PDF - 22KB, Legends for supplementary figures 1-5.

PDF - 68KB, Association of height with risk of breast cancer by level of potential effect modifiers. HR4s are adjusted for covariates in footnote 3 in Table 3.

PDF - 68KB, Association of height with risk of colorectal cancer by level of potential effect modifiers. HR4s are adjusted for covariates in footnote 1 in Table 3.

PDF - 68KB, Association of height with risk of endometrial cancer by level of potential effect modifiers. HR4s are adjusted for covariates in footnote 4 in Table 3.

PDF - 69KB, Association of height with risk of melanoma cancer by level of potential effect modifiers. HR4s are adjusted for covariates in footnote 6 in Table 3.

PDF - 67KB, Association of height with risk of lung cancer in ever smokers by level of potential effect modifiers. HR4s are adjusted for covariates in footnote 6 in Table 3.

A recent meta-analysis of five case–control studies and one cohort study reported that exposure to glyphosate was associated with increased risk of non-Hodgkin’s lymphoma (NHL). The meta-analysis was based on estimates of risk from the included studies at the highest reported exposure level obtained from analyses with the longest lag period. The extent to which the summary estimate depends upon the exposure definitions and assumed latency period is uncertain. We carried out sensitivity analyses to determine how the definition of exposure and the choice of latency period affect the summary estimate from meta-analyses of the 6 studies included in the recent meta-analysis. We also conducted a meta-analysis of ever-exposure to glyphosate incorporating the most updated results from the case–control studies. The summary estimates of risk varied considerably depending on both the assumptions about exposure level and latency. Using the highest reported exposure levels, evidence of an association between glyphosate and NHL was strongest when estimates from analyses in the cohort study with a 20-year lag [RR = 1.41 (95% CI 1.13–1.76)] and a 15-year lag [RR = 1.25 (95% CI 1.01–1.25)] were included. In our meta-analysis of ever-exposure with no lag period, the summary relative risk with updated estimates was 1.05 (95% CI 0.87–1.28). The results of meta-analyses of glyphosate exposure and NHL risk depend on assumptions made about both exposure level and latency period. Our results for ever-exposure are consistent with those of two recent meta-analyses conducted using somewhat different study inclusion criteria.

Background: Estrogen metabolite concentrations of 2-hydroxyestrone (2-OHE1) and 16-hydroxyestrone (16-OHE1) may be associated with breast carcinogenesis. However, no study has investigated their possible impact on mortality after breast cancer. Methods: This population-based study was initiated in 1996-1997 with spot urine samples obtained shortly after diagnosis (mean = 96 days) from 683 women newly diagnosed with first primary breast cancer and 434 age-matched women without breast cancer. We measured urinary concentrations of 2-OHE1 and 16-OHE1 using an enzyme-linked immunoassay. Vital status was determined via the National Death Index (n = 244 deaths after a median of 17.7 years of follow-up). We used multivariable-adjusted Cox proportional hazards to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the estrogen metabolites-mortality association. We evaluated effect modification using likelihood ratio tests. All statistical tests were two-sided. Results: Urinary concentrations of the 2-OHE1 to 16-OHE1 ratio (>median of 1.8 vs <= median) were inversely associated with all-cause mortality (HR = 0.74, 95% CI = 0.56 to 0.98) among women with breast cancer. Reduced hazard was also observed for breast cancer mortality (HR = 0.73, 95% CI = 0.45 to 1.17) and cardiovascular diseases mortality (HR = 0.76, 95% CI = 0.47 to 1.23), although the 95% confidence intervals included the null. Similar findings were also observed for women without breast cancer. The association with all-cause mortality was more pronounced among breast cancer participants who began chemotherapy before urine collection (n = 118, HR = 0.42, 95% CI = 0.22 to 0.81) than among those who had not (n = 559, HR = 0.98, 95% CI = 0.72 to 1.34; P-interaction =.008). Conclusions: The urinary 2-OHE1 to 16-OHE1 ratio may be inversely associated with long-termall-cause mortality, which may depend on cancer treatment status at the time of urine collection.

