Skip to main content
PMC home page
Scientific Reports logoLink to Scientific Reports
. 2017 Mar 20;7:44877. doi: 10.1038/srep44877

Hypertension and breast cancer risk: a systematic review and meta-analysis

Hedong Han 1,*, Wei Guo 1,*, Wentao Shi 1,*, Yamei Yu 2, Yunshuo Zhang 3, Xiaofei Ye 1, Jia He 1,a
PMCID: PMC5357949  PMID: 28317900

Abstract

Observational studies examining the relationship between hypertension and breast cancer risk have reported conflicting findings. We conducted this systematic review and meta-analysis to summarize the evidence regarding the association between hypertension and risk of breast cancer. Eligible studies were identified through a comprehensive literature search of PubMed, EMBASE, and the Cochrane library until August 2016. We included observational studies that reported relative risks (RR) with corresponding 95% confidence intervals (CIs). Results from individual studies were pooled by using a random-effects model. 29 articles of 30 studies, with totally 11643 cases of breast cancer, were eligible for inclusion in the meta-analysis. We observed a statistically significant association between hypertension and increased breast cancer risk (RR: 1.15; 95% CI: 1.08, 1.22). In the subgroup analysis, we found a positive association between hypertension and breast cancer incidence among postmenopausal women (RR: 1.20; 95% CI: 1.09, 1.31). In contrast, hypertension was not associated with risk of breast cancer among premenopausal women (RR: 0.97; 95% CI: 0.84, 1.12) and Asian population (RR: 1.07; 95% CI: 0.94, 1.22).This meta-analysis collectively suggests a significantly association between hypertension and breast cancer risk, specifically for postmenopausal hypertensive women.

Breast cancer is the second most common cancer overall (1.7 million cases) and ranks 5th as cause of death (522,000 cases) in 2012 worldwide1. Both incidence and mortality from breast cancer in women vary among populations around the world, with higher rates in most developed countries than in less developed countries2. The incidence rate of breast cancer has also been increasing rapidly in Asian countries3, particularly a steady growth rate of 3–5% annually has been reported in China for the past three decades4. Studies have suggested that several factors including age, starting menstruating early or having a late menopause, family history and genetic factors, previous benign breast disease, radiation, obesity, oral contraceptives, hormonal replacement therapy and diabetes mellitus are associated with high breast cancer risk2,5,6. Hypertension, a common chronic disease and major risk factor for cardiac cerebral vascular disease and chronic kidney disease, has also been implicated as a risk factor for breast cancer7.

However, case-control and cohort studies that examined the relationship between hypertension and breast cancer risk in women have given inconclusive results. One cohort study, one nested case-control study and ten case-control studies8,9,10,11,12,13,14,15,16,17,18 suggested that hypertension was related to increased risk of breast cancer, while other studies19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36 failed to reveal a significant correlation between hypertension and breast cancer risk. A possible reason for this inconsistency could be that individual studies did not provide sufficient power to indicate any benefit or harm. Another explanation was that adjustments varied among the included studies, especially for risk factors such as age, diabetes or obesity. Given the two major concerns of public health and conflicting results discussed above, we conducted a meta-analysis to summarize all available evidence from case-control and cohort studies on the relationship between hypertension and the risk of breast cancer. In the present study, we also examined whether the association between hypertension and the risk of breast cancer differed according to various study characteristics and menopausal status.

Methods

Data sources and search strategy

We followed the standard MOOSE37 and PRISMA38 criteria when conducting this meta-analysis and reporting the results. A systematic literature search was conducted for articles on hypertension and risk of breast cancer, which were published between 1965 and August 2016, using the databases of PubMed, EMBASE, and the Cochrane library. Searches were performed using Medical Subject Heading terms and the free keywords: (“Breast Neoplasms” OR “Breast Cancer” OR “Breast Tumor” OR “Breast Tumors” OR “Breast Carcinoma” OR “Breast Carcinomas”) AND (“Blood Pressure” OR “Hypertension”) AND (“Cohort” OR “Case-control” OR “Case control”). Furthermore, the reference lists of retrieved articles were manually scrutinized to identify potential relevant studies.

Selection criteria

Two reviewers (H.H. and W.G.) independently evaluated studies for inclusion, and studies were included in the meta-analysis if they met the following criteria: 1) cohort or case control or nested case-control design; 2) the exposure of interest was hypertension (blood pressure higher than corresponding cut-off values or taking antihypertensive medications), and the outcome of interest was breast cancer risk; 3) the risk estimates, such as relative risks, odds ratios, or hazard ratios that could be transformed into relative risks with 95% confidence intervals (CIs) were reported; 4) potential factors were adjusted for breast cancer risk.

