Literature DB >> 25657096

Long-Term Use of Antihypertensive Agents and Risk of Breast Cancer: A Population-Based Case-Control Study.

Henry W C Leung1, Li-Ling Hung, Agnes L F Chan, Chih-Hsin Mou.   

Abstract

INTRODUCTION: To evaluate the risk of breast cancer associated with long-term use of antihypertensive agents (AHs) in Taiwanese women with hypertension.
METHODS: A search of the Taiwan National Health Insurance Research Database identified 330,699 patients with hypertension who were treated with antihypertensive drugs between January 1, 1998 and December 31, 2011. Logistic regression models were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) between the use of AHs and breast cancer risk, adjusted for other types of antihypertensive drugs, statins and co-morbidities.
RESULTS: Among the AHs used to treat the hypertensive women enrolled in our study, our analysis revealed that those treated with one specific particular class of beta-blockers (beta-1 selective beta-blockers) had an increased risk for breast cancer. We also found that the ever-use of calcium channel blockers (CCBs; i.e. for 13 years) was associated with breast cancer in an adjusted model (OR 1.09; 95% CI 1.03-1.16). However, the use of nonselective beta-blockers, selective and nonselective alpha-blockers, angiotensin-converting enzyme inhibitors and angiotensin II antagonists were not associated with breast cancer risk.
CONCLUSION: Based on the results of our analysis, long-term use of CCBs or beta-1 selective beta-blockers are likely to be associated with the risk of breast cancer. Further large comprehensive population-based studies to support our findings are required for confirmation of this conclusion.

Entities:  

Year:  2015        PMID: 25657096      PMCID: PMC4472646          DOI: 10.1007/s40119-015-0035-1

Source DB:  PubMed          Journal:  Cardiol Ther        ISSN: 2193-6544


Introduction

Cardiac disease and hypertension have been the third and eighth leading causes of death in Taiwan since 2000 [1]. According to a recent study, the percentage of the population with a prescription for antihypertensive drugs in Taiwan has increased from 2001 to 2006 [2]. The authors of this study report that during this period, the average annual increase in prescriptions for calcium channel blockers (CCBs), angiotensin II receptor blockers (ARBs) and angiotensin-converting-enzyme inhibitors (ACEIs) were 10.7, 22.1 and 4.5 %, respectively [2]. In 2013, the sale volume of the three leading antihypertensive drugs in Taiwan amounted to about US$ 5 million; in comparison, in the USA the value of prescriptions filled for antihypertensive drugs in 2013 totaled about US$ 678.2 million [3]. The use of antihypertensive agents (AHs) has grown globally over the last decade. However, available data on a potential association between the use of AHs and risk of breast cancer are conflicting. Recent epidemiological studies suggest that beta-blockers prevent breast cancer progression or reduce recurrence and then improve survival [4-6]. In contrast, other studies have reported an increased risk or no association at all between the use of beta-blockers/CCBs and breast cancer risk [7-9]. In addition, evidence for any association between the use of ACEIs/ARBs and breast cancer is also inconsistent, with some studies suggesting that ACEIs/ARBs are not associated with cancer risk [10, 11], and others reporting an increased or reduced risk [12]. To address the conflicting evidence from previous studies, the aim of the study reported here was to evaluate the risk of breast cancer associated with long-term use of AHs in hypertensive women.

Methods

Data Source

Data were retrieved from the National Health Insurance Research Database (NHIRD) and Registry for Catastrophic Illness Patient dataset (HV dataset) between January 1, 1998 and December 31, 2011 in Taiwan. The NHIRD contains comprehensive information on demographic characteristics, pharmacy records and medical services from inpatient, outpatient and emergency care under a national health insurance program in which over 99% of the 23 million inhabitants of Taiwan are enrolled. The HV dataset comprises specific data subsets of the NHIRD for research purposes and contains registration files and original claim data on patients registered in the NHIRD who have/had a catastrophic illness. All patients records/information were de-identified and analyzed anonymously. Therefore, this study was exempt from the approval by the Ethics Review Board at our institution.

