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Br J Clin Pharmacol. Jul 2012; 74(1): 180–188.
Published online Jan 13, 2012. doi:  10.1111/j.1365-2125.2012.04170.x
PMCID: PMC3394143

Long term use of drugs affecting the renin-angiotensin system and the risk of cancer: a population-based case-control study

Abstract

AIMS

A recent meta-analysis of clinical trials has demonstrated a small excess of cancers in persons who had been allocated to angiotensin receptor blockers (ARBs). We undertook this observational study to look at dose–response and dose–duration effects and look for specificity with respect to outcome. Use of angiotensin converting enzyme inhibitors (ACEIs) was included in the main analysis since ACEIs share pharmacological properties with ARBs.

METHODS

We identified 149 417 incident cancer cases in Denmark during the period 2000–2005. Four controls, matched by age and gender, were selected for each case by a risk-set sampling. Data on medication were retrieved from the Danish National Prescription Registry. We defined long term exposure as at least 1000 defined daily doses redeemed within the past 5 years. Confounders were controlled by conditional logistic regression.

RESULTS

The odds ratio (OR) associating long term drug use with incident cancer was 1.12 (95% CI 1.06, 1.18), 1.17 (95% CI 1.14, 1.20), 1.23 (95% CI 1.20, 1.26), 1.18 (95% CI 1.14, 1.22), 1.25 (95% CI 1.22, 1.28), 1.37 (95% CI 1.21, 1.54), 1.29 (95% CI 1.22, 1.37) for ARBs, ACEIs, calcium channel blockers, β-adrenoceptor blockers, thiazide diuretics and α-adrenoceptor blockers. No consistent dose–duration or dose–response association could be demonstrated for ARBs or ACEIs.

CONCLUSIONS

The indication or possibly threshold for prescribing antihypertensives appears to be related to a small increase in cancer risk. The ARB-cancer association is probably too weak to be addressed in observational studies, given their limitations.

Keywords: angiotensin converting enzyme inhibitors, angiotensin receptor blockers, antihypertensives, cancer, case-controls study

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT

  • A recent meta-analysis has suggested an increased risk of cancer among users of angiotensin receptor blockers.

WHAT THIS STUDY ADDS

  • Within the limitations of an observational study there is no difference in the cancer incidence between users of drugs affecting the renin-angiotensin system and users of other antihypertensives.
  • No consistent dose or duration dependency could be demonstrated for angiotensin reeptor blockers and angiotensin converting enzyme inhibitors.

Introduction

Angiotensin-converting-enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) are widely used drugs and generally, they are considered as safe treatments with very few adverse effects [1]. However, there is increasing evidence that long term treatment with drugs that have an effect on the renin-angiotensin system (RAS) may affect the risk of cancer.

Angiotensin II is the main mediator in the RAS and it is generated by the activation of angiotensin I through the angiotensin converting enzyme. Mediators in RAS are important not only for the regulation of blood pressure, electrolytes and fluid homeostasis, but also for regulation of cellular proliferation, angiogenesis and tumour progression [2][5]. Local expression of several mediators of RAS has been found in various cancer cells and tissues, including brain, lung, breast, prostate, skin and cervix carcinomas [2].

In 2003, the CHARM study reported a significantly increased risk of cancer in patients exposed to candesartan (2.3%) compared with placebo (1.6%) [6]. Recently, a meta-analysis of randomized controlled trials reported a modestly increased risk of cancer in patients exposed to ARBs [7]. In trials where cancer development was a specified endpoint, an increased risk of about 10% was observed. Particularly, the risk of lung cancer was significantly higher in patients treated with ARBs compared with controls (RR 1.25, 95% CI 1.05, 1.49) [7]. A number of observational studies on the association between ARBs or ACEIs and cancer have given conflicting results [8][22].

As the association between ARBs and cancer now seems to be supported on a new and higher level of evidence, it would be relevant to revisit the ARB-cancer association in an observational approach. Many questions are not answered by the meta-analysis, e.g. what is the association with dose or duration. In addition, the proposed mechanism suggests that there might be a similar carcinogenesis with ACEI. There seem to be few reports where ARBs and ACEIs are studied in tandem by the same study set-up [17], [21]. Finally, as there may be confounders associated with the circumstances of treating hypertension, e.g. that ARBs or ACEIs were preferentially given to subjects with unhealthy lifestyles, we chose to study the specificity of the ARB-cancer association by looking also at the apparent association with other drugs used to treat hypertension.