Data extraction and quality assessment

Two reviewers (H.H., W.G.) independently screened the titles and abstracts of the studies to identify all potential eligible studies using a predefined data extraction form. The following data were extracted: the first author’s last name, year of publication, study location, ethnicity, study design, exposure assessment, the definition of hypertension (according to different cut-off values for diagnosis of hypertension), outcome assessment, matched or adjusted factors and NOS score. Quality assessment was conducted using Newcastle–Ottawa Quality Assessment Scale (NOS)39 and studies with an NOS score ≥7 were considered high quality.

Statistical analysis

We examined the relationship between hypertension and the risk of breast cancer based on the effect estimate RR and its 95% CI in each study. Relative risks (RR) were used as the common measure of association across the included studies. We transformed odds ratios (OR) and hazard ratios (HR) into RR. Because the absolute risk of breast cancer is low, the OR and HR approximate the RR40,41. Random-effect model was used to combine the estimated effects42. Statistical heterogeneity among studies was evaluated by using I2 statistics43. We conducted sensitivity analysis by removing each individual study at a time from the meta-analysis to evaluate the stability of the pooled results and investigate the potential source of the heterogeneity if the heterogeneity was significant. To explore the heterogeneity, we performed subgroup analysis based on study design, number of breast cancer cases, geographical regions, definition of hypertension, whether data was extracted from metabolic syndrome (Mets) studies and study quality. Meta-regression analysis (interaction test) was conducted to explore heterogeneity between subgroups. Publication bias was assessed with the Egger’s regression test44 and funnel plot. If publication bias existed, we evaluated the effect of publication bias by using the trim and fill method45.

Stata Version 12.0 software (Stata Corp, College Station, TX) was used for all analyses, and a P-value < 0.05 was considered to be statistically significant.

Results

Description of the selected studies

Our literature search identified 1143 articles and 1097 were excluded after review of title or abstract (Fig. 1). Forty-six full-text articles were further reviewed. We excluded seventeen studies due to the following reasons: eight studies did not report RRs or 95% CI; one was comment; four reported exposure of interest as a continuous variable; four reported duplicate population. One study was identified via hand searching and the study was included in our meta-analysis. Thus, the meta-analysis included 30 independent observational studies8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36 published between 1989 and 2016 with a total of 11643 breast cancer cases. The characteristics of the included studies were summarized in Table 1. Among these studies, eight were conducted in USA, six in Italy, three in China, two in Korea, two in Japan, two in Brazil and seven in other countries. According to the study design, eleven were cohort studies, one was nested case-control studies, and eighteen were case-control studies. Nine studies reported breast cancer patients with premenopausal status and thirteen studies reported breast cancer patients with postmenopausal status. About twenty-two of the included studies provided RRs that were adjusted for age, alcohol consumption, smoking, age at menarche, education, BMI or history of breast cancer. With regard to study quality, the NOS score ranged from 5 to 8.

Figure 1. Selection of studies for inclusion in this meta-analysis.

Figure 1

Open in a new tab

Table 1. Baseline characteristics of all the studies included in the meta-analysis.

