Anthropometric factors and ovarian cancer risk: a systematic review and nonlinear dose-response meta-analysis of prospective studies

Calcium Intake and the Risk of Ovarian Cancer: A Meta-Analysis

Several epidemiological studies have evaluated the association between calcium intake and the risk of ovarian cancer. However, the results of these studies remain controversial. Thus, we performed a meta-analysis to explore the association between calcium intake and the risk of ovarian cancer. Pubmed, Embase and Web of Science were searched for eligible publications up to April 2017. Pooled relative risks (RRs) with 95% confidence intervals (CIs) were calculated using the random-effects model. Small-study effect was estimated using Egger's test and the funnel plot. Among 15 epidemiological studies involving 493,415 participants and 7453 cases eligible for this meta-analysis, 13 studies were about dietary calcium intake, 4 studies about dairy calcium intake and 7 studies about dietary plus supplemental calcium intake. When comparing the highest with the lowest intake, the pooled RRs of ovarian cancer were 0.80 (95% CI 0.72-0.89) for dietary calcium, 0.80 (95% CI 0.66-0.98) for dairy calcium and 0.90 (95% CI 0.65-1.24) for dietary plus supplemental calcium, respectively. Dietary calcium was significantly associated with a reduced risk of ovarian cancer among cohort studies (RR = 0.86, 95% CI 0.74-0.99) and among case-control studies (RR = 0.75, 95% CI 0.64-0.89). In subgroup analysis by ovarian cancer subtypes, we found a statistically significant association between the dietary calcium (RR = 0.78, 95% CI 0.69-0.88) and the risk of epithelial ovarian cancer (EOC). This meta-analysis indicated that increased calcium intake might be inversely associated with the risk of ovarian cancer; this still needs to be confirmed by larger prospective cohort studies.

Obesity and Ovarian Cancer

Ovarian cancer is the most fatal gynecologic cancer and is an important source of cancer-related mortality, particularly in developed countries. Despite substantial research examining adiposity (primarily adult body mass index [BMI]), the overall evidence suggests only a weak positive association between adiposity and risk of ovarian cancer, with stronger associations observed for population-based case-control studies compared to prospective studies. Ovarian cancer is not one disease and emerging data suggest that higher BMI may only be associated with risk of certain histologic subtypes, including low-grade serous and invasive mucinous tumors. Interestingly, some larger studies and meta-analyses have reported a stronger relationship with premenopausal ovarian cancers, which are more likely to be of these subtypes. Relatively few studies have conducted detailed examinations of other adiposity-related factors such as measures of abdominal adiposity, early-life body size and weight change. While the underlying mechanisms that may relate adiposity to risk are unclear, increased inflammatory biomarkers have been associated with risk and hormonal factors, including androgen levels, may be important for the development of mucinous tumors. Future research should leverage the large sample sizes of consortia to evaluate associations by key tumor characteristics as well as consider patterns of weight change over the life course with both ovarian cancer risk and survival.

Comparison of general obesity and measures of body fat distribution in older adults in relation to cancer risk: meta-analysis of individual participant data of seven prospective cohorts in Europe

BACKGROUND

We evaluated the associations of anthropometric indicators of general obesity (body mass index, BMI), an established risk factor of various cancer, and body fat distribution (waist circumference, WC; hip circumference, HC; and waist-to-hip ratio, WHR), which may better reflect metabolic complications of obesity, with total obesity-related and site-specific (colorectal and postmenopausal breast) cancer incidence.

METHODS

This is a meta-analysis of seven prospective cohort studies participating in the CHANCES consortium including 18 668 men and 24 751 women with a mean age of 62 and 63 years, respectively. Harmonised individual participant data from all seven cohorts were analysed separately and alternatively for each anthropometric indicator using multivariable Cox proportional hazards models.