Methods

The study was conducted as a population-based case-control study of incident cancers in Denmark (population 5.4 million) during the period January 1 2000 to December 31 2005.

The material has been described in a previous publication [23]. In brief, we used data from the Danish Cancer Registry (DCR), the Danish National Registry of Patients (DNRP), the Prescription Database of the Danish Medicines Agency and the Danish Person Registry. The DCR has recorded incident cases of cancer on a nationwide basis since 1943 and has been shown to have accurate and almost complete ascertainment of cancer cases [24]. The DNRP contains data on all secondary care contacts in Denmark since 1977 [25]. The Prescription Database of the Danish Medicines Agency contains data on all prescription drugs redeemed by Danish citizens since 1995 [26]. Prescription data include the Central Person Registry number, the date of dispensing, the substance, brand name and quantity. The dosing instruction and the indication for prescribing are not recorded. Drugs are categorized according to the Anatomic Therapeutic Chemical code, a hierarchical classification system developed by the WHO for purposes of drug use statistics [27]. The quantity for each prescription is expressed by the defined daily dose (DDD) measure, also developed by the World Health Organization (WHO). The DDDs for ACEIs and ARBs are shown in the appendix. The Danish Person Registry contains data on vital status (date of death) and migrations in and out of Denmark, which allowed us to extract controls and to keep track of all subjects. All linkage occurred within Statistics Denmark, a governmental institution that maintains electronic records for statistical and scientific purposes.

Cases were all patients with a first time occurrence of a cancer diagnosis (the index date) in the period January 1 2000 to December 31 2005. Individuals who had a cancer diagnosis before 2000 were excluded, and we further excluded cases who were not inhabitants in Denmark at the index date or who immigrated to Denmark less than 5 years before the index date. For each case we selected four controls randomly among all Danish citizens with the same gender and birth year and who did not fulfil any of the exclusion criteria. Cases were eligible as controls until their first occurrence of cancer. The index date for the four matched controls was set to be that of the corresponding case. Thereby, the estimated odds ratios (OR) are unbiased estimates of the incidence rate ratio [28]. We based our analyses on cumulative past exposure and refrained from requiring that cases or controls should be active users on their index dates to count as exposed. This was justified by the natural course of nearly all cancers. As they are largely irreversible processes, long term past use was thought to be more relevant than current use.

Data were analyzed according to a conventional matched case-control design. Main exposure was defined by a use of ACEIs or ARBs at a cumulated dose of at least 1000 DDD within a 5 year period before the index date. The reference for all analyses was never use of ACEIs or ARBs as appropriate. Thus, a subject who had been an ARB user but had not reached 1000 DDD within the past 5 years was not included in the main analysis.

A cancerogenic effect of ACEIs and/or ARBs may be expected for a broad variety of malignancies, and in our primary analysis, we therefore used a composite end point defined by the occurrence of any type of cancer (DCR: ICD-7, 140–205; NPR: ICD8, 140–207; ICD10, C00-C97). Secondary analyses were done on specific cancer types: lung cancer, colon cancer, breast cancer, prostate cancer, haematologic cancers, tobacco related cancer (cancers of the lung, larynx, mouth, pharynx, oesophagus, pancreas, bladder, renal pelvis, kidney, stomach, cervix, and acute myeloid leukaemia) and non–tobacco-related cancer (all others). Confounders were adjusted for by conditional logistic regression. The following potential confounders were included in the regression model: (i) a prior discharge diagnosis of chronic obstructive pulmonary disease (COPD) as a crude marker of heavy smoking, (ii) a prior discharge diagnosis of inflammatory bowel disease, (iii) a modified Charlson Index [29] that contains 19 categories of co-morbidity. Each category has an associated weight based on the adjusted risk of 1 year mortality. To ensure comparability between cases and controls, we disregarded cancer diagnoses when computing the Charlson Index and (iv) a cumulated dose of at least 1000 DDD within the last 5 years before index date of non-steroidal anti-inflammatory drugs (NSAIDs) or high-dose aspirin, oestrogen hormone therapy, oral contraceptives, finasteride or statins. These drugs were chosen as they are known or suspected to modify the risk of some cancers.

