Antihypertensive Treatment and Cancer: Umbrella Review of Meta-Analyses of Randomized Controlled Trials and Observational Studies
,
Abstract
Background: Data on the link between use of antihypertensive medications and the risk of developing or dying from cancer have uncertain credibility and certainty.
Objectives: We sought to evaluate the credibility of evidence from observational studies and the certainty of evidence from randomized controlled trials (RCTs) on the association between antihypertensive medication use and cancer risk, mortality, or survival outcomes.
Methods: Comprehensive searches were performed in PubMed, Embase, Scopus, and the Cochrane Database of Systematic Reviews from their creation through July 2024. The study included systematic reviews and meta-analyses of epidemiological research investigating the relationships between antihypertensive therapies and cancer risk, mortality, or survival outcomes. The credibility of evidence from observational studies was categorized as convincing, highly suggestive, suggestive, weak, or nonsignificant. Through the GRADE framework, the certainty of evidence from RCTs was categorized as high, moderate, low, or very low.
Results: A total of 109 meta-analyses were identified, with 90 originating from observational studies and 23 from RCTs. The observational studies provided highly suggestive evidence that calcium channel blockers (CCBs) and diuretics were associated with an increased cancer risk (equivalent odds ratio [eOR], 1.07; 95% CI, 1.04 to 1.10; and eOR, 1.15; 95% CI, 1.10 to 1.20, respectively). Evidence suggests that β-blockers are associated with an increase in cancer-specific survival (eOR, 0.78; 95% CI, 0.69 to 0.89). No association satisfied the standards for convincing evidence. Pooled analyses of RCTs determined that CCB use was associated with an increased cancer risk (eOR, 1.06; 95% CI, 1.01 to 1.12; moderate certainty).
Conclusions: No strong or consistent evidence was found to support a causal relationship between antihypertensive medications and cancer outcomes. The observed associations were of very small magnitude, suggesting limited clinical relevance.
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6. Heinonen O, Shapiro S, Tuominen L, Turunen M. Reserpine use in relation to breast cancer. The Lancet. 1974;304(7882):675-7.
7. Grossman E, Messerli F, Goldbourt U. Antihypertensive therapy and the risk of malignancies. European heart journal. 2001;22(15):1343-52.
8. 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(7):627-36.
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10. Copland E, Canoy D, Nazarzadeh M, Bidel Z, Ramakrishnan R, Woodward M, et al. Antihypertensive treatment and risk of cancer: an individual participant data meta-analysis. The Lancet Oncology. 2021 Apr 1;22(4):558-70.
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12. Statement from FDA Commissioner Scott Gottlieb, M.D., and Janet Woodcock, M.D., director of the Center for Drug Evaluation and Research on FDA's ongoing investigation into valsartan impurities and recalls and an update on FDA's current findings. 2018.
13. Moore DE. Drug-induced cutaneous photosensitivity: incidence, mechanism, prevention and management. Drug safety. 2002;25:345-72.
14. Kreutz R, Algharably EAH, Douros A. Reviewing the effects of thiazide and thiazide-like diuretics as photosensitizing drugs on the risk of skin cancer. Journal of hypertension. 2019;37(10):1950-8.
15. Ioannidis JP. Why most published research findings are false. PLoS Med 2005;2:e124.
16. Dwan K, Gamble C, Williamson PR, Kirkham JJ, Reporting Bias G. Reporting Bias Group. Systematic review of the empirical evidence of study publication bias and outcome reporting bias - an updated review. PLoS One 2013;8:e66844.
17. Ioannidis JP. Why most discovered true associations are inflated. Epidemiology 2008; 19:640-8.
18. Shin K, Yang J, Yu Y, Son E, Kim K, Kim YH. Angiotensin-converting enzyme inhibitors or angiotensin receptor blockers and cancer risk: an updated meta-analysis of observational studies. Therapeutic Advances in Drug Safety. 2022 Oct; 13:20420986221129335.
