (n = 6643 case patients; n = 11187 control subjects) were 1.38 (95% CI = 1.31 to 1.44), 0.79 (95% CI = 0.73 to 0.85), and 1.53 (95% CI = 1.44 to 1.64). After additional adjustment for absolute dense area, associations between absolute nondense area and breast cancer became attenuated or null in several studies and summary odds ratios became 0.82 (95% CI = 0.71 to 0.94; P heterogeneity = .02) for premenopausal and 0.85 (95% CI = 0.75 to 0.96; P heterogeneity < .01) for postmenopausal women. CONCLUSIONS: The results suggest that percentage dense area is a stronger breast cancer risk factor than absolute dense area. Absolute nondense area was inversely associated with breast cancer risk, but it is unclear whether the association is independent of absolute dense area.

Associations between weight in early adulthood, change in weight, and breast cancer risk in postmenopausal women.

BACKGROUND: Adult weight is positively associated with postmenopausal breast cancer but few studies have investigated whether there are associations with weight and body mass index (BMI) in early adulthood, or subsequent weight change. METHODS: A total of 14,441 postmenopausal women from the Melbourne Collaborative Cohort Study (MCCS) were followed for 16.5 years (mean) and 668 incident breast cancers were identified. Hazard ratios (HRs) were estimated using Cox regression. RESULTS: Weight and BMI at 18 to 21 years were not associated with risk of any type of breast cancer and there was no variation by age. Women with the greatest increase in weight and BMI had higher risk at older ages [HR per 5 kg/m(2) gain in BMI = 1.24; 95% confidence interval (CI), 1.11-1.40], although the test for homogeneity by age was not significant. At older ages, the association was stronger for progesterone (PR) positive disease compared with PR negative disease (HR per 5 kg/m(2) gain in BMI, 1.43; 95% CI, 1.23-1.66; test for homogeneity by PR status, P < 0.01) and for diseases that were positive for both estrogen (ER) and PR (HR per 5 kg/m(2) gain in BMI, 1.45; 95% CI, 1.24-1.69; test for homogeneity by ER/PR status, P = 0.02). HRs were also greater for HER2- and luminal A tumors, but the P values for homogeneity by tumor subgroups were not significant. CONCLUSION: Early adulthood weight is not associated with risk of postmenopausal breast cancer. Greater weight gain during adulthood might be associated with increased risk for older women (>69 years) and this association might vary by tumor hormone receptor status. IMPACT: Further studies need to investigate the impact of increase in weight during adulthood on postmenopausal breast cancer risk and the potential variation by age or tumor characteristics.

Common breast cancer susceptibility variants in LSP1 and RAD51L1 are associated with mammographic density measures that predict breast cancer risk.

BACKGROUND: Mammographic density adjusted for age and body mass index (BMI) is a heritable marker of breast cancer susceptibility. Little is known about the biologic mechanisms underlying the association between mammographic density and breast cancer risk. We examined whether common low-penetrance breast cancer susceptibility variants contribute to interindividual differences in mammographic density measures. METHODS: We established an international consortium (DENSNP) of 19 studies from 10 countries, comprising 16,895 Caucasian women, to conduct a pooled cross-sectional analysis of common breast cancer susceptibility variants in 14 independent loci and mammographic density measures. Dense and nondense areas, and percent density, were measured using interactive-thresholding techniques. Mixed linear models were used to assess the association between genetic variants and the square roots of mammographic density measures adjusted for study, age, case status, BMI, and menopausal status. RESULTS: Consistent with their breast cancer associations, the C-allele of rs3817198 in LSP1 was positively associated with both adjusted dense area (P = 0.00005) and adjusted percent density (P = 0.001), whereas the A-allele of rs10483813 in RAD51L1 was inversely associated with adjusted percent density (P = 0.003), but not with adjusted dense area (P = 0.07). CONCLUSION: We identified two common breast cancer susceptibility variants associated with mammographic measures of radiodense tissue in the breast gland. IMPACT: We examined the association of 14 established breast cancer susceptibility loci with mammographic density phenotypes within a large genetic consortium and identified two breast cancer susceptibility variants, LSP1-rs3817198 and RAD51L1-rs10483813, associated with mammographic measures and in the same direction as the breast cancer association.

