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Breast Cancer Res Treat. Author manuscript; available in PMC Sep 1, 2012.
Published in final edited form as:
PMCID: PMC3145014
NIHMSID: NIHMS286894
Examining the Influence of Beta Blockers and ACE Inhibitors on the Risk for Breast Cancer Recurrence: Results from the LACE Cohort
Patricia A. Ganz, MD, Laurel A. Habel, PhD, Erin K. Weltzien, BA, Bette J. Caan, DrPH, and Steven W. Cole, PhD
Patricia A. Ganz, UCLA Schools of Public Health and Medicine, Jonsson Comprehensive Cancer Center, Los Angeles, California;
Corresponding author: Patricia A. Ganz, MD, Jonsson Comprehensive Cancer Center, Division of Cancer Prevention & Control Research, 650 Charles Young Dr. South, Room A2-125 CHS, Los Angeles, CA 90095-6900, Phone: 310-206-1404, Fax: 310-206-3566, pganz/at/mednet.ucla.edu
There is increasing interest in the relationship between host lifestyle factors and the outcomes of cancer treatment. Behavioral factors, comorbid conditions, and non-cancer related pharmaceutical exposures may affect breast cancer (BC) outcomes. We used observational data from the LACE Study cohort (women with early stage BC from the Kaiser Permanente Northern California Cancer Registry) to examine the association between beta-blockers (BB) and/or angiotensin converting enzyme inhibitors (ACEi) and BC recurrence, BC-specific mortality, and overall mortality. Among 1,779 women, there were 292 BC recurrences, 174 BC deaths, and 323 total deaths. 23% were exposed to either a BB and/or an ACEi. These drugs were associated with older age, postmenopausal status, tamoxifen therapy, greater pre-diagnosis BMI, hypertension, and diabetes. In Cox proportional hazards models, ACEi exposure was associated with BC recurrence (HR 1.56, 95% CI 1.02, 2.39, p=0.04), but not cause-specific mortality or overall mortality. Combined ACEi and BB was associated with overall mortality (HR 1.94, 95% CI 1.22, 3.10, p=0.01). BB exposure was associated with lower hazard of recurrence and cause-specific mortality. However, there was no evidence of a dose response with either medication. For recurrence and cause-specific mortality, BB combined with ACEi was associated with a lower HR for the outcome than when ACEi alone was used. These hypothesis generating findings suggest that BC recurrence and survival were associated with exposure to two commonly used classes of anti-hypertensive medications. These observations need to be confirmed and suggest that greater attention should focus on the potential role of these commonly used medications in BC outcomes.
During the past decade there has been increasing scientific interest in understanding the complex relationship between epithelial cancers and their microenvironment. [14] This is particularly relevant in breast and prostate cancers where non-invasive or low grade cancers may remain dormant for many years, failing to invade and metastasize.[57] Historically, cancer research has focused on the cancer cell and not the microenvironment in which it arises, proliferates and then invades.
A wide range of host lifestyle factors may influence the biological aggressiveness of cancers, as well as the likelihood of their metastasis.[8] Relevant factors considered in this context include obesity, diabetes, hypertension,[916] as well as regular physical activity and alcohol consumption.[1720] There is increasing interest in chronically used medications that may influence the risk for, as well as progression of cancer, e.g. aspirin, non-steroidal anti-inflammatory medications, statins, and metformin.[2126] Chronic inflammation in the tissue microenvironment has been proposed as a potential unifying mechanism for many of these host factors affecting the progression or inhibition of cancer.[27] Further, preclinical models in ovarian and breast cancer suggest a possible role for stress as a factor influencing inflammatory processes in the tumor microenvironment that may lead to earlier dissemination of tumors, working through the complex signaling between adrenergic receptors in the tumor and macrophages that are recruited in response.[2832] This process can be successfully blocked through administration of a commonly used non-selective beta 2 adrenergic antagonist, propanolol, suggesting a potential pharmacological strategy for prevention of cancer metastases.[30]
Two recent reports in women with breast cancer (BC) suggest that receipt of beta blockers (BB) reduces the risk for BC recurrence and improves survival.[33,34] Preclinical studies suggest a favorable biological role of angiotensin converting enzyme inhibitors (ACEi) in the development and progression of cancer,[35,36] although clinical data have been mixed [3739] The Life After Cancer Epidemiology (LACE) Study [40] includes a well-described cohort of BC patients in whom detailed pharmacy records were available from the year prior to and after the diagnosis of BC. We used this cohort to examine risks for BC recurrence, cause-specific mortality, and overall mortality in relation to BB and ACEi exposure, controlling for relevant medical, demographic and comorbid prognostic factors.