Study Study design No. of cases Age (years) Exposure assessment Definition of Hypertension Outcome assessment Adjustments NOS
Harding, 2015, Australia Cohort 549 11−96 Measurement BP ≥ 130/85mmhg Cancer registry Sex, age, smoking, education 7
Wang, 2015, China Case–control 43 46−61 Measurement BP ≥ 140/90mmhg Medical record Age, education, breastfeeding, family history of breast cancer, age at menarche, age at menopause, number of full-term pregnancies, and age at first birth 6
Sun, 2015, China Cohort 174 Median: 56.3 Physician-diagnosed NA Cancer registry Age, sex, urbanization level, occupation, income, and comorbidity of diabetes, hyperlipidemia, stroke, ischemic heart disease, chronic obstructive pulmonary disease, alcoholism, alcoholic liver damage, and medication of antihypertensive agents 7
Agnoli, 2015, Italy Cohort 593 46–61 Measurement BP ≥ 130/85mmhg Cancer registry Menopausal status, parity, age at menarche, smoking, physical activity, education, alcohol 7
Chuang, 2015, China Nested case-control 1545 Median: 31–40 Database NA Medical record Age, occupation, number of screening test before the index date, the average outpatient visit 6 months prior to the index date 7
Silva, 2015, Brazil Case-control 984 Mean: 55 for case 50.8 for control Measurement BP ≥ 140/90mmhg Histologically confirmed Age, sex, smoking 6
Jung, 2013, Korea Case-control 287 Mean: 48 for case 48.3 for control Questionnaire NA Medical record Age, age of menarche, pregnancy, age of first pregnancy, and family history of breast cancer 6
Noh, 2013, Korea Case-control 270 42.2–65.3 Medical record BP ≥ 130/85mmhg Routine health examination. Age, menopausal status, the time of visit to the Health Promotion Center 6
Mourouti, 2013, Greece Case-control 33 44–68 Questionnaire BP ≥ 130/85mmhg Physical biopsy Work, home places, age 6
Pereira, 2012, Chilean Case-control 340 Mean: 55.1 Medical record BP ≥ 140/90mmhg Histopathologically confirmed Age, alcohol use, fruit and vegetable intake, physical activity, type 2 diabetes, use of oral contraceptives, use of hormone replacement therapy, obesity, years of formal education, smoking, number of living births 6
Ronco, 2012, Uruguay Case-control 253 Mean: 40 Measurement NA Medical record Age, education, urban/rural status, age at menarche, number of live births, age at first delivery, years between menarche and first delivery, breastfeeding, oral contraception, family history of breast cancer 7
Bosco, 2012, USA Cohort 447 Median: 50 Self-reported BP ≥ 130/85mmhg Cancer registry Age, education, BMI at age 18, vigorous activity 8
Reeves, 2012, USA Cohort 551 ≥65 Measurement BP ≥ 130/85mmhg Pathology report Age, current hormone use, family history of breast cancer, and other Mets criteria, BMI 7
Osaki, 2012, Japan Cohort 77 Mean: 58.6 Medical record BP ≥ 130/85mmhg Medical record Age, smoking status, heavy drinking, presence of metabolic syndrome or pre-metabolic syndrome of each definition 7
Rosato, 2011, Italy Case–control 1063 33–86 Questionnaires BP ≥ 130/85mmhg Medical record Age, study center, study period, education, alcohol consumption, age at menarche, age at first birth, age at menopause, hormone replacement therapy use, and family history of breast cancer 6
Porto, 2011, Brazil Case–control 49 40–80 Questionnaires BP ≥ 130/85mmhg Medical record Age 6
Largent, 2010, USA Cohort 810 Mean: 52.8 Questionnaire NA Medical record Race, family history of breast cancer, age at first full-term pregnancy and number of full-term pregnancies combined variable, hormone therapy and menopausal status combined variable, lifetime physical activity, diabetes, BMI, smoking history, alcohol use, hysterectomy, breastfeeding, and quartiles of percent calories from fat 6
Cook, 2009, USA Cohort NA 30–55 Questionnaires NA Pathology reports Parity, age at each birth 6
Inoue, 2009, Japan Cohort 59 40–69 Measurements BP ≥ 130/85mmhg Cancer registry Age, study area, smoking status, weekly ethanol intake, total serum cholesterol 7
Beji, 2007, Turkey Case–control 231 28–72 Questionnaire NA Histologically confirmed Age 6
Largent, 2006, USA Case–control 172 50–75 Questionnaire NA Medical record Age, age at first full-term pregnancy, diabetes, family history of breast or ovarian cancer, smoking, alcohol, BMI, menopausal status and education 7
Lindgren, 2005, Finland Cohort 307 Mean: 51 Measurements BP ≥ 160/95mmhg Cancer registry Age, year of registration, DBP and SBP as continuous variables, smoking, BMI, use of antihypertensive drugs, functional diagnosis of hypertension and number of children for women 7
Peeters, 2000, Netherlands Cohort 523 Mean: 57 Measurements BP ≥ 160/95mmhg Cancer registry Age at baseline, height, BMI, smoking, parity, familial breast cancer, use of oral contraceptives 8
Weiss, 1999, USA Case–control 274 <45 Questionnaire NA Physician-diagnosed Age at diagnosis, race. site, menopausal status, age at first birth, number of births, family history, previous breast biopsy, alcohol, BMI, number of mammograms within the 5-year period prior to one year before diagnosis 6
Soler, 1999, Italy Case–control 639 <75 Questionnaire BP ≥ 160/95mmhg Histologically confirmed Age, area of residence, education, smoking, alcohol, parity, menopausal status, BMI 7
Talamini, 1997, Italy Case–control 86 20–74 Questionnaire NA Histologically confirmed Study area, age, education, parity, BMI, menopausal status 6
Moseson, 1993, USA Case–control 148 22–84 Physician-diagnosed NA Biopsy Age, family history of breast cancer, age at first full-term birth, height, screening variables, null parity, Jewish religion, Latin American birthplace 7
Franceschi, 1990, Italy Case–control 501 Mean: 45–54 Physician-diagnosed NA Histologically confirmed Terms for medical condition or procedure, age, area of residence, education, age at first birth, menopausal status and, except for severe overweight, BMI 6
Thompson, 1989, USA Case–control 635 <55 Physician-diagnosed NA Histologically confirmed Age and geographic region. 5
Open in a new tab

NA, not available; NOS, Newcastle–Ottawa Quality Assessment Scale; BP, blood pressure; DBP, diastolic blood pressure; SBP, systolic blood pressure; BMI, body mass index; USA, united states of America; Mets, metabolic syndrome.