19. Bommareddy K, Hamade H, Lopez-Olivo MA, Wehner M, Tosh T, Barbieri JS. Association of spironolactone use with risk of cancer: a systematic review and meta-analysis. JAMA dermatology. 2022 Mar 1;158(3):275-82.
20. Wu Z, Yao T, Wang Z, Liu B, Wu N, Lu M, et al. Association between angiotensin-converting enzyme inhibitors and the risk of lung cancer: a systematic review and meta-analysis. British Journal of Cancer. 2023 Jan 19;128(2):168-76.
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22. Wu Z, Xia F, Lin R. Global burden of cancer and associated risk factors in 204 countries and territories, 1980-2021: a systematic analysis for the GBD 2021. Journal of hematology & oncology. 2024 Nov 29;17(1):119.
23. Gates M, Gates A, Pieper D, Fernandes RM, Tricco AC, Moher D, Brennan SE, Li T, Pollock M, Lunny C, Sepúlveda D. Reporting guideline for overviews of reviews of healthcare interventions: development of the PRIOR statement. Bmj. 2022 Aug 9;378.
24. Ioannidis J, Zhou Y, Chang C, Schully S, Khoury M, Freedman A. Potential increased risk of cancer from commonly used medications: an umbrella review of meta-analyses. Annals of oncology. 2014;25(1):16-23.
25. Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. bmj. 2017;358.
26. DerSimonian R, Laird N. Meta-analysis in clinical trials. Controlled clinical trials. 1986;7(3):177-88.
27. IntHout J, Ioannidis JP, Borm GF. The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method. BMC medical research methodology. 2014 Dec;14:1-2.
28. Fusar-Poli P, Radua J. Ten simple rules for conducting umbrella reviews. BMJ Ment Health. 2018 Aug 1;21(3):95-100.
29. Chinn S. A simple method for converting an odds ratio to effect size for use in meta‐analysis. Statistics in medicine. 2000 Nov 30;19(22):3127-31.
30. Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a cancer journal for clinicians. 2024 May;74(3):229-63.
31. Borenstein M, Hedges LV, Higgins JP, Rothstein HR. Introduction to meta-analysis. John Wiley & Sons; 2021 Apr 6.
32. Riley RD, Higgins JP, Deeks JJ. Interpretation of random effects meta-analyses. Bmj. 2011 Feb 10;342.
33. Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. Bmj. 1997;315(7109):629-34.
34. Sterne JA, Sutton AJ, Ioannidis JP, Terrin N, Jones DR, Lau J, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ 2011;343:d4002.
35. Ioannidis JP, Trikalinos TA. An exploratory test for an excess of significant findings. Clinical trials. 2007 Jun;4(3):245-53.
36. Ioannidis JP. Clarifications on the application and interpretation of the test for excess significance and its extensions. Journal of Mathematical Psychology. 2013 Oct 1;57(5):184-7.
37. Lane MM, Gamage E, Du S, Ashtree DN, McGuinness AJ, Gauci S, et al. Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses. bmj. 2024 Feb 28;384.
38. Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. Bmj. 2008 Apr 24;336(7650):924-6.
39. Pollock A, Farmer SE, Brady MC, Langhorne P, Mead GE, Mehrholz J, et al. An algorithm was developed to assign GRADE levels of evidence to comparisons within systematic reviews. Journal of clinical epidemiology. 2016 Feb 1;70:106-10.
40. Harewood R, Disney R, Kinross J, von Wagner C, Cross AJ. Medication use and risk of proximal colon cancer: a systematic review of prospective studies with narrative synthesis and meta-analysis. Cancer Causes & Control. 2021 Oct;32:1047-61.
41. Ioannidis JP, Haidich AB, Pappa M, Pantazis N, Kokori SI, Tektonidou MG, et al. Comparison of evidence of treatment effects in randomized and nonrandomized studies. Jama. 2001 Aug 15;286(7):821-30.