Study Population
The LACE Study cohort contained 2,269 women with early stage invasive BC diagnosed between 1997 and 2000 and recruited primarily from the Kaiser Permanente Northern California (KPNC) Cancer Registry (83%) and the Utah Cancer Registry (12%) from 2000 to 2002. Further details are provided elsewhere. [40] For this evaluation, only patients enrolled from KPNC and in whom pharmacy records were available were included. We also required complete data on tumor characteristics, cancer treatment, pre-diagnosis body mass index (BMI), comorbidities, cancer recurrence and pharmacy medication records, which yielded 1,779 in the final analysis cohort. Mean follow-up time for this sample was 8.2 years. Participants provided informed consent for the study, which was reviewed by the institutional review board of the Kaiser Permanente Division of Research.
Clinical and Pharmacy Data Base Information
Clinical information was obtained through electronic data sources available from KPNC and confirmed by medical record review. Data included tumor size, number of positive lymph nodes, hormone receptor status, and treatment (i.e. surgery, chemotherapy, radiation therapy, and hormone therapy). Tumor stage was calculated according to criteria of the American Joint Committee on Cancer (third edition). Data on race, menopausal status, hypertension, diabetes, menopausal status, and pre-diagnosis BMI were obtained from the mailed baseline questionnaire. Information on medications was obtained from the KPNC electronic pharmacy database, which records each dispensed outpatient prescription and includes information on the date a prescription was dispensed and the drug name, dose, quantity and days supplied.
Outcome Ascertainment
Health outcomes in the LACE cohort were monitored through semi-annual questionnaires through the first five years of follow-up and then annually thereafter. These questionnaires asked about any events that might have occurred in the preceding time interval, including recurrences or new primary BC, other cancers, and hospitalizations. Those reporting an event were contacted by telephone for an interview to provide more details and medical records were reviewed to verify reported outcomes. All reported deaths from any cause, including date, were confirmed by death certificate as well as KPNC electronic data sources.
Three outcomes were considered. Breast cancer recurrence includes a loco-regional cancer recurrence, distant recurrence or metastasis, and the development of a contralateral breast cancer. Cause-specific mortality includes death attributable to BC as a primary or underlying cause on the death certificate. Overall death includes death from any cause including BC. These outcomes were last updated November 10, 2010.
Statistical Analysis
Comparisons of baseline cohort characteristics by ACEi and BB use were conducted using Pearson chi-square and Kruskal-Wallis (K-W) tests. Follow-up began at date of study entry and ended at date of first confirmed BC recurrence or date of death, depending on the specific analysis. Individuals who did not have an event were censored at date of last contact. Hazard ratios (HR) and 95% confidence intervals (CI) representing the association between a defined event and medication use were computed adjusting for covariates using the delayed-entry Cox proportional hazards model. Covariates included in the main models were: age at diagnosis, race, stage of disease, pre-diagnosis BMI, adjuvant treatment, hormone receptor status, tamoxifen use, and self-reported hypertension and diabetes, as specified in Table 1.
Table 1
Table 1
Demographic and Tumor Characteristics by Angiotensin Converting Enzyme Inhibitor (ACEi) and Beta Blocker (BB) Use
Sensitivity analyses were conducted to examine whether observed associations with BC recurrence, BC-specific mortality and all-cause mortality were strengthened with increasing duration of use of BB and ACEi. Although power was limited by small numbers, such a pattern would be supportive of a causal association. In these exploratory analyses, duration of BB alone and use of ACEi alone were categorized as none, ≤ 300, 301– 700, and > 700 days of supply in the year prior to or after BC diagnosis. We included the same covariates as those in the main models. Given patients who used ACEi more frequently had 4+ lymph nodes, we also examined potential confounding by number of positive lymph nodes.