Study Group

From the HV dataset, we identified 330,699 women with newly diagnosed hypertension [International Classification of Disease, Ninth Revision (ICD-9 CM) codes 401–405] who had been treated with any AHs continuously for at least 6 months between January 1, 1998 and December 31, 2011. Among these, we further identified women with a first diagnosis of breast cancer (ICD-9 CM codes 174.xx and 175.xx); these women were the cases in our study (Fig. 1). The date of diagnosis was the index date.
Fig. 1

Study flow diagram. AHT Antihypertensive, H/T hypertension, HV Registry for Catastrophic Illness Patient dataset, NHIRD National Health Insurance Research Database

Study flow diagram. AHT Antihypertensive, H/T hypertension, HV Registry for Catastrophic Illness Patient dataset, NHIRD National Health Insurance Research Database We excluded patients who had a history of breast cancer or any cancer recorded in the HV dataset any time before the initiation of antihypertensive treatment and patients without continuous enrolment in a NHI program. Patients were followed from the date of diagnosis of hypertension in 1998 up to December 31, 2011 (median duration 13 years) or death, whichever came first (Fig. 1). We randomly selected hypertensive women registered in the NHIRD without any diagnosis of breast cancer who were receiving treatment for hypertension in the same period as the cases. These were matched (1:4) for age (5-year categories), index date and year of hypertension diagnosis with the cases to establish the control group (Fig. 1).

Exposure Variables

The main exposure of interest was that to beta-blocker, CCB, ACEI and ARB therapy. We collected information on prescribed drug types according to Anatomical Therapeutic Chemical Classification System codes (C07 for beta-blockers; C02D, C08C, C08D, C08DA51 for CCBs; C02E, C02L, C09A, C09BA for ACEIs; C09CA for ARBs), dosage, date of prescription, supply days and total number of prescriptions from the outpatient and inpatient records [13]. The cumulative defined daily dose (cDDD) of each AH was calculated as recommended by the World Health Association [14]. Beta-blockers were further classified as nonselective and beta-1 selective beta-blockers, and as selective and nonselective alpha-blockers.

Potential Covariates

Several potential covariates, including age and comorbidities at cancer diagnosis, were also measured in the year preceding the index date. Other covariates tested included the use of statins and hormone replacement therapy.

Sensitivity Analysis

We evaluated the sensitivity effects by changing the inclusion criteria of drug prescription for three types of AH beginning at least from 6–9 months before the index date.

Statistical Analysis

Logistic regression was used to estimate the crude and adjusted odds ratio (OR) and 95% confidence interval (CI) for breast cancer risk. We calculated a running sum of the duration and DDD of each drug from the date of the initial AH prescription to the index date. We categorized the cumulative use for each patient as follows: ≤1, 1–2, 2–3 and ≥3 years of duration. Cumulative DDD of each AH was classified by quartile. Multivariable logistical regression was used to adjust the covariates. We also estimated the trend of the duration and cDDD of each drug use. Data were analyzed using the SAS Statistical Package, version 9.3 (SAS Institute, Cary, NC). The significance level was set at P < 0.05 (two-tailed test).

Results

We identified 6,463 hypertensive women with breast cancer as cases and 18,987 hypertensive women without breast cancer as controls. Among the 6,463 cases, the most commonly prescribed AHs was CCBs (52.8%), followed by ACEIs (45.5%) and beta-blockers (41.1%) (Table 1). No significant differences in age and mean Charlson comorbidity score (P > 0.05) were found between cases and controls. Ever-use of CCBs and beta-blockers for longer than 10 years was significantly associated with breast cancer (OR 1.09; 95% CI 1.03–1.16) in an adjusted model. The risk of breast cancer was even higher in patients receiving hormone replacement therapy (OR 1.28, 95% CI 1.18–1.39) and statins (OR 1.68, 95 % CI 1.50–1.83) (Table 1).
Table 1