RESULTS

After a median follow-up period of 12 years, 1656 first-incident obesity-related cancers (defined as postmenopausal female breast, colorectum, lower oesophagus, cardia stomach, liver, gallbladder, pancreas, endometrium, ovary, and kidney) had occurred in men and women. In the meta-analysis of all studies, associations between indicators of adiposity, per s.d. increment, and risk for all obesity-related cancers combined yielded the following summary hazard ratios: 1.11 (95% CI 1.02-1.21) for BMI, 1.13 (95% CI 1.04-1.23) for WC, 1.09 (95% CI 0.98-1.21) for HC, and 1.15 (95% CI 1.00-1.32) for WHR. Increases in risk for colorectal cancer were 16%, 21%, 15%, and 20%, respectively per s.d. of BMI, WC, HC, and WHR. Effect modification by hormone therapy (HT) use was observed for postmenopausal breast cancer (Pinteraction<0.001), where never HT users showed an ∼20% increased risk per s.d. of BMI, WC, and HC compared to ever users.

CONCLUSIONS

BMI, WC, HC, and WHR show comparable positive associations with obesity-related cancers combined and with colorectal cancer in older adults. For postmenopausal breast cancer we report evidence for effect modification by HT use.

Adiposity and cancer at major anatomical sites: umbrella review of the literature

Objective To evaluate the strength and validity of the evidence for the association between adiposity and risk of developing or dying from cancer.Design Umbrella review of systematic reviews and meta-analyses.Data sources PubMed, Embase, Cochrane Database of Systematic Reviews, and manual screening of retrieved references.Eligibility criteria Systematic reviews or meta-analyses of observational studies that evaluated the association between indices of adiposity and risk of developing or dying from cancer.Data synthesis Primary analysis focused on cohort studies exploring associations for continuous measures of adiposity. The evidence was graded into strong, highly suggestive, suggestive, or weak after applying criteria that included the statistical significance of the random effects summary estimate and of the largest study in a meta-analysis, the number of cancer cases, heterogeneity between studies, 95% prediction intervals, small study effects, excess significance bias, and sensitivity analysis with credibility ceilings.Results 204 meta-analyses investigated associations between seven indices of adiposity and developing or dying from 36 primary cancers and their subtypes. Of the 95 meta-analyses that included cohort studies and used a continuous scale to measure adiposity, only 12 (13%) associations for nine cancers were supported by strong evidence. An increase in body mass index was associated with a higher risk of developing oesophageal adenocarcinoma; colon and rectal cancer in men; biliary tract system and pancreatic cancer; endometrial cancer in premenopausal women; kidney cancer; and multiple myeloma. Weight gain and waist to hip circumference ratio were associated with higher risks of postmenopausal breast cancer in women who have never used hormone replacement therapy and endometrial cancer, respectively. The increase in the risk of developing cancer for every 5 kg/m2 increase in body mass index ranged from 9% (relative risk 1.09, 95% confidence interval 1.06 to 1.13) for rectal cancer among men to 56% (1.56, 1.34 to 1.81) for biliary tract system cancer. The risk of postmenopausal breast cancer among women who have never used HRT increased by 11% for each 5 kg of weight gain in adulthood (1.11, 1.09 to 1.13), and the risk of endometrial cancer increased by 21% for each 0.1 increase in waist to hip ratio (1.21, 1.13 to 1.29). Five additional associations were supported by strong evidence when categorical measures of adiposity were included: weight gain with colorectal cancer; body mass index with gallbladder, gastric cardia, and ovarian cancer; and multiple myeloma mortality.Conclusions Although the association of adiposity with cancer risk has been extensively studied, associations for only 11 cancers (oesophageal adenocarcinoma, multiple myeloma, and cancers of the gastric cardia, colon, rectum, biliary tract system, pancreas, breast, endometrium, ovary, and kidney) were supported by strong evidence. Other associations could be genuine, but substantial uncertainty remains. Obesity is becoming one of the biggest problems in public health; evidence on the strength of the associated risks may allow finer selection of those at higher risk of cancer, who could be targeted for personalised prevention strategies.

