the long-term use of calcium channel blockers and the risk ... · the long-term use of calcium...

12
The Long-term Use of Calcium Channel Blockers and the Risk of Breast Cancer. NOYCIA 2015 Sara Soldera 1 , Nathaniel Bouganim 1 , Jamil Asselah 1 , Hui Yin 2 , Ralph Maroun 1 and Laurent Azoulay 2 Department of Oncology, McGill University Health Center 1 and Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital 2, , Montreal, QC

Upload: others

Post on 20-Apr-2020

1 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: The Long-term Use of Calcium Channel Blockers and the Risk ... · The Long-term Use of Calcium Channel Blockers and the Risk of Breast Cancer. NOYCIA 2015 Sara Soldera1, Nathaniel

The Long-term Use of Calcium Channel

Blockers and the Risk of Breast Cancer.

NOYCIA 2015

Sara Soldera1, Nathaniel Bouganim1, Jamil Asselah1,

Hui Yin2, Ralph Maroun1 and Laurent Azoulay2

Department of Oncology, McGill University Health Center1 and Centre for Clinical Epidemiology,

Lady Davis Institute, Jewish General Hospital2,, Montreal, QC

Page 2: The Long-term Use of Calcium Channel Blockers and the Risk ... · The Long-term Use of Calcium Channel Blockers and the Risk of Breast Cancer. NOYCIA 2015 Sara Soldera1, Nathaniel

Background

• Calcium channel blockers (CCB) are

widely used in the treatment of various

cardiovascular conditions.

• Their safety remains controversial, with

studies associating their use with several

adverse events, including breast cancer.

Page 3: The Long-term Use of Calcium Channel Blockers and the Risk ... · The Long-term Use of Calcium Channel Blockers and the Risk of Breast Cancer. NOYCIA 2015 Sara Soldera1, Nathaniel

Objective

• The objective of this study was to

determine whether the use of CCB is

associated with an increased risk of breast

cancer overall, and to assess whether this risk varies with cumulative duration of use.

Page 4: The Long-term Use of Calcium Channel Blockers and the Risk ... · The Long-term Use of Calcium Channel Blockers and the Risk of Breast Cancer. NOYCIA 2015 Sara Soldera1, Nathaniel

Methods

• A cohort of 273,152 women newly treated with antihypertensive drugs between January 1, 1995 and December 31, 2009, followed until December 31, 2010, was identified using the UK Clinical Practice Research Datalink.

• A Cox proportional hazards model using a time-varying CCB exposure definition, lagged by one year for latency and reverse causality considerations, was used to estimate adjusted hazard ratios (HR) with 95% confidence intervals (CI) of incident breast cancer.

Page 5: The Long-term Use of Calcium Channel Blockers and the Risk ... · The Long-term Use of Calcium Channel Blockers and the Risk of Breast Cancer. NOYCIA 2015 Sara Soldera1, Nathaniel

Methods (2)

• A secondary analysis was conducted to

assess whether the risk varied with

cumulative duration of use.

• All models were adjusted for various

potential confounders.

Page 6: The Long-term Use of Calcium Channel Blockers and the Risk ... · The Long-term Use of Calcium Channel Blockers and the Risk of Breast Cancer. NOYCIA 2015 Sara Soldera1, Nathaniel

Results

• During 1,567,104 person-years of follow-up, 4520 women were newly-diagnosed with breast cancer.

• Compared with other antihypertensive drugs, the use of CCB was not associated with an increased risk of breast cancer.

• In a secondary analysis, the risk did not vary according to cumulative duration of use.

Page 7: The Long-term Use of Calcium Channel Blockers and the Risk ... · The Long-term Use of Calcium Channel Blockers and the Risk of Breast Cancer. NOYCIA 2015 Sara Soldera1, Nathaniel

Characteristic Calcium channel blockers

Use No use

Total 107,337 165,815

Age, years (mean, SD) 62.6 (14.3) 58.0 (16.2)

Excessive alcohol use, n (%) 3,337 (3.1) 5,757 (3.5)

Smoking status, n (%)

Ever 37,033 (34.5) 59,456 (35.9)

Never 56,881(53.0) 86,944 (52.4)

Unknown 13,423 (12.5) 19,415 (11.7)

Body mass index, n (%)

<18.5 kg/m2 1,620 (1.5) 2,345 (1.4)

18.5-25 kg/m2 22,899 (21.3) 35,729 (21.6)

25-30 kg/m2 23,463 (21.9) 33,781 (20.4)

≥30.0 kg/m2 19,701 (18.4) 30,032 (18.1)

Unknown 39,654 (36.9) 63,928 (38.6)

Previous mammography screening, n (%) 94,909 (32.5) 46,910 (28.3)

Previous cancer, n (%) 6,958 (6.5) 10,619 (6.4)

Oophorectomy, n (%) 2,788 (2.6) 4,034 (2.4)

Anti-diabetic agents, n (%)

Metformin 3,121 (2.9) 6,173 (3.7)

Sulfonylureas 2,794 (2.6) 4,298 (2.6)

Thiazolidinediones 299 (0.3) 958 (0.6)