Overall analysis of hypertension and breast cancer risk

30 studies regarding the relationship between hypertension and breast cancer risk were included for overall analysis in our meta-analysis. The combined effect estimations (RRs) using random-effects model were presented in Fig. 2. The overall results suggested a statistically significant 15% increase in risk of breast cancer (combined RR: 1.15; 95% CI: 1.08, 1.22). There was statistically significant heterogeneity across the included studies (I2 = 72.30%, p < 0.001).

Figure 2. Forest plots of hypertension and the risk of breast cancer.

Figure 2

Open in a new tab

Subgroup and meta-regression analysis

Subgroup analyses were performed based on study design (prospective, retrospective), definition of hypertension (HP ≥ 160/95mmhg, ≥140/90mmhg or ≥130/85mmhg), menopausal status (premenopausal status, postmenopausal status), geographical region (Asia, America or Europe) and study quality (low quality, high quality). The results of subgroup analysis regarding the relationship between hypertension and risk of breast cancer were shown in Table 2. In the subgroup analysis stratified by study design, statistically significant association was observed in both prospective studies (combined RR: 1.07; 95% CI: 1.01, 1.14, I2 = 57.30%, p = 0.01) and retrospective studies (combined RR: 1.29; 95% CI: 1.14, 1.47, I2 = 77.80%, p < 0.001). When subgroup analysis was conducted based on geographical region, no significant association was observed in Asian participates (combined RR: 1.07; 95% CI: 0.94, 1.22, I2 = 29.40%, p = 0.23). When stratified by definition of hypertension and number of breast cancer cases, no significant association was observed in hypertension defined as BP ≥ 160/90mmhg (combined RR: 1.09; 95% CI: 0.91, 1.31, I2 = 79.70%, p = 0.01) and in studies with a smaller number of breast cancer cases (combined RR: 1.20; 95% CI: 0.97, 1.47, I2 = 62.90%, p = 0.01). In subgroup analysis concerning menopausal status, the pooled RRs for postmenopausal hypertensive women was 1.20 (95% CI: 1.09, 1.31) with evidence of heterogeneity (I2 = 63.20%, p = 0.001), while the pooled RRs for premenopausal hypertensive women was 0.97 (95% CI: 0.84, 1.12) with no evidence of heterogeneity (I2 = 29.20%, p = 0.19) (Fig. 3). Meta-regression analysis showed that no variables might account for the heterogeneity across studies (Table 2).

Table 2. Subgroup analysis of the relationship between hypertension and risk of breast cancer.

Characteristics No. of studies RR (95% CI) I2 (%) P-valuea P-valueb
Total 30 1.15 (1.08,1.22) 72.30 <0.001  
Geographical region
 America 14 1.18 (1.06,1.31) 72.80 <0.001 0.84
 Europe 11 1.16 (1.05,1.29) 78.90 <0.001  
 Asia 5 1.07 (0.94,1.22) 29.40 0.23  
Study design
 Retrospective 18 1.29 (1.14,1.47) 77.80 <0.001 0.22
 Prospective 12 1.07 (1.01,1.14) 57.30 0.01  
Number of breast cancer cases
 <200 9 1.20 (0.97,1.47) 62.90 0.01 0.98
 ≥200 20 1.15 (1.07,1.25) 75.40 <0.001  
Data extracted from Mets studies
 Yes 7 1.26 (1.08,1.47) 59.40 0.02 0.38
 No 23 1.12 (1.05,1.20) 74.50 <0.001  
Study quality
 NOS < 7 16 1.21 (1.10,1.34) 80.10 <0.001 0.88
 NOS ≥ 7 14 1.09 (1.01,1.17) 45.30 0.03  
Definition of hypertension
 ≥130/85mmhg 11 1.14 (1.02,1.26) 54.40 0.02 —
 ≥140/90mmhg 3 2.18 (1.31,3.65) 42.40 0.18  
 ≥160/95mmhg 3 1.09 (0.91,1.31) 79.70 0.01  
Menopausal status
 Premenopausal 9 0.97 (0.84,1.12) 29.30 0.19 —
 Postmenopausal 13 1.20 (1.09,1.31) 63.20 0.001  
Open in a new tab

RR, relative risk; CI, confidence interval; NOS, Newcastle–Ottawa Quality Assessment Scale; P-valuea, p for heterogeneity within each subgroup; P-valueb., p for heterogeneity between subgroups.

Figure 3. Forest plots of hypertension and the risk of premenopausal and postmenopausal breast cancer.