Characteristics of hypertensive patients with breast cancer and non-breast cancer during the study period (1998–2011)

CharacteristicCase (N = 6,463)Control (N = 18,987)Odds ratio (95 % CI)
n % n %CrudeAdjusted
Mean age, years (SD)61.9(10.7)61.9(10.9)
  18–442724.217854.13
  45–541,48923.04,40923.2
  55–642,32035.96,72935.4
  65–741,61024.94,77825.2
  75–846459.981,91210.1
  85+1271.973741.97
Menopause4,70272.713,79372.6
Mean CCI score (SD)0.33(0.87)0.34(0.92)0.98 (0.95–1.01)
  Diabetes1,76127.34,80325.31.11 (1.04–1.18)**1.08 (1.02–1.16)*
  Hyperlipidemia3,19649.59,20748.51.04 (0.98–1.10)
Ever users of HRT
  No5,45084.316,62687.61.00 (Reference)1.00 (Reference)
  Yes1,01315.72,36112.41.31 (1.21–1.42)***1.28 (1.18–1.39)***
Ever users of statins
  No5,72588.617,70093.21.00 (Reference)1.00 (Reference)
  Yes73811.41,2876.781.77 (1.61–1.95)***1.68 (1.52–1.85)***
Types of AHT
  ACEI
    No3,52054.510,15253.51.00 (Reference)
    Yes2,94345.58,83546.50.96 (0.91–1.02)
  ARB
    No4,68272.414,29075.31.00 (Reference)1.00 (Reference)
    Yes1,78127.64,69724.71.16 (1.09–1.23)***1.04 (0.98–1.12)
  CCBs
    No3,05247.29,69751.11.00 (Reference)1.00 (Reference)
    Yes3,41152.89,29048.91.17 (1.10–1.23)***1.09 (1.03–1.16)**
  Beta-blocker
    No3,80658.911,72161.71.00 (Reference)1.00 (Reference)
    Yes2,65741.17,26638.31.13 (1.06–1.19)***1.05 (0.99–1.12)

* P < 0.05, ** P < 0.01, *** P < 0.001

SD Standard deviation, CCI Charlson comorbidity index, HRT hormone replacement therapy,AHT Antihypertensive therapy, ACEI angiotensin-converting-enzyme inhibitor, ARB angiotensin receptor II blocker, CCB calcium channel blocker, CI confidence interval

Characteristics of hypertensive patients with breast cancer and non-breast cancer during the study period (1998–2011) * P < 0.05, ** P < 0.01, *** P < 0.001 SD Standard deviation, CCI Charlson comorbidity index, HRT hormone replacement therapy,AHT Antihypertensive therapy, ACEI angiotensin-converting-enzyme inhibitor, ARB angiotensin receptor II blocker, CCB calcium channel blocker, CI confidence interval When we stratified the risk of breast cancer associated with different sub-types of beta-blockers, we found a statistically significant risk of breast cancer with most beta-1 selective beta-blockers, such as atenolol (OR 1.14; 95% CI 1.05–1.25) acebutolol (OR 1.29; 1.00–1.66) and bisoprolol (OR 1.08; 1.01–1.16) (Fig. 2). The non-selective beta-blockers, alpha-selective and beta-non selective showed no significant association with breast cancer (Fig. 2).
Fig. 2

Forest plot of breast cancer risk associated with use of beta-blockers, 1998–2011. OR Odds ratio, CI confidence interval

Forest plot of breast cancer risk associated with use of beta-blockers, 1998–2011. OR Odds ratio, CI confidence interval We then stratified beta-blocker, ARB and CCB users by exposure duration and the cumulative DDD. The results show that the risk of breast cancer was significantly increased in beta-blocker and CCB users with increasing exposure duration and increasing cDDD compared to the controls [trend test for beta-blocker users: P = 0.003 (exposure duration), P = 0.0003 (cDDD); trend test for CCB users: P = 0.006 (exposure duration), P = 0.002 (cDDD)] (Table 2).
Table 2

