Breast cancer, the most common cancer in women worldwide, accounted for 1.7 million new cases in 2012, comprising a quarter of all new cancer cases [
Metabolic syndrome (MS) is a cluster of pathophysiological disorders comprising central obesity, insulin resistance, high blood pressure, and dyslipidemia. Reaven’s definition of MS in 1988 [
MS has been identified as a risk factor for several cancers, particularly breast, pancreatic, colorectal, and prostate cancers [
Previous epidemiologic studies on MS and breast cancer risk show contrary results. For example, only four [
A recent systematic review and meta-analysis of MS and postmenopausal breast cancer found that MS was moderately associated with the risk of postmenopausal breast cancer [
The
Studies not meeting all inclusion criteria were excluded from this review. Excluded studies were those that (1) were not published as full reports, such as conference abstracts and letters to the editors; (2) only examined individual components of MS; (3) measured the MS variables at time of cancer diagnosis; (4) used cancer mortality, rather than incidence, as the outcome; and (5) were published in a language other than English.
A comprehensive and systematic search was conducted using four electronic databases: PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Web of Science, and ProQuest (from their commencement to June 30, 2012). Since the term MS dates back to the late 1950s, with variations in use as early as the 1920s, the start dates of each of the databases were used as the commencement date for study search: Web of Science (1900), CINAHL (1952), PubMed (1966), and ProQuest (1861). In addition, cross-referencing from retrieved studies was also performed. Major keywords used in the search for potentially eligible studies included “metabolic syndrome” (“insulin resistance syndrome,” “syndrome x”) and “breast cancer” (“neoplasm and breast”). Using the most recent publication, trials published as duplicate reports (parallel publications) were only included once. All electronic searches were conducted using the graphical user interface for each database. The last search was conducted on June 30, 2012. An initial cut-off point for the inclusion of studies was not used given the difficulty in establishing such a point, as well as our concern about the potential loss of studies that met our eligibility criteria.
At the first screening, one author (RB) screened all abstracts and selected articles for full-text examination. At the second level of the study selection process, two of the authors (RB and TH) examined the full-text articles and then selected the included studies following mutual discussion and consensus.
Two of the authors (RB and TH) reviewed every study selected and independently extracted data from studies onto electronic coding forms. These forms could hold up to 52 items per study. Attempts were made to contact authors of three of the original studies for missing information [
Risk of bias was assessed using a modified version of Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist [
Criteria for risk of bias assessment.
Criteria | Low risk | High risk | Unclear risk |
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Study design | Prospective or retrospective cohort, nested case-control | Case-control | Information not reported |
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Adjustment of confounders | Adjusted for 4 or more of the following: age, education/income, family history of cancer, hormone therapy use/oral contraceptive use/reproductive history, smoking status, and alcohol consumption | Adjusted for 3 or less of the following: age, education/income, family history of cancer, hormone therapy use/oral contraceptive use/reproductive history, smoking status, and alcohol consumption | Information not reported |
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Selection of participants and their eligibility criteria | Studies clearly stating their eligibility criteria and the sources and methods of selection of participants | Studies not clearly stating their eligibility criteria and the sources and methods of selection of participants | Information not reported |
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Measurement of predictor variables | Identified through objective measures | Self-reported or pharmaceutical prescriptions | Information not reported |
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Breast cancer diagnosis | Histologically confirmed or identified through cancer registry/medical records | Self-reported | Information not reported |
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Study size | Large enough for adequate power | Not large enough for adequate power | Information not reported |
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Handling of missing data | Missing data analysis specified | Missing data deleted from analysis | Information not reported |
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Reasons for nonparticipation of individuals at each stage of the study | Reasons clearly reported for each stage of study | Reasons not reported for each stage of study | Information not reported |
Risk estimates were used to examine the association between MS and risk of breast cancer. These were derived from reported relative risks, odds ratios, hazard ratios, incident rate ratios, or standardized incidence ratios, together with corresponding 95% confidence intervals (CIs), from the original studies. Where necessary and possible, all metrics were converted to risk ratios (RRs). Adjusted risk estimates were pooled for analysis from multivariable models in the original studies. However, for two case-control studies that were included [
All RR results were pooled using a random-effects model, an approach that incorporates between-study heterogeneity into the model [
Influence analysis was conducted with each study result deleted from the model once, in order to examine the effects of each on the overall pooled results. Cumulative meta-analysis, ranked by year, was also conducted in order to examine the accumulation of results over time. A separate pooled analysis, limited to postmenopausal women, was conducted because studies show that MS in postmenopausal women increases the risk of breast cancer [
Figure
Flow diagram describing the selection of studies.