Figure 3

Open in a new tab

Publication bias and sensitivity analysis

Publication bias was assessed by funnel plot and Egger’s regression test. Funnel plot shapes demonstrated a symmetrical distribution (Fig. 4) and no evidence of publication bias was detected by the Egger’s regression test (p = 0.26). Sensitivity analysis shown that none of the studies influence the combined results substantially in this meta-analysis.

Figure 4. Funnel plots of studies evaluating the risk of breast cancer associated with hypertension.

Figure 4

Open in a new tab

Discussion

To our knowledge, this is the first meta-analysis to comprehensively summarize the evidence between hypertension and breast cancer risk. This association has been long reported and assessed, yet with inconsistent results. The meta-analysis demonstrated a positive association between hypertension and breast cancer risk. Summary results showed that women with hypertension may have 15% increased risk of breast cancer. The association between hypertension and breast cancer was consistent for case-control and cohort studies, while the positive association was found in postmenopausal women not in premenopausal women.

The subgroup analyses indicated the effect of increased breast cancer risk was significant only in postmenopausal women, this might be explained by different estrogen metabolism pathways amongst premenopausal and postmenopausal women46,47. In addition, no significant association detected in smaller sample size studies and studies with a hypertension definition of BP ≥ 160/95mmhg might be due to insufficient statistical power. In our meta-analysis, Asian hypertensive participants did not seem to be associated with increased breast cancer risk, which was corresponding to a relatively low incidence of breast cancer in less developed countries2. Subgroup results above were likely the source of heterogeneity in our study, although test for interaction was not statistically significant (p = 0.84). As one component of metabolic syndrome, hypertension was reported to associate with increased postmenopausal breast cancer risk in a meta-analysis48, with the pooled risk estimations (combined RR:1.13; 95% CI: 1.01, 1.26) that was comparable to our result (combined RR: 1.20; 95% CI: 1.09, 1.31).

Several mechanisms have been proposed for the relationship between hypertension and breast cancer risk. First, breast cancer and hypertension may share common pathophysiological pathway mediated by adipose tissue, which could cause chronic inflammation and further increased the risk of both breast cancer and hypertension16,49,50,51. Another possible explanation is that hypertension may increase breast cancer risk by blocking and subsequently modifying apoptosis, thereby affecting the regulation of cell turnover52,53. In addition, studies reported that this positive association may be confounded by BMI and diabetes12,54, as significant association appeared to be confined to women with a BMI of at least 25 kg/m2 16. And overweight had been long reported to be associated with elevated estrogen levels and availability and consequently with the risk of postmenopausal breast cancer. However, the analytical model with BMI or diabetes as a covariate indicated that BMI or diabetes did not fully account for the positive association16,17. Finally, some studies showed women who used antihypertensive medications showed an increased risk of breast cancer compared to those without prescriptions of antihypertensive medications55,56,57. For example, Li et al. reported that the use of calcium channel blockers (one of the most commonly prescribed medications for hypertension) was associated with an over two-fold increased risk of breast cancer57. However, this positive association was widely doubted58,59 as the study was based on a quite limited sample size (12 controls, 27 for ductal cases and 31 for lobular cases). In addition, with regard to the design of case-control, potential selection bias, recall bias, and confounding by indication might lead to a biased estimation about the association. Notably, previous meta-analysis and large long-term follow-up cohort studies60,61,62 had confirmed the null association between antihypertensive drugs and breast cancer risk to a large extent. According to the analysis above, antihypertensive medications use was unlikely to alter results in this meta-analysis substantially.

There were several strengths in our study. First, a total of 30 published studies with 11,643 breast cancer cases were pooled in this meta-analysis, which might enhance the statistical power of the data analysis and thus provide more reliable estimates. Second, studies included in this review were not limited to studies with complete cross-table data, but extended to the studies with ORs and 95% CIs. Third, the included studies were conducted in different countries, which made the results more generalizable. Fourth, according to the results of Egger’s test and the funnel plot, we did not find a significant publication bias among included studies. Therefore, we concluded that the results based on the current evidences were relatively convincing.

This meta-analysis also has some limitations. First, we had no access to individual patient-level data, which would have allowed a more reliable assessment of relationship between hypertension and breast cancer risk in different patient groups. Second, hypertension and breast cancer share several risk factors that may confound the relationship. However, confounding cannot be fully excluded because our analyses were based on observational studies. Third, none of the selected studies provided the stages or grades of hypertension and risk of breast cancer; therefore, we were unable to conduct a dose-response analysis to assess the relationship between these variables more precisely. Fourth, the cutoff points for the high and low blood pressure groups were various in the included studies, which might contribute to the heterogeneity and have an influence on the summary risk estimate. Fifth, a high level of heterogeneity was found overall across the analysis. Although we used random-effect models to combine the effect estimations and performed subgroup analysis and meta-regression analysis to explore the sources of heterogeneity, according to our results, these are unlikely to have fully accounted for heterogeneity, suggesting that other potential factors like variation in grades of hypertension, molecular subtypes of breast cancer, exposure assessment or outcome assessment could be involved in this heterogeneity. Finally, breast cancer comprises various histologic subtypes with distinct clinical characteristics, but these were not demonstrated in this study.