Odds risk and 95% confidence intervals for risk of breast cancer associated with exposure to different types of antihypertensives, duration of exposure and dosage

Type of antihypertensive agentNo. of study subjectsNo. of breast cancer casesMultivariable-adjusted odds ratio
Odds ratio (95 % CI) P for trend
Any beta-blockera
  Never use15,5273,8061.00 (Reference)
  Ever-use exposure duration (years)0.003
    ≤12,0855210.99 (0.89–1.11)
    1–22,3005480.91 (0.82–1.01)
    2–31,5124021.03 (0.92–1.17)
    >34,0261,1861.16 (1.07–1.26)***
  Cumulative DDDb 0.0003
    cDDD < Q12,4805970.93 (0.84–1.02)
    Q1 ≤ cDDD < Q22,4826210.97 (0.88–1.07)
    Q2 ≤ cDDD < Q32,4806841.08 (0.98–1.19)
    cDDD ≥ Q42,4817551.22 (1.11–1.34)***
Any ARBc
  Never use18,9724,6821.00 (Reference)
  Ever-use exposure duration (years)0.71
    ≤11,3553701.05 (0.93–1.19)
    1–21,6524391.00 (0.89–1.12)
    2–31,0832880.98 (0.85–1.12)
    >32,3886841.03 (0.93–1.14)
  Cumulative DDDb 0.53
    cDDD < Q11,6184441.06 (0.94–1.19)
    Q1 ≤ cDDD < Q21,6214140.95 (0.84–1.07)
    Q2 ≤ cDDD < Q31,6184411.00 (0.89–1.13)
    cDDD ≥ Q41,6214821.07 (0.95–1.21)
Any CCBd
  Never use12,7493,0521.00 (Reference)
  Ever-use exposure duration (years)0.006
    ≤12,2575721.05 (0.94–1.16)
    1–22,6626961.08 (0.98–1.19)
    2–31,9585221.09 (0.98–1.22)
    >35,8521,6211.11 (1.03–1.19)**
  Cumulative DDDb 0.002
    cDDD < Q13,1758181.05 (0.96–1.15)
    Q1 ≤ cDDD < Q23,1768341.07 (0.98–1.18)
    Q2 ≤ cDDD < Q33,1748381.06 (0.97–1.17)
    cDDD ≥ Q41,6214821.16 (1.06–1.28)**

** P < 0.01, *** P < 0.001

cDDD Cumulative defined daily dose

aAdjusted for peripheral vascular disease, diabetes mellitus and medicine use (included HRT, statin, ARB and CCB)

bBeta-blocker: Q1 (25%) = 195.25 DDD, Q2 (50%) = 448 DDD, Q3 (75%) = 1,012 DDD. CCB: Q1 (25%) = 390.1 DDD, Q2 (50%) = 851 DDD, Q3 (75%) = 1,641.3 DDD. ARB: Q1 (25%) = 405 DDD, Q2 (50%) = 800.5 DDD, Q3 (75%) = 1,464 DDD

cAdjusted for peripheral vascular disease, diabetes mellitus and medicine use (including HRT, statin, beta-blocker and CCB)

dAdjusted for peripheral vascular disease, diabetes mellitus and medicine use (including HRT, statin, beta-blocker and ARB)