42. Kyzas PA, Denaxa-Kyza D, Ioannidis JP. Almost all articles on cancer prognostic markers report statistically significant results. European Journal of Cancer. 2007 Nov 1;43(17):2559-79.
43. McLaughlin JK, Tarone RE. False positives in cancer epidemiology. Cancer Epidemiology, Biomarkers & Prevention. 2013 Jan 1;22(1):11-5.
44. Tsilidis KK, Kasimis JC, Lopez DS, Ntzani EE, Ioannidis JP. Type 2 diabetes and cancer: umbrella review of meta-analyses of observational studies. Bmj. 2015 Jan 2;350.
45. Mariotto AB, Noone AM, Howlader N, Cho H, Keel GE, Garshell J, et al. Cancer survival: an overview of measures, uses, and interpretation. Journal of the National Cancer Institute Monographs. 2014 Nov 1;2014(49):145-86.
46. Renehan AG, Yeh HC, Johnson JA, Wild SH, Gale EA, Møller H. Diabetes and Cancer Research Consortium. Diabetes and cancer (2): evaluating the impact of diabetes on mortality in patients with cancer. Diabetologia. 2012 Jun;55:1619-32.
47. Theodoratou E, Tzoulaki I, Zgaga L, Ioannidis JP. Vitamin D and multiple health outcomes: umbrella review of systematic reviews and meta-analyses of observational studies and randomised trials. Bmj. 2014 Apr 1;348.
48. Moher D, Jones A, Cook DJ, Jadad AR, Moher M, Tugwell P, et al. Does quality of reports of randomised trials affect estimates of intervention efficacy reported in meta-analyses?. The Lancet. 1998 Aug 22;352(9128):609-13.
49. Solmi M, De Toffol M, Kim JY, Choi MJ, Stubbs B, Thompson T, et al. Balancing risks and benefits of cannabis use: umbrella review of meta-analyses of randomised controlled trials and observational studies. bmj. 2023 Aug 30;382.
50. Peto R, Emberson J, Landray M et al. Analyses of cancer data from three ezetimibe trials. N Engl J Med 2008; 359: 1357-1366.
51. Ryan PB, Madigan D, Stang PE et al. Empirical assessment of methods for risk identification in healthcare data: results from the experiments of the Observational Medical Outcomes Partnership. Stat Med 2012; 31: 4401-4415.
52. Fan B, Zhang J, Zhao JV. Systematic review of Mendelian randomization studies on antihypertensive drugs. BMC medicine. 2024 Nov 20;22(1):547.
53. Yu H, Liu Z, Wu Y, Zheng L, Wang K, Wu J, et al. Antihypertensive medications and cancer risk: evidence from 0.27 million patients with newly diagnosed hypertension. Frontiers in Pharmacology. 2025 Jul 1;16:1559604.
54. Park YJ, Kim MS, Lee Y, Lew BL, Kwon SH. Impact of Hydrochlorothiazide on Nonmelanoma Skin Cancer: A Distributed Network Analysis of 11 Real-world Databases. Annals of Dermatology. 2024 Dec 5;37.
55. Boyko EJ. Observational research-opportunities and limitations. Journal of Diabetes and its Complications. 2013 Nov 1;27(6):642-8.
2. Farrar J, Frieden T. WHO global report on hypertension 2025. The Lancet. 2025 Nov 15;406(10517):2318-9.
3. McEvoy JW, McCarthy CP, Bruno RM, Brouwers S, Canavan MD, Ceconi C, et al. ESC Guidelines for the management of elevated blood pressure and hypertension: Developed by the task force on the management of elevated blood pressure and hypertension of the European Society of Cardiology (ESC) and endorsed by the European Society of Endocrinology (ESE) and the European Stroke Organisation (ESO). European heart journal. 2024 Oct 7;45(38):3912-4018.