In conclusion, our meta-analysis demonstrates that hypertension is associated with increased risk of breast cancer, especially among postmenopausal women. Consequently, health workers should increase the rate of breast cancer screening for postmenopausal hypertensive patients. Meanwhile the, general population is recommended to be involved in behavioral interventions like diet or physical activity to lower the risk of breast cancer by controlling the development of hypertension.

Additional Information

How to cite this article: Han, H. et al. Hypertension and breast cancer risk: a systematic review and meta-analysis. Sci. Rep. 7, 44877; doi: 10.1038/srep44877 (2017).

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Acknowledgments

Y.Y. and Y.Z. helped perform the literature search. This study was conducted under a grant from the National Nature Science Foundation of China (81373105) and the Fourth Round of Three-year Action Plan on Public Health Discipline and Talent Program: Evidence-based Public Health and Health Economics (No. 15GWZK0901).

Footnotes

The authors declare no competing financial interests.

Author Contributions H.H. and Y.Y. designed the research. H.H., W.G. and W.S. conducted the search. H.H. and W.G. had full access to the study data and carried out all analysis. H.H. and W.G. wrote the draft of this paper. X.Y. and Y.Z. revised the article critically. All the authors contributed to the manuscript writing, read and approved the final manuscript. J.H. was the guarantor.