Body mass index, abdominal fatness, fat mass and the risk of atrial fibrillation: a systematic review and dose-response meta-analysis of prospective studies

Different adiposity measures have been associated with increased risk of atrial fibrillation, however, results have previously only been summarized for BMI. We therefore conducted a systematic review and meta-analysis of prospective studies to clarify the association between different adiposity measures and risk of atrial fibrillation. PubMed and Embase databases were searched up to October 24th 2016. Summary relative risks (RRs) were calculated using random effects models. Twenty-nine unique prospective studies (32 publications) were included. Twenty-five studies (83,006 cases, 2,405,381 participants) were included in the analysis of BMI and atrial fibrillation. The summary RR was 1.28 (95% confidence interval: 1.20-1.38, I² = 97%) per 5 unit increment in BMI, 1.18 (95% CI: 1.12-1.25, I² = 73%, n = 5) and 1.32 (95% CI: 1.16-1.51, I² = 91%, n = 3) per 10 cm increase in waist and hip circumference, respectively, 1.09 (95% CI: 1.02-1.16, I² = 44%, n = 4) per 0.1 unit increase in waist-to-hip ratio, 1.09 (95% CI: 1.02-1.16, I² = 94%, n = 4) per 5 kg increase in fat mass, 1.10 (95% CI: 0.92-1.33, I² = 90%, n = 3) per 10% increase in fat percentage, 1.10 (95% CI: 1.08-1.13, I² = 74%, n = 10) per 5 kg increase in weight, and 1.08 (95% CI: 0.97-1.19, I² = 86%, n = 2) per 5% increase in weight gain. The association between BMI and atrial fibrillation was nonlinear, p _nonlinearity < 0.0001, with a stronger association at higher BMI levels, however, increased risk was observed even at a BMI of 22-24 compared to 20. In conclusion, general and abdominal adiposity and higher body fat mass increase the risk of atrial fibrillation.

Visceral adiposity and cancer survival: a review of imaging studies

Although obesity is a well-known risk factor for cancer, the association between obesity and cancer survival remains controversial. This is partially due to the inability of conventional obesity measures to directly assess adiposity or adipose tissue distribution. As a metabolic organ, visceral adipose tissue (VAT) secrets a variety of cytokines and cytokine-like factors, potentially affecting cancer survival. The objective of this review was to investigate the influence of imaging-assessed VAT on cancer survival. A total of 22 studies assessing the impact of visceral adiposity on survival were included. Negative associations between VAT and survival were more frequently observed among patients with colorectal (four of six studies) and pancreatic (three of five studies) cancers, compared to higher VAT predicting longer survival in most studies of renal cell carcinoma patients (four of five studies). Methodological limitations, including unstandardised VAT measurement methods, lack of other body composition measurement (i.e. muscle mass), small sample size and heterogeneous cohort characteristics, may explain controversial findings related to the impact of VAT on cancer survival.

Assessing the genetic architecture of epithelial ovarian cancer histological subtypes

Epithelial ovarian cancer (EOC) is one of the deadliest common cancers. The five most common types of disease are high-grade and low-grade serous, endometrioid, mucinous and clear cell carcinoma. Each of these subtypes present distinct molecular pathogeneses and sensitivities to treatments. Recent studies show that certain genetic variants confer susceptibility to all subtypes while other variants are subtype-specific. Here, we perform an extensive analysis of the genetic architecture of EOC subtypes. To this end, we used data of 10,014 invasive EOC patients and 21,233 controls from the Ovarian Cancer Association Consortium genotyped in the iCOGS array (211,155 SNPs). We estimate the array heritability (attributable to variants tagged on arrays) of each subtype and their genetic correlations. We also look for genetic overlaps with factors such as obesity, smoking behaviors, diabetes, age at menarche and height. We estimated the array heritabilities of high-grade serous disease ([Formula: see text] = 8.8 ± 1.1 %), endometrioid ([Formula: see text] = 3.2 ± 1.6 %), clear cell ([Formula: see text] = 6.7 ± 3.3 %) and all EOC ([Formula: see text] = 5.6 ± 0.6 %). Known associated loci contributed approximately 40 % of the total array heritability for each subtype. The contribution of each chromosome to the total heritability was not proportional to chromosome size. Through bivariate and cross-trait LD score regression, we found evidence of shared genetic backgrounds between the three high-grade subtypes: serous, endometrioid and undifferentiated. Finally, we found significant genetic correlations of all EOC with diabetes and obesity using a polygenic prediction approach.

Mendelian randomization study of adiposity-related traits and risk of breast, ovarian, prostate, lung and colorectal cancer

BACKGROUND

Adiposity traits have been associated with risk of many cancers in observational studies, but whether these associations are causal is unclear. Mendelian randomization (MR) uses genetic predictors of risk factors as instrumental variables to eliminate reverse causation and reduce confounding bias. We performed MR analyses to assess the possible causal relationship of birthweight, childhood and adult body mass index (BMI), and waist-hip ratio (WHR) on the risks of breast, ovarian, prostate, colorectal and lung cancers.