Insulins 1,359 (1.3) 2,791 (1.7)

Other anti-diabetic drugs 358 (0.3) 505 (0.3)

Aspirin, n (%) 18,015 (16.8) 25,423 (15.3)

Other NSAID, n (%) 51,501 (48.0) 80,048 (48.3)

Statins, n (%) 11,894 (11.1) 19,107 (11.5)

Hormone replacement therapy, n (%) 25,421 (23.7) 45,004 (27.1)

Oral contraceptives, n (%) 11,733 (10.9) 32,259 (19.5)

Antihypertensive drugs at cohort entry

Calcium channel blockers, monotherapy, n (%) 31,672 (29.5) 0 (0.0)

Beta-blockers, monotherapy, n (%) 19,348 (18.0) 42,851 (25.8)

Diuretics, monotherapy, n (%) 36,843 (34.3) 71,968 (43.4)

ACE inhibitors, monotherapy, n (%) 10,774 (10.0) 25,237 (15.2)

ARBs, monotherapy, n (%) 1,183 (1.1) 2,811 (1.7)

Other antihypertensive drugs, monotherapy, n (%) 1,512 (1.4) 16,182 (9.8)

Calcium channel blockers in combination, n (%) 3,328 (3.1) 0 (0.0)

Other combinations, n (%) 2,677 (2.5) 6,766 (4.1)

Table 1. Baseline demographics and

clinical characteristics according to use

of CCB

Page 8: The Long-term Use of Calcium Channel Blockers and the Risk ... · The Long-term Use of Calcium Channel Blockers and the Risk of Breast Cancer. NOYCIA 2015 Sara Soldera1, Nathaniel

Conventional adjustment Time-varying adjustment

CCB use Events Person-

years Incidence rate

(95% CI) Crude HR HR (95% CI)

Marginal structural model HR (95% CI)

No use 3002 1,075,336 2.8 (2.7 to 2.9) 1 1.00 [Reference] 1.00 [Reference]

Use 1518 491,768 3.1 (2.9 to 3.2) 1.08 0.96 (0.90 to 1.03) 0.97 (0.89 to 1.05)

Table 2. Crude and adjusted HR for the association between the use of CCB and the risk

of breast cancer

Page 9: The Long-term Use of Calcium Channel Blockers and the Risk ... · The Long-term Use of Calcium Channel Blockers and the Risk of Breast Cancer. NOYCIA 2015 Sara Soldera1, Nathaniel

CCBs exposure Events Person-

years

Incidence rate

(95% CI) Crude HR Adjusted HR (95% CI)

No use 3,002 1,075,336 2.8 (2.7 to 2.9) 1 1.00 [Reference]

CCB use, years

< 5 years 1,302 431,598 3.0 (2.9 to 3.2) 1.06 0.96 (0.90 to 1.03)

5 to 10 years 207 56,192 3.7 (3.2 to 4.2) 1.22 1.05 (0.90 to 1.22)

≥ 10 years 9 3,978 2.3 (1.0 to 4.3) 0.73 0.61 (0.32 to 1.20)

p-trend = 0.25

Long- and short-acting

Short-acting 119 43,070 2.8 (2.3 to 3.3) 0.98 1.03 (0.85 to 1.24)

Long-acting 1,291 414,139 3.1 (2.9 to 3.3) 1.09 0.96 (0.90 to 1.03)

Both 108 34,559 3.1 (2.6 to 3.8) 1.06 0.95 (0.79 to 1.16)

Dihydropyridines

Dihydropyridines 1,246 412,671 3.0 (2.9 to 3.2) 1.05 0.95 (0.88 to 1.02)

Non-dihydropyridines 191 54,975 3.5 (3.0 to 4.0) 1.22 1.12 (0.96 to 1.30)

Both 81 24,122 3.4 (2.7 to 4.2) 1.13 0.96 (0.77 to 1.21)

Table 3. Crude and adjusted HR for secondary analyses between CCB and the risk of

breast cancer

Page 10: The Long-term Use of Calcium Channel Blockers and the Risk ... · The Long-term Use of Calcium Channel Blockers and the Risk of Breast Cancer. NOYCIA 2015 Sara Soldera1, Nathaniel

Discussion Strengths

• One of the largest observational studies investigating this question

• Use of new-user cohort eliminated biases related to the inclusion of prevalent users

• Models adjusted for multiple potential confounders

• Exposure definition considered latency and reverse causality, with sensitivity analyses yielding consistent results

Limitations

• Prescriptions issued by general practitioners; misclassification of exposure possible if non compliance or treatment by specialist

• Observational nature of the study; possible residual confounders

• Secondary analysis powered to rule out an increased risk of at least 20% in patients who used CCB for more than 10 years, which is below the point estimates observed in the study reporting an increased risk of breast cancer after more than 10 years of CCB use

Page 11: The Long-term Use of Calcium Channel Blockers and the Risk ... · The Long-term Use of Calcium Channel Blockers and the Risk of Breast Cancer. NOYCIA 2015 Sara Soldera1, Nathaniel

Conclusion

• The results of this large population-based

study provide evidence that the use of

CCB is not associated with an increased

risk of breast cancer in women treated

with antihypertensive drugs.