4. Writing Committee Members*, Jones DW, Ferdinand KC, Taler SJ, Johnson HM, Shimbo D, Abdalla M, Altieri MM, Bansal N, Bello NA, Bress AP. 2025 AHA/ACC/AANP/AAPA/ABC/ACCP/ ACPM/AGS/AMA/ASPC/NMA/PCNA/SGIM guideline for the prevention, detection, evaluation and management of high blood pressure in adults: a report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. Circulation. 2025 Sep 16;152(11):e114-218.
5. Ettehad D, Emdin CA, Kiran A, Anderson SG, Callender T, Emberson J, et al. Blood pressure lowering for prevention of cardiovascular disease and death: a systematic review and meta-analysis. The Lancet. 2016;387(10022):957-67.
6. Heinonen O, Shapiro S, Tuominen L, Turunen M. Reserpine use in relation to breast cancer. The Lancet. 1974;304(7882):675-7.
7. Grossman E, Messerli F, Goldbourt U. Antihypertensive therapy and the risk of malignancies. European heart journal. 2001;22(15):1343-52.
8. 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(7):627-36.
9. Sipahi I. Risk of cancer with angiotensin-receptor blockers increases with increasing cumulative exposure: meta-regression analysis of randomized trials. PLoS One. 2022;17(3):e0263461.
10. Copland E, Canoy D, Nazarzadeh M, Bidel Z, Ramakrishnan R, Woodward M, et al. Antihypertensive treatment and risk of cancer: an individual participant data meta-analysis. The Lancet Oncology. 2021 Apr 1;22(4):558-70.
11. Link WT, De Felice A. An FDA overview of rodent carcinogenicity studies of angiotensin II AT-1 receptor blockers: pulmonary adenomas and carcinomas. Regulatory Toxicology and Pharmacology. 2014;70(2):555-63.
12. Statement from FDA Commissioner Scott Gottlieb, M.D., and Janet Woodcock, M.D., director of the Center for Drug Evaluation and Research on FDA's ongoing investigation into valsartan impurities and recalls and an update on FDA's current findings. 2018.
13. Moore DE. Drug-induced cutaneous photosensitivity: incidence, mechanism, prevention and management. Drug safety. 2002;25:345-72.
14. Kreutz R, Algharably EAH, Douros A. Reviewing the effects of thiazide and thiazide-like diuretics as photosensitizing drugs on the risk of skin cancer. Journal of hypertension. 2019;37(10):1950-8.
15. Ioannidis JP. Why most published research findings are false. PLoS Med 2005;2:e124.
16. Dwan K, Gamble C, Williamson PR, Kirkham JJ, Reporting Bias G. Reporting Bias Group. Systematic review of the empirical evidence of study publication bias and outcome reporting bias - an updated review. PLoS One 2013;8:e66844.
17. Ioannidis JP. Why most discovered true associations are inflated. Epidemiology 2008; 19:640-8.
18. Shin K, Yang J, Yu Y, Son E, Kim K, Kim YH. Angiotensin-converting enzyme inhibitors or angiotensin receptor blockers and cancer risk: an updated meta-analysis of observational studies. Therapeutic Advances in Drug Safety. 2022 Oct; 13:20420986221129335.
19. Bommareddy K, Hamade H, Lopez-Olivo MA, Wehner M, Tosh T, Barbieri JS. Association of spironolactone use with risk of cancer: a systematic review and meta-analysis. JAMA dermatology. 2022 Mar 1;158(3):275-82.
20. Wu Z, Yao T, Wang Z, Liu B, Wu N, Lu M, et al. Association between angiotensin-converting enzyme inhibitors and the risk of lung cancer: a systematic review and meta-analysis. British Journal of Cancer. 2023 Jan 19;128(2):168-76.