Characteristics of Study Sample
Table 1 shows the characteristics of the LACE study sample according to exposure to ACEi, BB, or the combination of ACEi and BB. Sixty-one percent of the sample were age 55 or older at cohort entry, and those using the drugs of interest were significantly older (p<0.0001). However, there were no significant differences in stage or race by drug exposure. Not surprisingly, use of ACEi and BB medications were more frequent among those with hypertension and diabetes. Postmenopausal women were more likely to be exposed to these drugs (p<0.0001), reflecting the older age of those taking these drugs, and chemotherapy was less frequently used in those exposed to either ACEi or BB (p=0.001).
Completeness of pharmacy data and types of medication
There were 1,372 patients who did not have a prescription filled for either a BB or and ACEi in the year prior to or year after BC diagnosis. Of the 407 patients who filled one or more prescriptions for a BB or ACEi during this period, 66 patients filled a prescription for both, 137 filled a prescription for ACEi only and 204 filled a prescription for BB only. The majority of BB prescriptions were for beta-1-selective antagonists, with approximately 74% of fills for atenolol and 8% for metoprolol. Propanolol was the only non-selective beta blocker used with any frequency (14% of all BB prescriptions). The majority of ACEi prescription fills were for the first generation medications: 85% for lisinopril, 10% for prinivil, and the remaining 5% for other ACEi. Among those using ACEi, 72% used both before and after their BC diagnosis; among the users of BB, before and after use occurred in approximately 70%.
Breast Cancer Recurrence
There were 292 BC recurrences among 1,779 in the LACE cohort at this analysis. In the model examining BC recurrence, controlling for important covariates, ACEi was significantly associated with a greater hazard of recurrence (HR = 1.56, 95% CI 1.02, 2.39; p=.04) (see Table 2). BB exposure was not statistically significantly associated with recurrence, although the HR was 0.86 and the combination of ACEi and BB exposure had an intermediate HR of 1.14. When this same analysis was restricted to patients with a diagnosis of hypertension (sample size 569 with 107 events), ACEi use was still associated with an increased HR of 1.77 (95% CI 1.10, 2.85) with p=0.02 (data not shown). The pattern for BB exposure was similar to the full model, and was not statistically significantly associated with the HR.
Table 2
Table 2
Breast Cancer Recurrence (n=292 events)
Other covariates that were significantly associated with greater hazard of BC recurrence in this model (Table 2) included older age and higher stage, while Hispanic race was associated with significantly lower hazard of recurrence. In the analysis restricted to patients with a diagnosis of hypertension, age was no longer significant in the model while stage and Hispanic race remained significant (data not shown).
Cause specific mortality
There were 174 BC deaths among 1,779 women. Neither exposure to ACEi or BB was associated with hazard of BC deaths in this sample, although the event rate was low (see Table 3). As in the previous model for recurrence, older age was associated with a greater hazard of death, as was more advanced stage, and combined use of chemotherapy and radiation as initial therapy. Hispanic race women had a lower hazard of BC specific death.
Table 3
Table 3
Breast Cancer Cause-Specific Mortality (n=174 events)
All cause mortality and sensitivity analyses
There were 323 deaths among 1,779 women. For this model, the combined use of ACEi and BB were associated with significantly greater hazard of death (HR 1.94, 95% CI 1.22, 3.10; p=0.01), while individually, neither ACEi nor BB therapy affected this outcome (see Table 4). Hispanic race women continued to show a significantly lower hazard of death, along with those who received chemotherapy, while advanced stage and older age were associated with a greater hazard of death (see Table 4). When the model was restricted to only those with a hypertension diagnosis (event rate 136 among 569 women), only stage II cancer, diabetes, and treatment with combined ACEi and BB were associated with an increased hazard of death, with parameter estimates and p-values similar in magnitude to the full model (data not shown). When the model was restricted to those with hypertension who were less than 70 years (65 events among 384 women), the risk associated with combined ACEi and BB was no longer statistically significant (data not shown).