A general description of the included studies is shown in Table
Characteristics of studies.
Author | Year | Country | Study design | Sample size | Baseline year | Follow-up years | Age | Breast cancer cases | Menopausal status | Statistic |
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Agnoli et al. [ |
2010 | Italy | Prospective nested case-control | 792 | 1987–92 | 2003 | 35–69 | 163 | Post | Rate ratios |
Bosco [ |
2011 | USA | Prospective cohort | 49,172 | 1995 | 2007 | 21–69 | 1228 | Mixed, post | Incidence rate ratios |
Inoue et al. [ |
2009 | Japan | Prospective cohort | 18,176 | 1990–94 | 2004 | 40–69 | 120 | Mixed, post | Hazard ratios |
Kabat et al. [ |
2009 | USA | Prospective cohort | 4,888 | 1993–98 | 2005 | 50–79 | 165 | Post | Hazard ratios |
Osaki et al. [ |
2012 | Japan | Retrospective cohort | 15,386 | 1992–2000 | 2007 | 20+ | 77 | Mixed, post | Hazard ratios |
Ronco et al. [ |
2012 | Uruguay | Case-control | 912 | 2004 | 2009 | <70 | 367 | Post | Odds ratios |
Rosato et al.—Cohort I [ |
2011 | Italy | Case-control | 3,858 | 1983 | 1994 | 33–86 | 1,988 | Post | Odds ratios |
Rosato et al.—Cohort II [ |
2011 | Italy and Switzerland | Case-control | 4,093 | 1991 | 2007 | 33–79 | 1,881 | Post | Odds ratios |
Russo et al. [ |
2008 | Italy | Prospective cohort | Not reported | 1999 | 2005 | ≥40 | 99 | Mixed | Standardized incidence ratios |
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Author | Exposure assessment | Cancer identification | Confounders | |||||||
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Agnoli et al. [ |
Questionnaire, anthropometric measures, and fasting blood draw | Cancer registry | Age, age at menarche, age at first birth, years from menopause, number of full-term pregnancies, oral contraceptives, hormone therapy, education, cancer in first degree relatives, breastfeeding, smoking, and alcohol consumption | |||||||
Bosco [ |
Questionnaire | Medical records or cancer registry data | Age, education, BMI at 18, and vigorous activity | |||||||
Inoue et al. [ |
Questionnaire, anthropometric measures, and fasting and nonfasting blood draw | Self-report | Age, study area, smoking status, ethanol intake, physical activity, and total cholesterol | |||||||
Kabat et al. [ |
Questionnaire, anthropometric measures, and fasting blood draw | Self-report confirmed by medical records and tumor registry abstracts | Age, education, ethnicity, BMI, oral contraceptive use, postmenopausal hormone therapy, age at menarche, age at first birth, age at menopause, alcohol, family history of breast cancer, history of breast biopsy, physical activity, energy intake, and smoking status | |||||||
Osaki et al. [ |
Questionnaire, anthropometric measures, and fasting blood draw | Cancer registry | Age, smoking, and heavy drinking | |||||||
Ronco et al. [ |
Questionnaire and anthropometric measures after cancer | Histologically confirmed breast cancer | Age, residence, age at menarche, parity, age at first live birth, months of breastfeeding, use of oral contraceptives, BMI, menopausal status, family history of breast cancer, and intake of beef, tomatoes, and oranges | |||||||
Rosato et al. [ |
Questionnaire and waist circumference measure | Histologically confirmed breast cancer | Age, study center, study period, education, alcohol consumption, age at menarche, parity and age at first birth, age at menopause, hormone replacement therapy use, and family history of breast cancer | |||||||
Russo et al. [ |
Pharmaceutical prescriptions for MS | Cancer registry | Not reported |
Definitions and criteria for metabolic syndrome in the included studies.