21. Chong B, Jayabaskaran J, Jauhari SM, Chan SP, Goh R, Kueh MT, Li H, Chin YH, Kong G, Anand VV, Wang JW. Global burden of cardiovascular diseases: projections from 2025 to 2050. European journal of preventive cardiology. 2025 Aug;32(11):1001-15.
22. Wu Z, Xia F, Lin R. Global burden of cancer and associated risk factors in 204 countries and territories, 1980-2021: a systematic analysis for the GBD 2021. Journal of hematology & oncology. 2024 Nov 29;17(1):119.
23. Gates M, Gates A, Pieper D, Fernandes RM, Tricco AC, Moher D, Brennan SE, Li T, Pollock M, Lunny C, Sepúlveda D. Reporting guideline for overviews of reviews of healthcare interventions: development of the PRIOR statement. Bmj. 2022 Aug 9;378.
24. Ioannidis J, Zhou Y, Chang C, Schully S, Khoury M, Freedman A. Potential increased risk of cancer from commonly used medications: an umbrella review of meta-analyses. Annals of oncology. 2014;25(1):16-23.
25. Shea BJ, Reeves BC, Wells G, Thuku M, Hamel C, Moran J, et al. AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. bmj. 2017;358.
26. DerSimonian R, Laird N. Meta-analysis in clinical trials. Controlled clinical trials. 1986;7(3):177-88.
27. IntHout J, Ioannidis JP, Borm GF. The Hartung-Knapp-Sidik-Jonkman method for random effects meta-analysis is straightforward and considerably outperforms the standard DerSimonian-Laird method. BMC medical research methodology. 2014 Dec;14:1-2.
28. Fusar-Poli P, Radua J. Ten simple rules for conducting umbrella reviews. BMJ Ment Health. 2018 Aug 1;21(3):95-100.
29. Chinn S. A simple method for converting an odds ratio to effect size for use in meta‐analysis. Statistics in medicine. 2000 Nov 30;19(22):3127-31.
30. Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a cancer journal for clinicians. 2024 May;74(3):229-63.
31. Borenstein M, Hedges LV, Higgins JP, Rothstein HR. Introduction to meta-analysis. John Wiley & Sons; 2021 Apr 6.
32. Riley RD, Higgins JP, Deeks JJ. Interpretation of random effects meta-analyses. Bmj. 2011 Feb 10;342.
33. Egger M, Smith GD, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. Bmj. 1997;315(7109):629-34.
34. Sterne JA, Sutton AJ, Ioannidis JP, Terrin N, Jones DR, Lau J, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ 2011;343:d4002.
35. Ioannidis JP, Trikalinos TA. An exploratory test for an excess of significant findings. Clinical trials. 2007 Jun;4(3):245-53.
36. Ioannidis JP. Clarifications on the application and interpretation of the test for excess significance and its extensions. Journal of Mathematical Psychology. 2013 Oct 1;57(5):184-7.
37. Lane MM, Gamage E, Du S, Ashtree DN, McGuinness AJ, Gauci S, et al. Ultra-processed food exposure and adverse health outcomes: umbrella review of epidemiological meta-analyses. bmj. 2024 Feb 28;384.
38. Guyatt GH, Oxman AD, Vist GE, Kunz R, Falck-Ytter Y, Alonso-Coello P, et al. GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. Bmj. 2008 Apr 24;336(7650):924-6.
39. Pollock A, Farmer SE, Brady MC, Langhorne P, Mead GE, Mehrholz J, et al. An algorithm was developed to assign GRADE levels of evidence to comparisons within systematic reviews. Journal of clinical epidemiology. 2016 Feb 1;70:106-10.
40. Harewood R, Disney R, Kinross J, von Wagner C, Cross AJ. Medication use and risk of proximal colon cancer: a systematic review of prospective studies with narrative synthesis and meta-analysis. Cancer Causes & Control. 2021 Oct;32:1047-61.