Odds risk and 95% confidence intervals for risk of breast cancer associated with exposure to different types of antihypertensives, duration of exposure and dosage ** P < 0.01, *** P < 0.001 cDDD Cumulative defined daily dose aAdjusted for peripheral vascular disease, diabetes mellitus and medicine use (included HRT, statin, ARB and CCB) bBeta-blocker: Q1 (25%) = 195.25 DDD, Q2 (50%) = 448 DDD, Q3 (75%) = 1,012 DDD. CCB: Q1 (25%) = 390.1 DDD, Q2 (50%) = 851 DDD, Q3 (75%) = 1,641.3 DDD. ARB: Q1 (25%) = 405 DDD, Q2 (50%) = 800.5 DDD, Q3 (75%) = 1,464 DDD cAdjusted for peripheral vascular disease, diabetes mellitus and medicine use (including HRT, statin, beta-blocker and CCB) dAdjusted for peripheral vascular disease, diabetes mellitus and medicine use (including HRT, statin, beta-blocker and ARB) The risk of breast cancer increased with ever-use of atenolol or acebutolol (Table 3). This risk increased with increasing exposure,duration of use (trend test: P = 0.0003 for atenolol; P = 0.01 for acebutolol) and cDDD (trend test: P = 0.002 for atenolol; P = 0.02 for acebutolol).
Table 3

Breast cancer risk associated with exposure duration and dosage of specific beta-blockers during the study period (1998–2011)

VariableAcebutololAtenololBisoprolol
n/N Odds ratio (95 % CI) n/N Odds ratio (95 % CI) n/N Odds ratio (95 % CI)
Duration of exposure to antihypertensive agent
  AHT non-use6,371/25,1631.00 (Reference)5,661/22,6831.00 (Reference)4,887/19,6971.00 (Reference)
  Exposure duration (years)
    ≤130/1041.10 (0.71–1.68)248/9421.01 (0.87–1.17)1,318/4,9131.06 (0.99–1.14)
    2–321/711.10 (0.66–1.84)222/7951.07 (0.91–1.26)121/4021.14 (0.92–1.42)
    3–417/521.37 (0.77–2.46)120/4231.08 (0.87–1.34)57/1791.24 (0.90–1.70)
    >324/601.85 (1.10–3.12)*212/6071.43 (1.20–1.70)***80/2591.12 (0.86–1.47)
    P for trend0.010.00030.03
Dosage (cDDD)a
  <Q121/711.10 (0.66–1.84)187/8911.04 (0.87–1.23)384/14571.04 (0.92–1.18)
  ≥Q1–<Q219/720.97 (0.57–1.64)187/6891.03 (0.87–1.23)408/14291.14 (1.01–1.29)*
  ≥Q2–<Q326/721.56 (0.96–2.53)202/6951.13 (0.96–1.34)382/14351.02 (0.90–1.15)
  ≥Q326/721.59 (0.98–2.58)226/6921.30 (1.10–1.53)**402/14321.10 (0.98–1.25)
  P for trend0.020.0020.053

* P < 0.05, ** P < 0.01, *** P < 0.001

Adjusted for diabetes mellitus and medicine use (including HRT, statins, ARBs and CCBs)

n Number of breast cancer patients using a specific AHT, N total number of study population using a specific AHT

aBeta-blocker: Q1 (25%) = 195.25 DDD, Q2 (50%) = 448 DDD, Q3 (75%) = 1,012 DDD. CCB: Q1 (25%) = 390.1 DDD, Q2 (50%) = 851 DDD, Q3 (75%) = 1,641.3 DDD. ARB: Q1 (25%) = 405 DDD, Q2 (50%) = 800.5 DDD, Q3 (75%) = 1,464 DDD

Breast cancer risk associated with exposure duration and dosage of specific beta-blockers during the study period (1998–2011) * P < 0.05, ** P < 0.01, *** P < 0.001 Adjusted for diabetes mellitus and medicine use (including HRT, statins, ARBs and CCBs) n Number of breast cancer patients using a specific AHT, N total number of study population using a specific AHT aBeta-blocker: Q1 (25%) = 195.25 DDD, Q2 (50%) = 448 DDD, Q3 (75%) = 1,012 DDD. CCB: Q1 (25%) = 390.1 DDD, Q2 (50%) = 851 DDD, Q3 (75%) = 1,641.3 DDD. ARB: Q1 (25%) = 405 DDD, Q2 (50%) = 800.5 DDD, Q3 (75%) = 1,464 DDD In the sensitivity analysis for exposure duration of AHs, the results were unchanged when the inclusion criteria of AH prescription was changed from <6 to >9 months (Table 4).
Table 4