References

  1. Ferlay J. et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. International journal of cancer 136, E359–386 (2015). [DOI] [PubMed] [Google Scholar]
  2. Ban K. A. & Godellas C. V. Epidemiology of Breast Cancer. Surgical oncology clinics of North America 23, 409–422 (2014). [DOI] [PubMed] [Google Scholar]
  3. Youlden D. R. et al. The descriptive epidemiology of female breast cancer: an international comparison of screening, incidence, survival and mortality. Cancer epidemiology 36, 237–248 (2012). [DOI] [PubMed] [Google Scholar]
  4. Li T., Mello-Thoms C. & Brennan P. C. Descriptive epidemiology of breast cancer in China: incidence, mortality, survival and prevalence. Breast cancer research and treatment, s10549-016-3947-0 (2016). [DOI] [PubMed] [Google Scholar]
  5. Boyle P. et al. Diabetes and breast cancer risk: a meta-analysis. British journal of cancer 107, 1608–1617 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. McPherson K., Steel C. M. & Dixon J. M. ABC of breast diseases. Breast cancer-epidemiology, risk factors, and genetics. BMJ (Clinical research ed.) 321, 624–628 (2000). [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Staessen J. A., Wang J., Bianchi G. & Birkenhager W. H. Essential hypertension. Lancet 361, 1629–1641 (2003). [DOI] [PubMed] [Google Scholar]
  8. Silva L. A. et al. Association between hypertension and breast cancer in patients from Salvador, Bahia. European Journal of Surgical Oncology 41, S90 (2015). [Google Scholar]
  9. Chuang S. C. et al. Associations between medical conditions and breast cancer risk in asians: A nationwide population-based study in Taiwan. PloS one 10 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Jung S. J. et al. Association of selected medical conditions with breast cancer risk in Korea. Journal of preventive medicine and public health=Yebang Uihakhoe chi 46, 346–352 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Ronco A. L., De Stefani E. & Deneo-Pellegrini H. Risk factors for premenopausal breast cancer: a case-control study in Uruguay. Asian Pacific journal of cancer prevention: APJCP 13, 2879–2886 (2012). [DOI] [PubMed] [Google Scholar]
  12. A P. et al. Hypertension and the risk of breast cancer in Chilean women: a case-control study. Asian Pacific journal of cancer prevention: APJCP (2012). [DOI] [PubMed] [Google Scholar]
  13. Rosato V. et al. Metabolic syndrome and the risk of breast cancer in postmenopausal women. Annals of oncology: official journal of the European Society for Medical Oncology/ESMO 22, 2687–2692 (2011). [DOI] [PubMed] [Google Scholar]
  14. Porto L. A. et al. Metabolic syndrome is an independent risk factor for breast cancer. Archives of gynecology and obstetrics 284, 1271–1276 (2011). [DOI] [PubMed] [Google Scholar]
  15. Beji N. K. & Reis N. Risk factors for breast cancer in Turkish women: a hospital-based case-control study. Eur J Cancer Care (Engl) 16, 178–184 (2007). [DOI] [PubMed] [Google Scholar]
  16. Largent J. A. et al. Hypertension, diuretics and breast cancer risk. Journal of human hypertension 20, 727–732 (2006). [DOI] [PubMed] [Google Scholar]
  17. Soler M. et al. Hypertension and hormone-related neoplasms in women. Hypertension 34, 320–325 (1999). [DOI] [PubMed] [Google Scholar]
  18. Cook N. R., Rosner B. A., Hankinson S. E. & Colditz G. A. Mammographic screening and risk factors for breast cancer. American journal of epidemiology 170, 1422–1432 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Wang M. et al. Metabolic syndrome and the risk of breast cancer among postmenopausal women in North-West China. Climacteric 18, 852–858 (2015). [DOI] [PubMed] [Google Scholar]
  20. Sun L. M. et al. Hypertension and subsequent genitourinary and gynecologic cancers risk: a population-based cohort study. Medicine 94, e753 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Harding J. et al. The metabolic syndrome and cancer: Is the metabolic syndrome useful for predicting cancer risk above and beyond its individual components? Diabetes & metabolism 41, 463–469 (2015). [DOI] [PubMed] [Google Scholar]
  22. Agnoli C. et al. Metabolic syndrome and breast cancer risk: a case-cohort study nested in a multicentre italian cohort. PloS one 10, e0128891 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Noh H. M., Song Y. M., Park J. H., Kim B. K & Choi Y. H. Metabolic factors and breast cancer risk in Korean women. Cancer causes & control: CCC 24, 1061–1068 (2013). [DOI] [PubMed] [Google Scholar]
  24. Mourouti N. et al. Cardiometabolic factors and breast cancer: A case-control study in women. Open Hypertens. J. 5, 49–55 (2013). [Google Scholar]
  25. Reeves K. W., McLaughlin V., Fredman L., Ensrud K & Cauley J. A. Components of metabolic syndrome and risk of breast cancer by prognostic features in the study of osteoporotic fractures cohort. Cancer causes & control: CCC 23, 1241–1251 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Osaki Y., Taniguchi S., Tahara A., Okamoto M. & Kishimoto T. Metabolic syndrome and incidence of liver and breast cancers in Japan. Cancer epidemiology 36, 141–147 (2012). [DOI] [PubMed] [Google Scholar]
  27. Bosco J. L., Palmer J. R., Boggs D. A., Hatch E. E. & Rosenberg L. Cardiometabolic factors and breast cancer risk in U.S. black women. Breast cancer research and treatment 134, 1247–1256 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Largent J. A. et al. Hypertension, antihypertensive medication use, and breast cancer risk in the California Teachers Study cohort. Cancer causes & control: CCC 21, 1615–1624 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Inoue M. et al. Impact of metabolic factors on subsequent cancer risk: results from a large-scale population-based cohort study in Japan. European journal of cancer prevention: the official journal of the European Cancer Prevention Organisation (ECP) 18, 240–247 (2009). [DOI] [PubMed] [Google Scholar]
  30. Lindgren A. M., Nissinen A. M., Tuomilehto J. O. & Pukkala E. Cancer pattern among hypertensive patients in North Karelia, Finland. Journal of human hypertension 19, 373–379 (2005). [DOI] [PubMed] [Google Scholar]