41. Ioannidis JP, Haidich AB, Pappa M, Pantazis N, Kokori SI, Tektonidou MG, et al. Comparison of evidence of treatment effects in randomized and nonrandomized studies. Jama. 2001 Aug 15;286(7):821-30.
42. Kyzas PA, Denaxa-Kyza D, Ioannidis JP. Almost all articles on cancer prognostic markers report statistically significant results. European Journal of Cancer. 2007 Nov 1;43(17):2559-79.
43. McLaughlin JK, Tarone RE. False positives in cancer epidemiology. Cancer Epidemiology, Biomarkers & Prevention. 2013 Jan 1;22(1):11-5.
44. Tsilidis KK, Kasimis JC, Lopez DS, Ntzani EE, Ioannidis JP. Type 2 diabetes and cancer: umbrella review of meta-analyses of observational studies. Bmj. 2015 Jan 2;350.
45. Mariotto AB, Noone AM, Howlader N, Cho H, Keel GE, Garshell J, et al. Cancer survival: an overview of measures, uses, and interpretation. Journal of the National Cancer Institute Monographs. 2014 Nov 1;2014(49):145-86.
46. Renehan AG, Yeh HC, Johnson JA, Wild SH, Gale EA, Møller H. Diabetes and Cancer Research Consortium. Diabetes and cancer (2): evaluating the impact of diabetes on mortality in patients with cancer. Diabetologia. 2012 Jun;55:1619-32.
47. Theodoratou E, Tzoulaki I, Zgaga L, Ioannidis JP. Vitamin D and multiple health outcomes: umbrella review of systematic reviews and meta-analyses of observational studies and randomised trials. Bmj. 2014 Apr 1;348.
48. Moher D, Jones A, Cook DJ, Jadad AR, Moher M, Tugwell P, et al. Does quality of reports of randomised trials affect estimates of intervention efficacy reported in meta-analyses?. The Lancet. 1998 Aug 22;352(9128):609-13.
49. Solmi M, De Toffol M, Kim JY, Choi MJ, Stubbs B, Thompson T, et al. Balancing risks and benefits of cannabis use: umbrella review of meta-analyses of randomised controlled trials and observational studies. bmj. 2023 Aug 30;382.
50. Peto R, Emberson J, Landray M et al. Analyses of cancer data from three ezetimibe trials. N Engl J Med 2008; 359: 1357-1366.
51. Ryan PB, Madigan D, Stang PE et al. Empirical assessment of methods for risk identification in healthcare data: results from the experiments of the Observational Medical Outcomes Partnership. Stat Med 2012; 31: 4401-4415.
52. Fan B, Zhang J, Zhao JV. Systematic review of Mendelian randomization studies on antihypertensive drugs. BMC medicine. 2024 Nov 20;22(1):547.
53. Yu H, Liu Z, Wu Y, Zheng L, Wang K, Wu J, et al. Antihypertensive medications and cancer risk: evidence from 0.27 million patients with newly diagnosed hypertension. Frontiers in Pharmacology. 2025 Jul 1;16:1559604.
54. Park YJ, Kim MS, Lee Y, Lew BL, Kwon SH. Impact of Hydrochlorothiazide on Nonmelanoma Skin Cancer: A Distributed Network Analysis of 11 Real-world Databases. Annals of Dermatology. 2024 Dec 5;37.
55. Boyko EJ. Observational research-opportunities and limitations. Journal of Diabetes and its Complications. 2013 Nov 1;27(6):642-8.
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| Issue | Vol 21 No 2 (2026) | |
| Section | Review Article(s) | |
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| Hypertension Cancer Risk Mortality Survival Review | ||
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How to Cite
1.
Rostami A, Rahimi K, Ashraf H, Mosavari H, Fahimfar N. Antihypertensive Treatment and Cancer: Umbrella Review of Meta-Analyses of Randomized Controlled Trials and Observational Studies. Res Heart Yield Transl Med. 2026;21(2):156-168.