METHODS

We tested the association between genetic risk scores and each trait using summary statistics from published genome-wide association studies (GWAS) and from 51 537 cancer cases and 61 600 controls in the Genetic Associations and Mechanisms in Oncology (GAME-ON) Consortium.

RESULTS

We found an inverse association between the genetic score for childhood BMI and risk of breast cancer [odds ratio (OR) = 0.71 per standard deviation (s.d.) increase in childhood BMI; 95% confidence interval (CI): 0.60, 0.80; P = 6.5 × 10(-5)). We also found the genetic score for adult BMI to be inversely associated with breast cancer risk (OR = 0.66 per s.d. increase in BMI; 95% CI: 0.57, 0.77; P = 2.5 × 10(-7)), and positively associated with ovarian cancer (OR = 1.35; 95% CI: 1.05, 1.72; P = 0.017), lung cancer (OR = 1.27; 95% CI: 1.09, 1.49; P = 2.9 × 10(-3)) and colorectal cancer (OR = 1.39; 95% CI: 1.06, 1.82, P = 0.016). The inverse association between genetically predicted adult BMI and breast cancer risk remained even after adjusting for directional pleiotropy via MR-Egger regression.

CONCLUSIONS

Findings from this study provide additional understandings of the complex relationship between adiposity and cancer risks. Our results for breast and lung cancer are particularly interesting, given previous reports of effect heterogeneity by menopausal status and smoking status.

BMI and all cause mortality: systematic review and non-linear dose-response meta-analysis of 230 cohort studies with 3.74 million deaths among 30.3 million participants

OBJECTIVE

To conduct a systematic review and meta-analysis of cohort studies of body mass index (BMI) and the risk of all cause mortality, and to clarify the shape and the nadir of the dose-response curve, and the influence on the results of confounding from smoking, weight loss associated with disease, and preclinical disease.

DATA SOURCES

PubMed and Embase databases searched up to 23 September 2015.

STUDY SELECTION

Cohort studies that reported adjusted risk estimates for at least three categories of BMI in relation to all cause mortality.

DATA SYNTHESIS

Summary relative risks were calculated with random effects models. Non-linear associations were explored with fractional polynomial models.

RESULTS

230 cohort studies (207 publications) were included. The analysis of never smokers included 53 cohort studies (44 risk estimates) with >738 144 deaths and >9 976 077 participants. The analysis of all participants included 228 cohort studies (198 risk estimates) with >3 744 722 deaths among 30 233 329 participants. The summary relative risk for a 5 unit increment in BMI was 1.18 (95% confidence interval 1.15 to 1.21; I(2)=95%, n=44) among never smokers, 1.21 (1.18 to 1.25; I(2)=93%, n=25) among healthy never smokers, 1.27 (1.21 to 1.33; I(2)=89%, n=11) among healthy never smokers with exclusion of early follow-up, and 1.05 (1.04 to 1.07; I(2)=97%, n=198) among all participants. There was a J shaped dose-response relation in never smokers (Pnon-linearity <0.001), and the lowest risk was observed at BMI 23-24 in never smokers, 22-23 in healthy never smokers, and 20-22 in studies of never smokers with ≥20 years' follow-up. In contrast there was a U shaped association between BMI and mortality in analyses with a greater potential for bias including all participants, current, former, or ever smokers, and in studies with a short duration of follow-up (<5 years or <10 years), or with moderate study quality scores.

CONCLUSION

Overweight and obesity is associated with increased risk of all cause mortality and the nadir of the curve was observed at BMI 23-24 among never smokers, 22-23 among healthy never smokers, and 20-22 with longer durations of follow-up. The increased risk of mortality observed in underweight people could at least partly be caused by residual confounding from prediagnostic disease. Lack of exclusion of ever smokers, people with prevalent and preclinical disease, and early follow-up could bias the results towards a more U shaped association.