Sensitivity analysis for criteria of antihypertensive use

VariableAny beta-blockera Any ARBb Any CCBc
n/N Odds ratio (95 % CI) n/N Odds ratio (95 % CI) n/N Odds ratio (95 % CI)
Non-user4,107/16,6901.00 (Reference)4,876/19,7001.00 (Reference)3,367/14,0121.00 (Reference)
User2,356/8,7601.04 (0.98–1.11)1,587/5,7501.01 (0.94–1.09)3,096/11,4381.09 (1.03–1.16)**
Drug use (years)
  ≤2220/9220.94 (0.80–1.10)176/6271.08 (0.90–1.29)257/9941.07 (0.92–1.24)
  2–3548/2,3000.91 (0.82–1.01)439/1,6521.00 (0.89–1.12)696/2,6621.07 (0.98–1.18)
  3–4402/1,5121.03 (0.91–1.16)288/1,0830.97 (0.84–1.12)522/1,9581.09 (0.98–1.22)
  >41,186/4,0261.15 (1.06–1.25)***684/2,3881.03 (0.93–1.14)1,621/5,8241.11 (1.03–1.19)**
  P for trend0.0050.760.005

* P < 0.05, ** P < 0.01, *** P < 0.001

N Total number of study population using specific AHT, n number of breast cancer patients using specific AHT

aAdjusted for peripheral vascular disease, diabetes mellitus and medicine use (including HRT, statins, ARBs and CCBs)

bAdjusted for peripheral vascular disease, diabetes mellitus and medicine use (including HRT, statins, beta-blockers and CCBs)

cAdjusted for peripheral vascular disease, diabetes mellitus and medicine use (including HRT, statins, beta-blockers and ARBs)

Sensitivity analysis for criteria of antihypertensive use * P < 0.05, ** P < 0.01, *** P < 0.001 N Total number of study population using specific AHT, n number of breast cancer patients using specific AHT aAdjusted for peripheral vascular disease, diabetes mellitus and medicine use (including HRT, statins, ARBs and CCBs) bAdjusted for peripheral vascular disease, diabetes mellitus and medicine use (including HRT, statins, beta-blockers and CCBs) cAdjusted for peripheral vascular disease, diabetes mellitus and medicine use (including HRT, statins, beta-blockers and ARBs)