• No association was observed according to

CCB subtype or by cumulative duration of

use.

Page 12: The Long-term Use of Calcium Channel Blockers and the Risk ... · The Long-term Use of Calcium Channel Blockers and the Risk of Breast Cancer. NOYCIA 2015 Sara Soldera1, Nathaniel

References 1. Li W, Shi Q, Wang W, Liu J, Li Q, Hou F. Calcium channel blockers and risk of breast cancer: a meta-analysis of 17 observational studies. PLoS One 2014;9:e105801.

2. Chen Q, Zhang Q, Zhong F, et al. Association between calcium channel blockers and breast cancer: a meta-analysis of observational studies. Pharmacoepidemiol Drug Saf 2014;23:711-8.

3. Pahor M, Guralnik JM, Ferrucci L, Corti MC, Salive ME, Cerhan JR et al. Calcium-channel blockade and incidence of cancer in aged populations. Lancet 1996;348:493-7.

4. Fitzpatrick AL, Daling JR, Furberg CD, Kronmal RA, Weissfeld JL. Use of calcium channel blockers and breast carcinoma risk in postmenopausal women. Cancer 1997;80:1438-47.

5. Li CI, Daling JR, Tang MT, et al. Use of antihypertensive medications and breast cancer risk among women aged 55 to 74 years. JAMA Intern Med 2013;173:1629-37.

6. Bergman GJ, Khan S, Danielsson B, Borg N. Breast cancer risk and use of calcium channel blockers using Swedish population registries. JAMA Intern Med 2014;174:1700-1.

7. Devore EE, Kim S, Ramin CA, Wegrzyn LR, Massa J, Holmes MD et al. Antihypertensive medication use and incident breast cancer in women. Breast Cancer Res Treat 2015;150:219-29.

8. Leung HW, Hung LL, Chan AL, Mou CH. Long-Term Use of Antihypertensive Agents and Risk of Breast Cancer: A Population-Based Case-Control Study. Cardiol Ther 2015.

9. Walley T, Mantgani A. The UK General Practice Research Database. Lancet 1997;350:1097-9.

10. Garcia Rodriguez LA, Perez GS. Use of the UK General Practice Research Database for pharmacoepidemiology. Br J Clin Pharmacol 1998;45:419-25.

11. National Health Service. Read codes. United Kingdom National Health Service [ 2012 [cited 2013 June 12]; Available from: URL:http://www.connectingforhealth.nhs.uk/systemsandservices/data/uktc/readcodes

12. Jick H, Jick SS, Derby LE. Validation of information recorded on general practitioner based computerised data resource in the United Kingdom. BMJ 1991;302:766-8.

13. Lawrenson R, Williams T, Farmer R. Clinical information for research; the use of general practice databases. J Public Health Med 1999;21:299-304.

14. Lawrenson R, Todd JC, Leydon GM, Williams TJ, Farmer RD. Validation of the diagnosis of venous thromboembolism in general practice database studies. Br J Clin Pharmacol 2000;49:591-6.

15. Jick SS, Kaye JA, Vasilakis-Scaramozza C, Garcia Rodriguez LA, Ruigomez A, Meier CR, et al. Validity of the general practice research database. Pharmacotherapy 2003;23:686-9.

16. Herrett E, Thomas SL, Schoonen WM, et al.. Validation and validity of diagnoses in the General Practice Research Database: a systematic review. Br J Clin Pharmacol 2010;69:4-14.

17. Li CI, Malone KE, Weiss NS, et al. Relation between use of antihypertensive medications and risk of breast carcinoma among women ages 65-79 years. Cancer 2003;98:1504-13.

18. Saltzman BS, Weiss NS, Sieh W, Fitzpatrick AL, McTiernan A, Daling JR et al. Use of antihypertensive medications and breast cancer risk. Cancer Causes Control 2013;24:365-71.

19. Robins JM, Hernan MA, Brumback B. Marginal structural models and causal inference in epidemiology. Epidemiology 2000;11:550-60.

20. Hernan MA, Brumback B, Robins JM. Marginal structural models to estimate the causal effect of zidovudine on the survival of HIV-positive men. Epidemiology 2000;11:561-70.

21. Cole SR, Hernan MA. Constructing inverse probability weights for marginal structural models. Am J Epidemiol 2008;168:656-64.

22. Greenland S. Dose-response and trend analysis in epidemiology: alternatives to categorical analysis. Epidemiology 1995;6:356-65.

23. Heinzl H, Kaider A, Zlabinger G. Assessing interactions of binary time-dependent covariates with time in cox proportional hazards regression models using cubic spline functions. Stat Med 1996;15:2589-601.

24. Ray WA. Evaluating medication effects outside of clinical trials: new-user designs. Am J Epidemiol 2003;158:915-20.

25. Boggon R, van Staa TP, Chapman M, et al. Cancer recording and mortality in the General Practice Research Database and linked cancer registries. Pharmacoepidemiol Drug Saf 2013;22:168-75.