Table 4
Table 4
All cause mortality (n=323 events)
In sensitivity analyses, there was no pattern of increasing risk of recurrence, BC-specific mortality or overall mortality with increasing days of supply of ACEi medication in the year prior to or after BC diagnosis (data not shown). In contrast, there was a pattern of decreasing risk of each of these endpoints with decreasing days supply of BB (data not shown). Adding number of positive lymph nodes to our models only modestly attenuated our HR estimates. For example, the HR for BC recurrence associated with ACEi went from 1.56 (95% CI 1.02, 2.39) to 1.43 (95% CI 0.93, 2.19).
There will be a dramatic increase in the number of BC cases based on the aging of the population of US women. Standard risk factors for recurrence and prognosis focus on the tumor stage and the biological characteristics of the tumor, [41,42] as well as the receipt of appropriate adjuvant therapies. The extent to which other comorbid conditions and their associated medications influence BC recurrence and mortality is an area of recent interest.[13,14,26,4345] Factoring these exposures into BC recurrence prediction may be important and potentially affect follow-up care. In addition, medications that are implicated in the prevention of recurrence may become candidates for use in primary prevention and adjuvant therapy settings. [26,44,46]
The findings from the LACE cohort provide a window on the biology of BC recurrence in a diverse population of women who are insured and have access to care in a group model health maintenance organization, with access to both specialist and generalist care. In this setting, there is no evidence of racial disparity in BC outcomes for Black women controlling for cancer specific variables (stage, treatment), demographic and chronic disease variables (age, obesity, diabetes, hypertension), as well as the medications studied. Consistent with an expanding literature on host lifestyle factors, diabetes was significantly associated with greater hazard for overall mortality, as in the general population of women. However, in this patient sample there was no association of diabetes with BC recurrence or cause-specific mortality. Among other findings, being overweight or obese was not statistically significantly associated with recurrence, cause-specific mortality or mortality, which likely relates to the access to care in this setting as well as the control for other chronic disease variables that may be in the causal pathway.
What about the relationship between the pharmacological agents studied and the risk for BC recurrence? We did not find a statistically significant relationship between use of BB and any of the BC outcomes. This evaluation is hampered by the small number of women who took a non-selective BB, i.e. propanolol (14% of BB sample), which would be the best therapeutic agent to affect the beta-2-adrenergic receptor implicated as a therapeutic target in BC metastasis preclinical models.[30] While one recent study has suggested clinical benefit from both selective beta 1 adrenergic antagonists as well as non-selective BB therapy,[33] another study of a large BC sample only found benefit in women receiving a non-selective BB.[34] In our analyses, it is noteworthy that women receiving BB therapy had lower HR for recurrence and cause- specific mortality, although these findings were not statistically significant given the low event rate in the LACE cohort. In contrast, we found that use of ACEi therapy was associated with an increased hazard of recurrence (HR 1.56, 95% CI 1.02, 2.39, p=0.04), but not for cause-specific mortality or overall mortality. Interestingly, patients on both a BB and an ACEi did not have an increased hazard of recurrence (HR 1.14, 95% CI 0.61, 2.14, p=0.69), suggesting that the addition of the BB to ACEi therapy may have a beneficial effect on recurrence.