AbstractMeta-analysis is a statistical technique for combining studies in order to obtain a larger sample size and produce a more stable estimate of an effect. But, like any technique, it can be well used or abused, says Geoffrey C. Kabat

BACKGROUND:Obesity is a strong risk factor for endometrial cancer, but it is unclear whether metabolic syndrome (MetS) contributes to endometrial cancer risk over and above the contribution of obesity.METHODS:We examined the association of MetS and its components with risk of endometrial cancer in a sub-cohort of 24,210 women enrolled in the Women's Health Initiative cohort study. Two variants of the National Cholesterol Education Program Adult Treatment Panel III definition of the MetS were used: one including and one excluding waist circumference (WC). Cox proportional hazards models were used to estimate the association of the study exposures with disease risk.RESULTS:When WC was included in the definition, MetS showed an approximately two-fold increase in endometrial cancer risk (HR 2.20; 95% CI 1.61-3.02); however, when WC was excluded, MetS was no longer associated with risk. We also observed that women with hyperglycemia, dyslipidemia and hypertension, in combination, had almost a twofold increased risk of endometrial cancer, independent of WC (HR 1.94; 95% CI 1.09, 3.46). Glucose, and, in particular, WC and body mass index were also positively associated with risk.CONCLUSIONS:Our findings suggest that MetS may predict risk of endometrial cancer independent of obesity among women with the remaining four Mets components.

Background: Estrogen metabolites play a role in breast cancer development. Previous studies have particularly focused on the two competing metabolism pathways which yield metabolites 2-hydroxyestrone (2-OHE1) and 16-hydroxyestrone (16-OHE1). 2-OHE1 has been shown to have antiestrogenic effects, but 16-OHE1has strong estrogenic and even genotoxic activity. No study has investigated their biologically plausible role in predicting prognosis/mortality among women diagnosed with breast cancer. Methods: In the Long Island Breast Study Project, spot urine samples were obtained from 687 women diagnosed with first primary breast cancer (shortly after diagnosis) in 1996-1997. Urinary concentrations of estrogen metabolites 2-OHE1 and 16-OHE1 were measured using enzyme linked immuno-assay. Vital status was determined by the National Death Index through December 31, 2014; 244 deaths (84 breast cancer-specific and 80 cardiovascular diseases-specific) were identified. We used multivariable-adjusted Cox proportional hazards regression model to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) for all-cause, breast cancer and cardiovascular diseases mortality as related to the two individual metabolites and their ratio (2-OHE1/16-OHE1). Multiplicative interactions with menopausal hormone therapy, body mass index, menopausal status, and breast cancer treatments were evaluated with likelihood ratio tests. Results: During a median follow-up of 18 years, urinary concentration of the 2-OHE1/16-OHE1 ratio (> median of 1.8 vs. ≤ median of 1.8) was associated with reduced risk of all-cause mortality (HR=0.74, 95% CI=0.56-0.98) among women with breast cancer. This inverse association with the 2-OHE1/16-OHE1 ratio was also observed for breast cancer mortality (HR=0.73, 95% CI=0.45-1.17) and cardiovascular diseases mortality (HR=0.76, 95% CI=0.47-1.23), although the 95%CIs included the null. The 2-OHE1/16-OHE1 ratio-mortality associations did not significantly differ by menopausal hormone therapy, body mass index, and menopausal status at the time of urine collection (Pinteration >0.05). Consistent patterns of association were not observed between the individual metabolites and mortality outcomes. Conclusion: To our knowledge, our study represents the first population-based epidemiologic evidence suggesting that the urinary concentration of the 2-OHE1/16-OHE1 ratio measured shortly after breast cancer diagnosis may be associated with improved overall mortality for breast cancer survivors. Future investigation is necessary to confirm our findings and to further understand the underlying biological mechanisms for estrogen metabolism–mortality relationships following breast cancer diagnosis. Citation Format: Tengteng Wang, Patrick B. Bradshaw, Sarah J. Nyante, Hazel B. Nichols, Patricia G. Moorman, Geoffrey C. Kabat, Susan L. Teitelbaum, Alfred I. Neugut, Marilie D. Gammon. Urinary estrogen metabolites and long-term all-cause and cause-specific mortality following breast cancer diagnosis: A population-based study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3294.

Obesity, which is commonly accompanied by dyslipidemia, is associated with an increased risk of certain cancers. However, the association of serum lipids with specific obesity-related cancers is unclear.