Acrylamide and glycidamide hemoglobin adduct levels and endometrial cancer risk: A nested case-control study in nonsmoking postmenopausal women from the EPIC cohort

Acrylamide, classified in 1994 by IARC as "probably carcinogenic to humans," was discovered in 2002 in some heat-treated, carbohydrate-rich foods. Four prospective studies have evaluated the association between dietary acrylamide intake and endometrial cancer (EC) risk with inconsistent results. The purpose of this nested case-control study, based on the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort, was to evaluate, for the first time, the association between hemoglobin adducts of acrylamide (HbAA) and glycidamide (HbGA) and the risk of developing EC in non-smoking postmenopausal women. Hemoglobin adducts were measured in red blood cells by HPLC/MS/MS. Four exposure variables were evaluated: HbAA, HbGA, their sum (HbAA+HbGA), and their ratio (HbGA/HbAA). The association between hemoglobin adducts and EC was evaluated using unconditional multivariable logistic regression models, and included 383 EC cases (171 were type-I EC), and 385 controls. Exposure variables were analyzed in quintiles based on control distributions. None of the biomarker variables had an effect on overall EC (HRHbAA;Q5vsQ1 : 0.84, 95%CI: 0.49-1.48; HRHbGA;Q5vsQ1 : 0.94, 95%CI: 0.54-1.63) or type-I EC risk. Additionally, none of the subgroups investigated (BMI < 25 vs. ≥25 kg m(-2) , alcohol drinkers vs. never drinkers, oral contraceptive users vs. non-users) demonstrated effect measure modification. Hemoglobin adducts of acrylamide or glycidamide were not associated with EC or type-I EC risk in 768 nonsmoking postmenopausal women from the EPIC cohort.

Obesity over the life course and risk of acute myeloid leukemia and myelodysplastic syndromes

BACKGROUND

Overweight and obesity are known risk factors for a number of cancers, with recent evidence suggesting that risk of hematologic cancer is also increased in obese individuals. We evaluated associations between body mass index (BMI) at differing time points during the life course in population-based case control studies of acute myeloid leukemia (AML) and myelodysplatic syndromes (MDS).

METHODS

Cases were identified by the Minnesota Cancer Surveillance System. Controls were identified through the Minnesota State driver's license/identification card list. BMI was calculated using self-reported height and weight at ages 18, 35, and 50 years and two years prior to interview, and categorized as normal (18.5-25 kg/m(2)), overweight (25-29.9 kg/m(2)), obese class I (30-34.9 kg/m(2)), and obese class II/III (35+ kg/m(2)). All analyses were stratified by sex. Unconditional logistic regression was used to calculate odds ratios and 95% confidence intervals.

RESULTS

We included 420 AML cases, 265 MDS cases and 1388 controls. Obesity two years prior to diagnosis was associated with AML in both males and females (OR=2.22, 95% CI 1.28, 3.85 and OR=1.85, 95% CI 1.08, 3.15 for BMI≥35 vs. BMI 18.5-24.9, respectively). In contrast, associations between obesity and MDS were observed only in females. Weight change in adulthood was not consistently associated with either outcome.

CONCLUSION

Our results extend the emerging literature suggesting that obesity is a risk factor for hematologic malignancy and provide evidence that that the association remains regardless of timing of obesity. Obesity in adulthood is a modifiable risk factor for both MDS and AML.

Acrylamide and Glycidamide Hemoglobin Adducts and Epithelial Ovarian Cancer: A Nested Case-Control Study in Nonsmoking Postmenopausal Women from the EPIC Cohort

BACKGROUND

Acrylamide was classified as "probably carcinogenic to humans (group 2A)" by the International Agency for Research on Cancer. Epithelial ovarian cancer (EOC) is the fourth cause of cancer mortality in women. Five epidemiological studies have evaluated the association between EOC risk and dietary acrylamide intake assessed using food frequency questionnaires, and one nested case-control study evaluated hemoglobin adducts of acrylamide (HbAA) and its metabolite glycidamide (HbGA) and EOC risk; the results of these studies were inconsistent.

METHODS

A nested case-control study in nonsmoking postmenopausal women (334 cases, 417 controls) was conducted within the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Unconditional logistic regression models were used to estimate ORs and 95% confidence intervals (CI) for the association between HbAA, HbGA, HbAA+HbGA, and HbGA/HbAA and EOC and invasive serous EOC risk.