The present data indicate divergent effects of two commonly prescribed anti-hypertensive medication classes (BB and ACEi) on the risk of BC recurrence. Such results and those from previous BB studies [33,34] suggest that the observed alterations in recurrence risk are unlikely to stem from reductions in hypertension per se, and instead likely reflect differences in the biological pathways through which those agents act. Preclinical studies suggest that BBs can influence the progression of solid epithelial tumors (including experimental BC) by inhibiting macrophage recruitment and neovascularization within the primary tumor. [29,30] Those effects are mediated predominately by inhibition of beta-2 adrenergic receptor signaling in tumor cells, vascular endothelial cells, and monocyte/macrophages, resulting in reduced signal transduction to support the expression of pro-metastatic and pro-angiogenic genes. [29,30] Beta adrenergic signaling may also support the survival of disseminated carcinoma cells (anoikis). [47] The reduced BC recurrence observed here in BB-treated patients, although not reaching statistical significance in this cohort, is thus consistent with BB biological processes observed in preclinical experimental data and other BB epidemiological studies in BC. [33,34]
In contrast, the mechanisms by which ACEi might increase BC recurrence are more obscure. Such effects are unlikely to stem from antihypertensive effects per se, and more likely to involve the specific biology of angiotensin and its receptor system. Angiotensin is therapeutically manipulated chiefly to modulate vasoconstriction, but this oligopeptide has a diverse array of other physiologic effects on other aspects cardiovascular function, neural function (including brain regulation of thirst and salt balance, and peripheral sympathetic norepinephrine outflow), and aldosterone production by the adrenal cortex. The increased hazard of BC recurrence observed here in ACEi-treated patients is consistent with previous reports linking these drugs to inflammation;[48,49] however, most studies of ACEi, as well as a recent study of angiotensin receptor blocker (ARB) exposure have focused on cancer incidence rather than progression or metastases.[5052] Given that ACEi and ARB medications target different specific molecules but are associated with similar effects on cancer risk, there could be a specific protective effect of angiotensin signaling on BC-related biology. Identifying the biological mechanisms by which BC biology is regulated by angiotensin signaling and its pharmacologic modulation by ACEi medications represents an important area for further preclinical research.
Strengths of this study include careful case ascertainment and follow-up for disease recurrence and mortality in the LACE cohort, an ethnically diverse patient sample, and access to a pharmacy database capturing medication use before and after BC diagnosis. Without the latter, questions related to potential benefits or harms of BB and ACEi therapy could not have been examined. However, caution should be used in interpreting the drug exposure findings, as we cannot exclude confounding of medication use with indication (e.g., heart disease and ACEi) or other types of bias in this observational study setting. In addition, there are other limitations that relate specifically to the cohort, including access to treatment for many chronic conditions that might favorably influence survival and BC specific outcomes. These access factors may have influenced the lack of survival disparities for Black women, although we may have reduced potential for observing disparities by controlling for diabetes and hypertension which are more prevalent in Black women.
Nevertheless, the findings from this study are provocative, and raise concerns about the potential harm of commonly prescribed ACEi therapy. Although the low event rates and small number of patients on BB limited our power to detect the potential benefits of individual BB medications, the main findings for BB are consistent with the hypothesis that this class of drugs may be risk reducing. However, our sensitivity analysis findings of decreasing risk with decreasing days of supply of medication, while only exploratory due to sample size, would argue against a causal association. Finally, the findings of an association of ACEi exposure with poor outcomes are hypothesis generating only, as they were not specified a priori, and were in fact counter to suggestions in the literature. Thus, they need further corroboration in other clinical databases and, if confirmed, their potential mechanism for adverse outcomes needs more detailed examination in the laboratory.
Acknowledgements
Funding for the conduct of this research: Ganz (the Breast Cancer Research Foundation, the Jonsson Comprehensive Cancer Center Foundation, R01CA109650), Habel (R01 CA98838 and R01 CA129059), Weltzien (R01 CA129059), Caan (R01 CA129059), Cole (R01 CA116778)
Footnotes
None of the authors have any financial disclosures or conflicts of interest to report.
Author contributions: Dr. Habel and Ms. Weltzien had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data and the accuracy of the data analysis.
Study Concept and Design: Ganz, Habel, Cole
Acquisition of data: Caan
Analysis and interpretation of data: Ganz, Habel, Weltzien, Caan, Cole
Drafting of the manuscript: Ganz, Habel, Weltzien
Critical revision of the manuscript: Ganz, Habel, Weltzien, Caan, Cole
Statistical Analysis: Habel, Weltzien
Contributor Information
Patricia A. Ganz, UCLA Schools of Public Health and Medicine, Jonsson Comprehensive Cancer Center, Los Angeles, California.