Agnoli et al. [ |
2 definitions (≥3 of the following components). |
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Bosco [ |
≥3 of the following components: WC ≥ 88 cm; Type 2 Diabetes Mellitus self-reported diagnosis at ≥ 30 years at baseline; HTN self-reported diagnosis plus diuretics or hypertensive medication use at baseline; cholesterol self-reported diagnosis of high cholesterol and cholesterol-lowering medication at baseline. |
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Inoue et al. [ |
2 definitions. |
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Kabat et al. [ |
ATP III modified to exclude those with glucose ≥ 126 mg/dL or those taking diabetic medication. |
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Osaki et al. [ |
6 definitions: Japan 2005, modified NCEP 2001, modified NCEP 2004, modified IDF 2006, modified WHO 1999, and NCEP 2001 with BP 140/90. |
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Ronco et al. [ |
2 definitions. |
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Rosato et al. [ |
Combined presence of diabetes, drug-treated HTN, drug-treated hyperlipidemia (as a proxy indicator of elevated triglycerides and reduced HDL-C), and WC ≥ 88 cm or BMI ≥ 30 kg/m2 when WC was missing. |
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Russo et al. [ |
Pharmacological definition: patients who chronically received antihypertensive, glucose-lowering, and lipid modifying drugs. |
Risk of bias results are shown in Table
Study-level results for risk of bias assessment.
Agnoli et al. [ |
Bosco [ |
Inoue et al. [ |
Kabat et al. [ |
Osaki et al. [ |
Ronco et al. [ |
Rosato et al. [ |
Russo et al. [ | |
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Methods | ||||||||
Study design | Low | Low | Low | Low | Low | High | High | Low |
Variables (confounders) | Low | High | High | Low | High | Low | Low | Unclear |
Participants (eligibility, selection) | Low | Low | Low | Low | Low | Low | Low | Low |
Data sources/predictor measurement | Low | High | Low | Low | Low | High | High | High |
Data sources/outcome measurement | Low | Low | High | Low | Low | Low | Low | Low |
Study size (adequate power) | Low | Low | Low | Low | Low | Low | Low | Low |
Missing data analysis | High | High | High | Low | High | Low | Unclear | Unclear |
Results | ||||||||
Participants (non-participation) | High | High | High | High | Low | Low | High | High |
Overall, a statistically significant increase of 47% in the risk for incident breast cancer was observed for adult females with MS (RR: 1.47, 95% CI, 1.15–1.87;
Forest plot for metabolic syndrome and breast cancer risk (random-effects model). The black circles represent the weighted risk ratio (RR) for each result from each study, while the horizontal lines represent the lower and upper 95% confidence intervals (CI) for the RR. The black diamond represents the overall pooled RR, while the left and right sides of the diamond represent the lower and upper 95% CI for the pooled RR. For studies that included more than one definition of metabolic syndrome, the following were used: Agnoli et al. (tertile definition), Bosco (time-independent definition), Osaki et al. (modified NCEP 2001 definition), and Ronco et al. (diabetes, overweight, and hypertension definition).
Funnel plot of precision by log risk ratio.
With each study deleted from the model once, results remained positive and statistically significant (Figure
Influence analysis with each result from each study deleted from the random-effects model once. The black circles represent the risk ratio (RR) for each result from each study while the horizontal lines represent the lower and upper 95% confidence interval (CI) for the RR. The black diamond represents the overall pooled result while the left and right sides of the diamond represent the lower and upper 95% CI for the pooled RR. For studies that included more than one definition of metabolic syndrome, the following were used: Agnoli et al. (tertile definition), Bosco (time-independent definition), Osaki et al. (modified NCEP 2001 definition), and Ronco et al. (diabetes, overweight, and hypertension definition).