RESULTS

No overall associations were observed between biomarkers of acrylamide exposure analyzed in quintiles and EOC risk; however, positive associations were observed between some middle quintiles of HbGA and HbAA+HbGA. Elevated but nonstatistically significant ORs for serous EOC were observed for HbGA and HbAA+HbGA (ORQ5vsQ1, 1.91; 95% CI, 0.96-3.81 and ORQ5vsQ1, 1.90; 95% CI, 0.94-3.83, respectively); however, no linear dose-response trends were observed.

CONCLUSION

This EPIC nested case-control study failed to observe a clear association between biomarkers of acrylamide exposure and the risk of EOC or invasive serous EOC.

IMPACT

It is unlikely that dietary acrylamide exposure increases ovarian cancer risk; however, additional studies with larger sample size should be performed to exclude any possible association with EOC risk.

Adult lifetime alcohol consumption and invasive epithelial ovarian cancer risk in a population-based case-control study

OBJECTIVE

Meta-analyses report a null association between recent alcohol consumption and ovarian cancer risk. However, because few studies investigated different types of alcohol over adult ages, we investigated adult lifetime and type (beer, wine, spirits) of consumption and risk.

METHODS

Consumption after age 20years was ascertained in 1144 invasive epithelial ovarian cancer cases and 2513 controls in a population-based case-control study (Alberta and British Columbia, Canada, 2001-2012). Non-drinkers consumed any types of alcohol <12 times per year on average. Logistic regression was use to estimate adjusted odds ratios [aOR] and 95% confidence intervals [CIs].

RESULTS

Wine consumption was associated with a risk reduction (aOR=0.67, 95% CI: 0.50-0.88) relative to non-drinkers, but not beer (aOR=1.06, 95% CI: 0.71-1.58) or spirits (aOR=0.98, 95% CI: 0.69-1.39). The reduced risk was stronger for exclusive red wine drinkers (aOR=0.44, 95% CI: 0.19-0.92) than white wine drinkers (aOR=0.79, 95% CI: 0.46-1.34), although most women drank both types of wine. Risk decreased with increasing cumulative consumption of any wine (P-trend<0.05) and was evident for the serous histotype. Wine consumption initiated prior to age 50 was associated with a risk reduction (e.g., at 40-49years, aOR=0.58, 95% CI: 0.42-0.78), but not drinking initiated after 50years of age. For any type, level, or age at initiation of alcohol consumption, we found no increased risks.

CONCLUSIONS

For the moderate consumption in this study, higher levels of wine consumption were generally associated with risk reductions; reductions may be stronger for red wine. Our results suggest that alcohol consumption that is guideline concordant will not increase epithelial ovarian cancer risk.

Comparison of anthropometric measures as predictors of cancer incidence: A pooled collaborative analysis of 11 Australian cohorts

Obesity is a risk factor for cancer. However, it is not known if general adiposity, as measured by body mass index (BMI) or central adiposity [e.g., waist circumference (WC)] have stronger associations with cancer, or which anthropometric measure best predicts cancer risk. We included 79,458 men and women from the Australian and New Zealand Diabetes and Cancer Collaboration with complete data on anthropometry [BMI, WC, Hip Circumference (HC), WHR, waist to height ratio (WtHR), A Body Shape Index (ABSI)], linked to the Australian Cancer Database. Cox proportional hazards models assessed the association between each anthropometric marker, per standard deviation and the risk of overall, colorectal, post-menopausal (PM) breast, prostate and obesity-related cancers. We assessed the discriminative ability of models using Harrell's c-statistic. All anthropometric markers were associated with overall, colorectal and obesity-related cancers. BMI, WC and HC were associated with PM breast cancer and no significant associations were seen for prostate cancer. Strongest associations were observed for WC across all outcomes, excluding PM breast cancer for which HC was strongest. WC had greater discrimination compared to BMI for overall and colorectal cancer in men and women with c-statistics ranging from 0.70 to 0.71. We show all anthropometric measures are associated with the overall, colorectal, PM breast and obesity-related cancer in men and women, but not prostate cancer. WC discriminated marginally better than BMI. However, all anthropometric measures were similarly moderately predictive of cancer risk. We do not recommend one anthropometric marker over another for assessing an individuals' risk of cancer.