Laurel A. Habel, Division of Research, Kaiser Permanente, Northern California, Oakland, CA.
Erin K. Weltzien, Division of Research, Kaiser Permanente, Northern California, Oakland, CA.
Bette J. Caan, Division of Research, Kaiser Permanente, Northern California, Oakland, CA.
Steven W. Cole, UCLA School of Medicine, Jonsson Comprehensive Cancer Center, Los Angeles, California.
1. Chiang AC, Massague J. Molecular Basis of Metastasis. New Engl J Med. 2008;359:2814–2823. [PubMed]
2. McAllister SS, Weinberg RA. Tumor-Host Interactions: A Far-Reaching Relationship. J Clin Oncol. 2010;28:4022–4028. [PubMed]
3. Chung LWK, Baseman A, Assikis V, Zhau HE. Molecular Insights into Prostate Cancer Progression: The Missing Link of Tumor Microenvironment. The Journal of Urology. 2005;173:10–20. [PubMed]
4. Udagawa T, Wood M. Tumor-stromal cell interactions and opportunities for therapeutic intervention. Current Opinion in Pharmacology. 2010;10:369–374. [PubMed]
5. Esserman L, Shieh Y, Thompson I. Rethinking Screening for Breast Cancer and Prostate Cancer. JAMA. 2009;302:1685–1692. [PubMed]
6. Welch HG, Black WC. Overdiagnosis in Cancer. J Natl Cancer Inst. 2010;102:605–613. [PubMed]
7. Esserman L, Thompson I. Solving the Overdiagnosis Dilemma. J Natl Cancer Inst. 2010;102:582–583. [PubMed]
8. Goodwin PJ, Meyerhardt JA, Hursting SD. Host Factors and Cancer Outcome. J Clin Oncol. 2010;28:4019–4021. [PubMed]
9. Caan B, Kwan M, Hartzell G, et al. Pre-diagnosis body mass index, post-diagnosis weight change, and prognosis among women with early stage breast cancer. Cancer Causes and Control. 2008;19:1319–1328. [PMC free article] [PubMed]
10. Goodwin PJ, Boyd NF. Body size and breast cancer prognosis: a critical review of the evidence. Breast Cancer Res Treat. 1990;16:205–214. [PubMed]
11. Goodwin PJ, Ennis M, Pritchard KI, et al. Fasting Insulin and Outcome in Early-Stage Breast Cancer: Results of a Prospective Cohort Study. J Clin Oncol. 2002;20:42–51. [PubMed]
12. Goodwin PJ. Weight Gain in Early-Stage Breast Cancer: Where Do We Go From Here? J Clin Oncol. 2001;19:2367–2369. [PubMed]
13. Largent J, Bernstein L, Horn-Ross P, et al. Hypertension, antihypertensive medication use, and breast cancer risk in the California Teachers Study cohort. Cancer Causes and Control. 2010;21:1615–1624. [PMC free article] [PubMed]
14. Emaus A, Veierød MB, Tretli S, et al. Metabolic profile, physical activity, and mortality in breast cancer patients. Breast Cancer Research and Treatment. 2010;121:651–660. [PubMed]
15. Kroenke CH, Chen WY, Rosner B, Holmes MD. Weight, Weight Gain, and Survival After Breast Cancer Diagnosis. J Clin Oncol. 2005;23:1370–1378. [PubMed]
16. Peairs KS, Barone BB, Snyder CF, et al. Diabetes Mellitus and Breast Cancer Outcomes: A Systematic Review and Meta-Analysis. J Clin Oncol. 2011;29:40–46. [PMC free article] [PubMed]
17. McTiernan A, Irwin M, VonGruenigen V. Weight, Physical Activity, Diet, and Prognosis in Breast and Gynecologic Cancers. J Clin Oncol. 2010;28:4074–4080. [PMC free article] [PubMed]
18. Holmes MD, Chen WY, Feskanich D, Kroenke CH, Colditz GA. Physical Activity and Survival After Breast Cancer Diagnosis. JAMA. 2005;293:2479–2486. [PubMed]