Purpose: The purpose of this study was to examine the association of type II diabetes and anthropometric variables with risk of pancreatic cancer among postmenopausal women. Methods: Weight, height, waist circumference, and hip circumference were measured by trained personnel, whereas history of diabetes and weight earlier in life were self-reported. Pancreatic cancer was ascertained via central review of medical records by physician adjudicators. After exclusions, 1045 cases of pancreatic cancer were diagnosed among 156,218 women over a median follow-up of approximately 18 years. Cox proportional hazards models were used to estimate the associations of study factors with pancreatic cancer risk. Results: Diabetes (hazards ratio (HR): 1.30; 95% confidence intervals (95% CI ): 1.01-1.66), and in particular, waist circumference, waist-to-hip ratio, and waist-to-height ratio showed positive associations with pancreatic cancer risk (HRs for highest vs. lowest level 1.38; 95% CI: 1.14-1.66, 1.40; 1.17-1.68; and 1.36; 1.13-1.64, respectively). Body mass index at the baseline showed only a borderline positive association with risk (HR: 1.21; 95% CI: 0.97-1.51). Body mass index at age 50 years, but not at ages 18 and 35 years, was also associated with increased pancreatic cancer risk. Conclusions: In this study of postmenopausal women, central adiposity and, to a lesser extent, general adiposity and a history of diabetes, were associated with increased pancreatic cancer risk. (C) 2018 Elsevier Inc. All rights reserved.

Obesity has been postulated to increase the risk of colorectal cancer by mechanisms involving insulin resistance and the metabolic syndrome. We examined the associations of body mass index (BMI), waist circumference, the metabolic syndrome, metabolic obesity phenotypes and homeostasis model‐insulin resistance (HOMA‐IR—a marker of insulin resistance) with risk of colorectal cancer in over 21,000 women in the Women's Health Initiative CVD Biomarkers subcohort. Women were cross‐classified by BMI (18.5–<25.0, 25.0–<30.0 and ≥30.0 kg/m2) and presence of the metabolic syndrome into 6 phenotypes: metabolically healthy normal weight (MHNW), metabolically unhealthy normal weight (MUNW), metabolically healthy overweight (MHOW), metabolically unhealthy overweight (MUOW), metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO). Neither BMI nor presence of the metabolic syndrome was associated with risk of colorectal cancer, whereas waist circumference showed a robust positive association. Relative to the MHNW phenotype, the MUNW phenotype was associated with increased risk, whereas no other phenotype showed an association. Furthermore, HOMA‐IR was not associated with increased risk. Overall, our results do not support a direct role of metabolic dysregulation in the development of colorectal cancer; however, they do suggest that higher waist circumference is a risk factor, possibly reflecting the effects of increased levels of cytokines and hormones in visceral abdominal fat on colorectal carcinogenesis.

BACKGROUND:Little is known about risk factors for adult glioma. Adiposity has received some attention as a possible risk factor. METHODS:We examined the association of body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR), measured at enrollment, as well as self-reported weight earlier in life, with risk of glioma in a large cohort of postmenopausal women. Over 18 years of follow-up, 217 glioma cases were ascertained, including 164 glioblastomas. Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals. RESULTS:There was a modest, non-significant trend toward increasing risk of glioma and glioblastoma with increasing measured BMI and WHR. No trend was seen for WC. Self-reported BMI earlier in life showed no association with risk. CONCLUSIONS:Our weak findings regarding the association of adiposity measures with risk of glioma are in agreement the results of several large cohort studies. In view of the available evidence, adiposity is unlikely to represent an important risk factor for glioma.

Background/Objective: Many studies have shown a U-shaped association of sleep duration with mortality; however, this association is difficult to interpret owing to possible reverse causation, residual confounding, and measurement issues. We used data from the Women's Health Initiative to examine the associations of sleep duration, insomnia, and use of sleep aids with death from cardiovascular disease (CVD), cancer, "other" causes, and all causes combined. Methods: Cox proportional hazards models were used in the analysis of baseline data and in time-dependent analyses of repeated measures to estimate associations of sleep-related factors with mortality. Among 158,203 women with information regarding sleep, 30,400 total deaths, 8857 CVD deaths, 9284 cancer deaths, and 11,928 other deaths were ascertained over a median of 17.8 years. Results: In both baseline and time-dependent analyses, both short (<= 5 h) and long sleep (>= 9 h) durations were associated with increased risk of total, CVD, and "other" deaths, but not with cancer deaths. Insomnia showed no association with mortality, whereas use of sleep medications was associated with an increased mortality risk. Conclusions: While our findings showed a small but robust association of sleep duration with mortality in postmenopausal women, studies including objective measurements of sleep quality and efficiency are needed to clarify these associations. (C) 2018 Elsevier B.V. All rights reserved.