Body size, weight change, and risk of colon cancer.

BACKGROUND: Epidemiologic studies have consistently reported positive associations between obesity and colon cancer risk for men, but the evidence is less consistent for women. Few studies have investigated effects of weight change on colon cancer risk. METHODS: Using the Melbourne Collaborative Cohort Study, which recruited men and women mostly in 40 to 69 years of age, we investigated associations between weight and body mass index (BMI) at age 18 years and at study entry and weight change since age 18 years and colon cancer. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using Cox regression. RESULTS: During follow-up of 16,188 men and 23,438 women for 14 years on average, we ascertained 569 incident colon cancers. Weight and BMI at study entry were positively associated with colon cancer risk for men [HR, 1.12 (95% CI, 1.04-1.21) per 5-kg increment; HR, 1.39 (95% CI, 1.12-1.71) per 5 kg/m(2)], but not women. Risk of colon cancer was not associated with weight or BMI at age 18 years. Adult weight change was positively associated with colon cancer risk for men (HR, 1.11 per 5-kg increment; 95% CI, 1.03-1.20), but not women (HR, 1.00; 95% CI, 0.94-1.07). Men who gained ≥20 kg from age 18 had an increased risk of colon cancer compared with men whose weight was stable (HR, 1.47; 95% CI, 0.94-2.31). CONCLUSION: Weight gain during adult life increases men's risk of colon cancer. IMPACT: Avoiding excessive weight gain might help reduce colon cancer risk for men.

Circulating steroid hormone levels and risk of breast cancer for postmenopausal women.

Epidemiologic studies have consistently reported that endogenous steroid hormone levels are associated with postmenopausal breast cancer risk, but little is known on the associations by tumor grade, hormone receptor status, or age at diagnosis. We performed a case-cohort study of naturally postmenopausal women within the Melbourne Collaborative Cohort Study that included a random sample of 857 women and 197 breast cancer cases diagnosed during a mean of 9.2 years of follow-up. Concentrations of total estradiol, estrone sulfate, testosterone, DHEA sulfate, androstenedione, and sex hormone binding globulin were measured in plasma collected at baseline before diagnosis; free estradiol plasma concentration was calculated. Cox regression was used to estimate associations adjusted for known and potential confounders. The HR for breast cancer comparing fourth and first quartiles was 1.44 [95% confidence interval (95% CI), 0.89-2.35] for total estradiol, 1.75 (95% CI, 1.06, 2.89) for free estradiol, 2.05 (95% CI, 1.24-3.37) for estrone sulfate, 1.25 (95% CI, 0.78-2.01) for testosterone, 1.41 (95% CI, 0.88-2.27) for DHEA sulfate, 1.49 (95% CI, 0.91-2.44) for androstenedione, and 0.33 (95% CI, 0.19-0.55) for sex hormone binding globulin. These associations did not differ by tumor grade and estrogen receptor/progesterone receptor status (all test for heterogeneity, P > 0.05). Risks associated with estrogen and androgen levels were stronger at older ages (test for interaction across age groups, P = 0.59 for total estradiol and P = 0.01 for testosterone). Our prospective study confirms earlier findings and suggests that the associations of endogenous hormones with postmenopausal breast cancer risk are independent of tumor grade, and hormone receptor status and might increase in strength with age.

Dietary patterns and prostate cancer risk.

Recent studies report that certain dietary patterns, especially those high in red and processed meats, are associated with prostate cancer risk. We prospectively investigated associations between empirically derived dietary patterns and prostate cancer risk using the Melbourne Collaborative Cohort Study. We followed 14,627 men of ages 34 to 75 years for an average of 13.6 years, and identified 1,018 incident prostate cancers. Factor analysis of the 121-item food frequency questionnaire identified four factors with eigenvalues >2 that explained 67% of the total variance. Using Cox proportional hazard models, we found no association between any dietary pattern and prostate cancer risk overall (all P(trend) >or= 0.2). The hazard ratios for quartiles of the dietary pattern scores ranged from 0.87 to 1.14 and all 95% confidence intervals included 1. The analyses by aggressiveness, Gleason score groups, and age at diagnosis did not show any association (all P(trend) > 0.07).