19. Kwan ML, Kushi LH, Weltzien E, et al. Alcohol Consumption and Breast Cancer Recurrence and Survival Among Women With Early-Stage Breast Cancer: The Life After Cancer Epidemiology Study. J Clin Oncol. 2010;28:4410–4416. [PMC free article] [PubMed]
20. Rock CL, Demark-Wahnefried W. Nutrition and Survival After the Diagnosis of Breast Cancer: A Review of the Evidence. J Clin Oncol. 2002;20:3302–3316. [PMC free article] [PubMed]
21. Holmes MD, Chen WY, Li L, Hertzmark E, Spiegelman D, Hankinson SE. Aspirin Intake and Survival After Breast Cancer. J Clin Oncol. 2010;28:1467–1472. [PMC free article] [PubMed]
22. Kwan M, Habel L, Slattery M, Caan B. NSAIDs and breast cancer recurrence in a prospective cohort study. Cancer Causes and Control. 2007;18:613–620. [PMC free article] [PubMed]
23. Bonovas S, Filioussi K, Tsavaris N, Sitaras NM. Use of Statins and Breast Cancer: A Meta-Analysis of Seven Randomized Clinical Trials and Nine Observational Studies. J Clin Oncol. 2005;23:8606–8612. [PubMed]
24. Kwan M, Habel L, Flick E, Quesenberry C, Caan B. Post-diagnosis statin use and breast cancer recurrence in a prospective cohort study of early stage breast cancer survivors. Breast Cancer Research and Treatment. 2008;109:573–579. [PMC free article] [PubMed]
25. Bosco JLF, Antonsen S, Sørensen HT, Pedersen L, Lash TL. Metformin and Incident Breast Cancer among Diabetic Women: A Population-Based Case-Control Study in Denmark. Cancer Epidemiology Biomarkers & Prevention. 2011;20:101–111. [PubMed]
26. Goodwin P, Stambolic V, Lemieux J, et al. Evaluation of metformin in early breast cancer: a modification of the traditional paradigm for clinical testing of anti-cancer agents. Breast Cancer Research and Treatment. 2010:1–6. [PubMed]
27. Antoni MH, Lutgendorf SK, Cole SW, et al. The influence of bio-behavioural factors on tumour biology: pathways and mechanisms. Nat Rev Cancer. 2006;6:240–248. [PMC free article] [PubMed]
28. Lutgendorf SK, Sood AK, Antoni MH. Host Factors and Cancer Progression: Biobehavioral Signaling Pathways and Interventions. J Clin Oncol. 2010;28:4094–4099. [PMC free article] [PubMed]
29. Thaker PH, Han LY, Kamat AA, et al. Chronic stress promotes tumor growth and angiogenesis in a mouse model of ovarian carcinoma. Nat Med. 2006;12:939–944. [PubMed]
30. Sloan EK, Priceman SJ, Cox BF, et al. The Sympathetic Nervous System Induces a Metastatic Switch in Primary Breast Cancer. Cancer Res. 2010;70:7042–7052. [PMC free article] [PubMed]
31. Luthy IA, Bruzzone A, Perez Pinero C, et al. Adrenoreceptors: Non Conventional Target for Breast Cancer? Current Medicinal Chemistry. 2009;16:1850–1862. [PubMed]
32. Lutgendorf SK, Lamkin DM, Jennings NB, et al. Biobehavioral Influences on Matrix Metalloproteinase Expression in Ovarian Carcinoma. Clin Cancer Res. 2008;14:6839–6846. [PMC free article] [PubMed]
33. Powe DG, Voss MJ, Zänker KS, et al. Beta-Blocker Drug Therapy Reduces Secondary Cancer Formation in Breast Cancer and Improves Cancer Specific Survival. Oncotarget Advance Publications. 2010 October 19; www.impactjournals.com/oncotarget. [PMC free article] [PubMed]
34. Barron TI, Connolly RM, Visvanathan K, et al. Association between Propanolol Use and Both Breast Cancer Incidence and Mortality; San Antonio Breast Cancer Symposium; 2010. Abstract.