Limited evidence suggests that hyperinsulinemia may contribute to the risk of breast, endometrial, and, possibly, ovarian cancer. The aim of this study was to assess the association of serum glucose and insulin with risk of these cancers in postmenopausal women, while taking into account potential confounding and modifying factors. We studied 21103 women with fasting baseline insulin and glucose measurements in a subsample of the Women's Health Initiative. The subsample was composed of four studies within Women's Health Initiative with different selection and sampling strategies. Over a mean of 14.7 years of follow-up, 1185 breast cancer cases, 156 endometrial cancer cases, and 130 ovarian cancer cases were diagnosed. We used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) by quartile of glucose or insulin. Serum insulin was positively associated with breast cancer risk (multivariable-adjusted HR for highest vs. lowest quartile 1.41, 95% CI: 1.16-1.72, P-trend<0.0003), and glucose and insulin were associated with roughly a doubling of endometrial cancer risk (for glucose: HR: 2.00, 95% CI: 1.203.35, P-trend=0.01; for insulin: HR: 2.39, 95% CI: 1.32-4.33, P-trend=0.008). These associations remained unchanged or were slightly attenuated after mutual adjustment, adjustment for serum lipids, and assessment of possible reverse causation. Glucose and insulin showed no association with ovarian cancer. Our findings provide support for a role of insulin-related pathways in the etiology of cancers of the breast and endometrium. However, because of the unrepresentative nature of the sample, our results need confirmation in other populations. Copyright (c) 2018 Wolters Kluwer Health, Inc. All rights reserved.

Obesity is a chronic inflammatory condition strongly associated with the risk of numerous cancers. We examined the association between circulating high-sensitivity C-reactive protein (hsCRP), a biomarker of inflammation and strong correlate of obesity, and the risk of three understudied obesity-related cancers in postmenopausal women: ovarian cancer, kidney cancer, and multiple myeloma.

Do cell phones cause brain cancer? Does BPA threaten our health? How safe are certain dietary supplements, especially those containing exotic herbs or small amounts of toxic substances? Is the HPV vaccine safe? We depend on science and medicine as never before, yet there is widespread misinformation and confusion, amplified by the media, regarding what influences our health. In Getting Risk Right, Geoffrey C. Kabat shows how science works—and sometimes doesn't—and what separates these two very different outcomes. Kabat seeks to help us distinguish between claims that are supported by solid science and those that are the result of poorly designed or misinterpreted studies. By exploring different examples, he explains why certain risks are worth worrying about, while others are not. He emphasizes the variable quality of research in contested areas of health risks, as well as the professional, political, and methodological factors that can distort the research process. Drawing on recent systematic critiques of biomedical research and on insights from behavioral psychology, Getting Risk Right examines factors both internal and external to the science that can influence what results get attention and how questionable results can be used to support a particular narrative concerning an alleged public health threat. In this book, Kabat provides a much-needed antidote to what has been called “an epidemic of false claims.”

Purpose: We used data from the Women's Health Initiative to examine the association of platelet count with total mortality, coronary heart disease (CHD) mortality, cancer mortality, and non-CHD/noncancer mortality.Methods: Platelet count was measured at baseline in 159,746 postmenopausal women and again in year 3 in 75,339 participants. Participants were followed for a median of 15.9 years. Cox proportional hazards models were used to estimate the relative mortality hazards associated with deciles of baseline platelet count and of the mean of baseline + year 3 platelet count.Results: Low and high deciles of both baseline and mean platelet count were positively associated with total mortality, CHD mortality, cancer mortality, and non-CHD/noncancer mortality. The association was robust and was not affected by adjustment for a number of potential confounding factors, exclusion of women with comorbidity, or allowance for reverse causality. Low-and high-platelet counts were associated with all four outcomes in never smokers, former smokers, and current smokers.Conclusions: In this large study of postmenopausal women, both low-and high-platelet counts were associated with total and cause-specific mortality. (C) 2017 Elsevier Inc. All rights reserved.