  31. Peeters P. H. M. et al. Hypertension and breast cancer risk in a 19-year follow-up study (the DOM cohort). Journal of hypertension 18, 249–254 (2000). [DOI] [PubMed] [Google Scholar]
  32. Weiss H. A. et al. Breast cancer risk in young women and history of selected medical conditions. International journal of epidemiology 28, 816–823 (1999). [DOI] [PubMed] [Google Scholar]
  33. Talamini R. et al. Selected medical conditions and risk of breast cancer. British journal of cancer 75, 1699–1703 (1997). [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Moseson M., Koenig K. L., Shore R. E. & Pasternack B. S. The influence of medical conditions associated with hormones on the risk of breast cancer. International journal of epidemiology 22, 1000–1009 (1993). [DOI] [PubMed] [Google Scholar]
  35. Franceschi S., la Vecchia C., Negri E., Parazzini F. & Boyle P. Breast cancer risk and history of selected medical conditions linked with female hormones. European journal of cancer (Oxford, England: 1990) 26, 781–785 (1990). [DOI] [PubMed] [Google Scholar]
  36. Thompson W. D., Jacobson H. I., Negrini B. & Janerich D. T. Hypertension, pregnancy, and risk of breast cancer. Journal of the National Cancer Institute 81, 1571–1574 (1989). [DOI] [PubMed] [Google Scholar]
  37. Stroup D. F. et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. Jama 283, 2008–2012 (2000). [DOI] [PubMed] [Google Scholar]
  38. Liberati A. et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS medicine 6 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Wells G. et al. The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analyses. http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp (2009).
  40. Zhang J. & Yu K. F. What’s the relative risk? A method of correcting the odds ratio in cohort studies of common outcomes. Jama 280, 1690–1691 (1998). [DOI] [PubMed] [Google Scholar]
  41. Greenland S. Quantitative methods in the review of epidemiologic literature. Epidemiologic reviews 9, 1–30 (1987). [DOI] [PubMed] [Google Scholar]
  42. Borenstein M. & Higgins J. P. Meta-analysis and subgroups. Prevention science: the official journal of the Society for Prevention Research 14, 134–143 (2013). [DOI] [PubMed] [Google Scholar]
  43. Higgins J. P., Thompson S. G., Deeks J. J & Altman D. G. Measuring inconsistency in meta-analyses. BMJ (Clinical research ed.) 327, 557–560 (2003). [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Egger M., Davey Smith G., Schneider M & Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ (Clinical research ed.) 315, 629–634 (1997). [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Taylor S. & Tweedie R. Practical Estimates of the Effect of Publication Bias in Meta-Analysis . Australasian Epidemiologist (1998). [Google Scholar]
  46. Brown S. B. & Hankinson S. E. Endogenous estrogens and the risk of breast, endometrial, and ovarian cancers. Steroids 99, 8–10 (2015). [DOI] [PubMed] [Google Scholar]
  47. Folkerd E. & Dowsett M. Sex hormones and breast cancer risk and prognosis. Breast (Edinburgh, Scotland) 22 Suppl 2, S38–43 (2013). [DOI] [PubMed] [Google Scholar]
  48. Esposito K. et al. Metabolic syndrome and postmenopausal breast cancer: systematic review and meta-analysis. Menopause 20, 1301–1309 (2013). [DOI] [PubMed] [Google Scholar]
  49. Balkwill F., Charles K. A. & Mantovani A. Smoldering and polarized inflammation in the initiation and promotion of malignant disease. Cancer cell 7, 211–217 (2005). [DOI] [PubMed] [Google Scholar]
  50. Li J. J., Fang C. H. & Hui R. T. Is hypertension an inflammatory disease? Medical hypotheses 64, 236–240 (2005). [DOI] [PubMed] [Google Scholar]
  51. Siiteri P. K. Adipose tissue as a source of hormones. The American journal of clinical nutrition 45, 277–282 (1987). [DOI] [PubMed] [Google Scholar]
  52. Hamet P. Cancer and hypertension. An unresolved issue. Hypertension 28, 321–324 (1996). [DOI] [PubMed] [Google Scholar]
  53. Hamet P. Cancer and hypertension: a potential for crosstalk? Journal of hypertension 15, 1573–1577 (1997). [DOI] [PubMed] [Google Scholar]
  54. Huang Z. et al. Body weight, weight change, and risk for hypertension in women. Annals of internal medicine 128, 81–88 (1998). [DOI] [PubMed] [Google Scholar]
  55. Fitzpatrick A. L., Daling J. R., Furberg C. D., Kronmal R. A. & Weissfeld J. L. Use of calcium channel blockers and breast carcinoma risk in postmenopausal women. Cancer 80, 1438–1447 (1997). [DOI] [PubMed] [Google Scholar]
  56. Chang C. H. et al. Antihypertensive agents and the risk of breast cancer in women aged 55 years and older: a nested case-control study. Journal of hypertension 34, 558–566; discussion 566 (2016). [DOI] [PubMed] [Google Scholar]
  57. Li C. I. et al. Use of antihypertensive medications and breast cancer risk among women aged 55 to 74 years. JAMA Intern Med 173, 1629–1637 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Hugon-Rodin J., Gompel A. & Plu-Bureau G. Antihypertensive medications and breast cancer risk. JAMA Intern Med 174, 640–641 (2014). [DOI] [PubMed] [Google Scholar]
  59. Coogan P. F. Calcium-channel blockers and breast cancer: a hypothesis revived. JAMA Intern Med 173, 1637–1638 (2013). [DOI] [PubMed] [Google Scholar]
  60. Chen Q. et al. Association between calcium channel blockers and breast cancer: a meta-analysis of observational studies. Pharmacoepidemiol Drug Saf 23, 711–718 (2014). [DOI] [PubMed] [Google Scholar]
  61. Azoulay L., Soldera S., Yin H. & Bouganim N. Use of Calcium Channel Blockers and Risk of Breast Cancer: A Population-based Cohort Study. Epidemiology 27, 594–601 (2016). [DOI] [PubMed] [Google Scholar]
  62. Wilson L. E., D’Aloisio A. A., Sandler D. P. & Taylor J. A. Long-term use of calcium channel blocking drugs and breast cancer risk in a prospective cohort of US and Puerto Rican women. Breast cancer research: BCR 18, 61 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Scientific Reports are provided here courtesy of Nature Publishing Group

RESOURCES