Discussion

The results of this study suggest that the use of ACEi, ARBs, and nonselective beta-adrenergic receptor antagonists (propranolol or carteolol) is not associated with breast cancer. These results are consistent with those of most observational studies [10, 11]. We also found that CCBs and the beta-1 selective beta-blockers acebutolol, atenolol and bisoprolol may increase the risk of breast cancer. This finding seems to differ from those of previous studies which reported that beta-1 selective beta-blockers and CCBs had marked protective effects [15, 16]. However, the authors of a recently published study reported observing a weak inverse association between cardio nonselective beta-blockers and breast cancer risk [9]. However, since the association did not reach statistical significance, the results did not support the hypothesis of beta-blocker usage protecting against breast cancer progression [9]. The results of a recently published network analysis indicated a lack of consistency in the effect of CCBs on breast cancer; this was attributed to the short duration of the follow-up in the trials included in the network meta-analysis [7]. The results of previous preclinical studies are inconclusive in terms of whether beta-blockers have agonist activity in breast cancer growth. Some studies has demonstrated that beta-2 adrenergic signaling plays a role in several pathways involved in breast tumor progression and metastasis [17, 18], but others have found that beta-adrenergic receptor (AR) stimulation may both inhibit and promote breast tumor growth [19-23]. A recently published study adds further to the body of evidence on the effect of agonist type, indicating that the beta 2-AR antagonist in particular seems to be the most cytotoxic beta-blocker in non-stimulated cancer cells [24]. However, the majority of clinical observational studies carried out to date have focused on comparing the association between the use of propranolol or atenolol and breast cancer risk or mortality and have not explored the relationship between the subtype of beta-AR expression and breast cancer risk [25, 26]. Our study is the first from Asia to report that treatment with the beta-1 selective blocker—but not the nonselective β1/β blocker—may increase the risk of breast cancer (Fig. 2). These results appear to be consistent with those of preclinical studies suggesting that the effects of beta-adrenergic signaling on tumor progression and metastasis are inhibited by the β2-receptor antagonists but not by β1 antagonists [18-24]. Consequently, better designed observational studies or randomized controlled trials are required before this type of beta-blocker can be considered as a therapeutic option for patients with breast cancer. We also observed that CCBs are likely to be associated with breast cancer risk. This finding is consistent with those from a recently published study performed by Li et al. [3]. Both studies seem to revive an earlier previous hypothesis and focus on the long-term use of CCBs among current or ever-users (10 years if the study of Li et al. [3]; 13 years in our study). However, other previously published studies found no increased risk of breast cancer associated with CCB use [25, 26]. Therefore, to date, the results on the effect of CCBs on breast cancer risk are inconsistent. Again, larger and more comprehensive studies are needed to confirm the effects of long-term use of CCBs on breast cancer. A major advantage of our study was that we collected information prospectively on healthcare beneficiaries registered in a large population-based database for whom complete data on drug prescriptions and cancer diagnoses were available. Thus, the possibility of selection and information biases was minimized. However, there were still some limitations to our study. First, the health insurance database that we used was developed for administrative purposes and contained de-identified records of each individual registered. Second, the database only provided information on the frequency and classes of prescribed medications and did not provide any clinical laboratory data or clinical information; therefore, we could not estimate patient’s responses to drug therapy. Finally, the database did not contain information on various lifestyle risk factors for cancer, such as physical activity, alcohol consumption, smoking, body mass index, socioeconomic status and diet; therefore, these were not included in the analysis. Although we adjusted the potential covariates, such as co-morbidities and the use of other medications, the misclassification of these covariates may have some impact on our results.

Conclusion

Our findings indicate that the long-term use of CCBs or beta-1 selective blockers are likely to be associated with breast cancer risk. Further comprehensive and large population-based studies are needed to confirm these findings before any definitive conclusion can be drawn.
  24 in total

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7.  The sympathetic nervous system induces a metastatic switch in primary breast cancer.

Authors:  Erica K Sloan; Saul J Priceman; Benjamin F Cox; Stephanie Yu; Matthew A Pimentel; Veera Tangkanangnukul; Jesusa M G Arevalo; Kouki Morizono; Breanne D W Karanikolas; Lily Wu; Anil K Sood; Steven W Cole
Journal:  Cancer Res       Date:  2010-09-07       Impact factor: 12.701

8.  Induction of a metastatogenic tumor cell type by neurotransmitters and its pharmacological inhibition by established drugs.

Authors:  Kerstin Lang; Theodore L Drell; Antje Lindecke; Bernd Niggemann; Christian Kaltschmidt; Kurt S Zaenker; Frank Entschladen
Journal:  Int J Cancer       Date:  2004-11-01       Impact factor: 7.396

9.  Use of antihypertensive medications and breast cancer risk among women aged 55 to 74 years.

Authors:  Christopher I Li; Janet R Daling; Mei-Tzu C Tang; Kara L Haugen; Peggy L Porter; Kathleen E Malone
Journal:  JAMA Intern Med       Date:  2013-09-23       Impact factor: 21.873

10.  Beta-adrenergic and arachidonic acid-mediated growth regulation of human breast cancer cell lines.

Authors:  Y Cakir; H K Plummer; P K Tithof; H M Schuller
Journal:  Int J Oncol       Date:  2002-07       Impact factor: 5.650

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  9 in total

1.  Use of Antihypertensive Medications and Risk of Adverse Breast Cancer Outcomes in a SEER-Medicare Population.

Authors:  Lu Chen; Jessica Chubak; Denise M Boudreau; William E Barlow; Noel S Weiss; Christopher I Li
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2017-08-14       Impact factor: 4.254

Review 2.  Statin use and breast cancer survival and risk: a systematic review and meta-analysis.