Cumulative meta-analysis, ranked by year and based on a random-effects model. The black circles represent the cumulative risk ratios (RR) while the horizontal lines represent the lower and upper 95% confidence intervals (CI) for the RR. The black diamond represents the overall pooled RR while the left and right sides of the diamond represent the lower and upper 95% CI for the pooled RR. For those studies that included more than one definition of metabolic syndrome, the following were used: Agnoli et al. (tertile definition), Bosco (time-independent definition), Osaki et al. (modified NCEP 2001 definition), and Ronco et al. (diabetes, overweight, and hypertension definition).
The purpose of this aggregate data meta-analysis was to examine the association between MS and the risk for breast cancer in adult females. Overall, the results suggest that there was a modest positive association between MS and risk of breast cancer. This finding is strengthened by the robustness of results from other analyses. These include (1) examination for publication bias, (2) influence analysis with each study being deleted from the model once, (3) deletion of the two case-control studies with odds ratios from the overall model, (4) limiting the analysis to prospective designs, (5) including only postmenopausal women in the analysis, and (6) limiting the results to studies that controlled for four or more of the important confounders. In addition, the results from cumulative meta-analysis, ranked by year, indicate an increasingly statistically significant association since 2011. In contrast, despite a slightly increased mean RR, overlapping CIs were observed when studies that included participants with diabetes or taking medications for diabetes were deleted from the model [
Assessment for risk of bias indicated that a majority of studies were at low risk regarding study design, cancer assessment, and sample size. However, a majority were at high risk or unclear risk in terms of handling of missing data and nonparticipation of subjects at each stage of follow-up. It is suggested that future studies provide complete information on the handling of missing data and on the nonparticipation of subjects at each stage of follow-up.
When limited to postmenopausal women, a stronger association between MS and breast cancer was observed. This association was stronger in case-control and retrospective cohort study designs compared to prospective cohort study designs. These findings concur with those from a recent meta-analysis on MS and breast cancer risk in postmenopausal women [
There are several potential mechanisms linking MS with an increased risk of breast cancer. First, obese postmenopausal women produce higher levels of estrogens, which in turn increase the biologically available fraction of circulating estradiol by reducing plasma concentration of sex hormone binding globulin (SHBG) [
The increasing prevalence of MS and its association with breast cancer, among other comorbidities, point toward the critical need to develop public health strategies to manage MS. Given the increasingly large global burden of metabolic risk factors, even a small association with breast cancer can have a substantial public health impact. Risk assessment tools can be developed which incorporate MS as a risk factor for breast cancer. Healthcare providers will then be better equipped to identify high-risk women for primary and secondary prevention.
This study has several strengths. First, to the best of our knowledge, this is the first systematic review and meta-analysis examining the association between MS and risk of breast cancer in all adult women. The analysis incorporates all women and a subanalysis of postmenopausal women. The overlapping meta-analysis on metabolic syndrome and breast cancer was confined to postmenopausal women only [
This study also has several potential limitations. These include (1) the different methods used to assess exposure, identify cancer, control for confounders, and define MS, (2) limiting studies to those published in English, which may have inflated the results [
In order to inform and undergird a biological rationale for the observed positive association between MS and breast cancer risk in adult females, future research should comprise analyses based on a standard definition of MS and employ objective and standard biomarkers for assessing each MS component. In addition, adjustments for all important potential confounders need to be made. It would be helpful if future studies examined the relationship between MS and breast cancer risk separately in perimenopausal and premenopausal women since breast cancer in women may be estrogen-independent. Along those lines, not all studies adjusted for hormone replacement therapy, a potential confounder. Future studies should report this information. Furthermore, they need to examine
In conclusion, the overall results of this meta-analysis suggest that there is a modest positive association between MS and risk of breast cancer in adult females.
The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the National Institute for Occupational Safety and Health.
The authors declare that there is no conflict of interests regarding the publication of this paper.
This work was done when Ruchi Bhandari was a doctoral student at West Virginia University.