35. Deshayes F, Nahmias C. Angiotensin receptors: a new role in cancer? Trends in Endocrinology and Metabolism. 2005;16:293–299. [PubMed]
36. George AJ, Thomas WG, Hannan RD. The rennin-angiotensin system and cancer: old dog, new tricks. Nat Rev Cancer. 2010;10:745–759. [PubMed]
37. Lever AF, Hole DJ, Gillis CR, et al. Do inhibitors of angiotensin-I-converting enzyme protect against risk of cancer? The Lancet. 1998;352:179–184. [PubMed]
38. Bangalore S, Kumar S, Kjeldsen SE, et al. Antihypertensive drugs and risk of cancer: network meta-analyses and trial sequential analyses of 324,168 participants from randomised trials. The Lancet Oncology. 2011;12:65–82. [PubMed]
39. Rosenthal T, Gavras I. Angiotensin inhibition and malignancies: a review. J Hum Hypertens. 2009;23:623–635. [PubMed]
40. Caan B, Sternfeld B, Gunderson E, Coates A, Quesenberry C, Slattery ML. Life After Cancer Epidemiology (LACE) Study: A cohort of early stage breast cancer survivors (United States) Cancer Causes and Control. 2005;16:545–556. [PubMed]
41. Paik S, Shak S, Tang G, et al. A Multigene Assay to Predict Recurrence of Tamoxifen-Treated, Node-Negative Breast Cancer. N Engl J Med. 2004;351:2817–2826. [PubMed]
42. Sorlie T, Tibshirani R, Parker J, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. PNAS. 2003;100:8418–8423. [PubMed]
43. Goodwin P. Metabolic Syndrome, Insulin Resistance, and Inflammation in Breast Cancer: Impact on Prognosis and Adjuvant Interventions. Current Breast Cancer Reports. 2010;2:182–189.
44. Cazzaniga M, Bonanni B, Guerrieri-Gonzaga A, Decensi A. Is it Time to Test Metformin in Breast Cancer Clinical Trials? Cancer Epidemiology Biomarkers & Prevention. 2009;18:701–705. [PubMed]
45. Decensi A, Gennari A. Insulin Breast Cancer Connection: Confirmatory Data Set the Stage for Better Care. J Clin Oncol. 2011;29:7–10. [PubMed]
46. Schuller HM. Beta-adrenergic signaling, a novel target for cancer therapy? Oncotarget advance publication online. 2010 November 11; [PMC free article] [PubMed]
47. Sood AK, Armaiz-Pena GN, Halder J, et al. Adrenergic modulation of focal adhesion kinase protects human ovarian cancer cells from anoikis. J Clin Invest. 2010;120:1515–1523. [PMC free article] [PubMed]
48. Kaplan AP, Joseph K, Silverberg M. Pathways for bradykinin formation and inflammatory disease. J Allergy Clin Immunol. 2002;109:195–209. [PubMed]
49. Johnsen SrP, Jacobsen J, Monster TBM, Friis Sr, McLaughlin JK, Sørensen HT. Risk of first-time hospitalization for angioedema among users of ACE inhibitors and angiotensin receptor antagonists. The American Journal of Medicine. 2005;118:1428–1429. [PubMed]
50. Friis S, Sørensen HT, Mellemkjaer L, McLaughlin JK, Nielsen GL, Blot WJ, et al. Angiotensin-converting enzyme inhibitors and the risk of cancer. Cancer. 2001;92:2462–2470. [PubMed]
51. Fryzek J, Poulsen A, Lipworth L, et al. A Cohort Study of Antihypertensive Medication Use and Breast Cancer Among Danish Women. Breast Cancer Research and Treatment. 2006;97:231–236. [PubMed]
52. Sipahi I, Debanne SM, Rowland DY, Simon DI, Fang JC. Angiotensin-receptor blockade and risk of cancer: meta-analysis of randomised controlled trials. The Lancet Oncology. 2010;11:627–636. [PubMed]