Authors:  Qi-Jun Wu; Chao Tu; Yuan-Yuan Li; Jingjing Zhu; Ke-Qing Qian; Wen-Jing Li; Lang Wu
Journal:  Oncotarget       Date:  2015-12-15

3.  Patients with uterine leiomyoma exhibit a high incidence but low mortality rate for breast cancer.

Authors:  Te-Chun Shen; Te-Chun Hsia; Chieh-Lun Hsiao; Cheng-Li Lin; Chih-Yi Yang; Khay-Seng Soh; Liang-Chih Liu; Wen-Shin Chang; Chia-Wen Tsai; Da-Tian Bau
Journal:  Oncotarget       Date:  2017-05-16

Review 4.  The Effect of Local Renin Angiotensin System in the Common Types of Cancer.

Authors:  Moudhi Almutlaq; Abir Abdullah Alamro; Hassan S Alamri; Amani Ahmed Alghamdi; Tlili Barhoumi
Journal:  Front Endocrinol (Lausanne)       Date:  2021-09-03       Impact factor: 5.555

5.  Feeding in the first six months of life is associated with the probability of having bronchiolitis: a cohort study in Spain.

Authors:  Inés Gómez-Acebo; Carolina Lechosa-Muñiz; Javier Llorca; María J Cabero-Perez; María Paz-Zulueta; Trinidad Dierssen Sotos; Jéssica Alonso-Molero
Journal:  Int Breastfeed J       Date:  2021-10-18       Impact factor: 3.461

6.  Association of Hypertension and Breast Cancer: Antihypertensive Drugs as an Effective Adjunctive in Breast Cancer Therapy.

Authors:  Yuanyuan Fan; Nazeer Hussain Khan; Muhammad Farhan Ali Khan; M D Faysal Ahammad; Tayyaba Zulfiqar; Razia Virk; Enshe Jiang
Journal:  Cancer Manag Res       Date:  2022-04-01       Impact factor: 3.989

7.  Prolonged use of human insulin increases breast cancer risk in Taiwanese women with type 2 diabetes.

Authors:  Chin-Hsiao Tseng
Journal:  BMC Cancer       Date:  2015-11-04       Impact factor: 4.430

8.  The Use of Antihypertensive Medication and the Risk of Breast Cancer in a Case-Control Study in a Spanish Population: The MCC-Spain Study.

Authors:  Inés Gómez-Acebo; Trinidad Dierssen-Sotos; Camilo Palazuelos; Beatriz Pérez-Gómez; Virginia Lope; Ignasi Tusquets; M Henar Alonso; Victor Moreno; Pilar Amiano; Antonio José Molina de la Torre; Aurelio Barricarte; Adonina Tardon; Antonio Camacho; Rosana Peiro-Perez; Rafael Marcos-Gragera; Montse Muñoz; Maria Jesus Michelena-Echeveste; Luis Ortega Valin; Marcela Guevara; Gemma Castaño-Vinyals; Nuria Aragonés; Manolis Kogevinas; Marina Pollán; Javier Llorca
Journal:  PLoS One       Date:  2016-08-10       Impact factor: 3.240

9.  Antihypertensive drug use and breast cancer risk: a meta-analysis of observational studies.

Authors:  Haibo Ni; Qin Rui; Xiaojue Zhu; Zhenquan Yu; Rong Gao; Huixiang Liu
Journal:  Oncotarget       Date:  2017-07-10
  9 in total

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