For individuals whose cumulative dose of ACEIs or ARBs was ≥200 DDD, we calculated the average daily dose as the cumulative dose between first and last prescription divided by the number of days between first and last prescription. We also explored if there was a cumulative dose–response relationship and/or a relation between the duration of exposure and the risk of cancer. For fixed dose combinations involving ARBs or ACEIs, we used the quantity in DDD for the ARB/ACEI component only. For the exploratory sub-analyses on cumulative dose, duration, number of prescriptions and daily dose we did not require that the subjects should have used 1000 DDD or more of ARBs or ACEIs during the past 5 years to count as exposed. We still had never users as reference.

We performed the analyses for other antihypertensives as well, using the same criteria for exposure and outcome. These other classes were calcium blockers, β-adrenoceptor blockers, thiazide diuretics and α-adrenoceptor blockers. For each of these analyses, we had as reference never-use of the drug in question. The study was approved by Statistics Denmark's scientific board. Ethics review was not required. All statistical analyses were done using Stata version 11 (Stata Corp.) [30].

Results

The material included 149 417 incident cancer cases and 597 668 controls, 52.3% were women and the mean age was 69.4 years. The four major cancer sites, breast, colon/rectum, lung and prostate gland accounted for altogether 43.1% of cases.

Among the 149 417 cancer cases, 1765 (1.18%) were long term users of ARBs and 10 544 (7.06%) were long term users of ACEIs. The corresponding figures for control subjects were 6220 (1.04%) and 36 154 (6.05%). Other characteristics of cases and controls are detailed in Table 1. The cases more often had a high comorbidity index, were more often long term users of hormone therapy, and more often had a history of hypertension, obstructive pulmonary disease or chronic renal failure.

Table 1
Characteristics of cases and controls

The association between long term use of ARBs or ACEIs and risk of cancer in various sites is shown in Tables 2 and and3.3. We found an adjusted OR for the main analysis, all cancers, of 1.12 (95% CI 1.06, 1.18) and 1.17 (95% CI 1.14, 1.20) for ARBs and ACEIs, respectively. The secondary analysis on specific cancer sites revealed a significant association between ARB and prostate cancer (OR 1.39, 95% CI 1.15, 1.68) and a composite group of non-tobacco related cancer (OR 1.13, 95% CI 1.06, 1.20). For ACEIs, we found significantly elevated ORs for colorectal cancer (OR 1.30, 95% CI 1.22, 1.39), breast cancer (OR 1.14, 95% CI 1.06, 1.22), prostate cancer (OR 1.28, 95% CI 1.18, 1.39), and non-smoking related cancers (OR 1.23, 95% CI, 1.19, 1.26).

Table 2
Association between long term use of angiotensin receptor blockers and the risk of cancer, by cancer site. Long term use was defined as 1000 defined daily doses with the past 5 years
Table 3
Association between long term use of angiotensin converting enzyme inhibitors and the risk of cancer, by cancer site. Long term use was defined as 1000 defined daily doses within the past 5 years.

The associations between ARB or ACEI use in different exposure patterns and cancer are shown in Tables 4 and and5.5. The reference for all these analyses was never use of ARBs and ACEIs, respectively, and all malignancies were included in the endpoint. There were no significant trends for exposure in neither cumulative dose, daily dose or number of prescriptions for any of the exposures, while ACEIs alone showed a positive trend with duration.

Table 4
Association between long term use of angiotensin receptor blockers (ARBs) and the risk of cancer, by exposure pattern. The reference for all analyses was never use of ARBs and all malignancies were included in the endpoint
Table 5
Association between long term use of angiotensin converting enzyme inhibitors (ACEIs) and the risk of cancer, by exposure pattern. The reference for all analyses was never use of ACEIs and all malignancies were included in the endpoint

We repeated all analyses in Tables 25 with exclusion of subjects who had been exposed to both ARBs and ACEIs, thus including only exclusive users. The results were very similar to the main finding (data not shown).

The ORs associating other antihypertensives were consistently elevated above unity with adjusted OR point estimates in the range 1.18 (β-adrenoceptor blockers) to 1.37 (α-adrenoceptor blockers). None of the confidence intervals crossed the null value (Table 6). As antihypertensives are often combined and may thereby confound estimates mutually, we performed a similar analysis limited to subjects who had only used drugs within one antihypertensive drug class. Except for wider confidence intervals, the results agreed very well with the main analysis (data not shown).

Table 6
Exploratory analyses on the apparent association between long term use of other antihypertensives and cancer. For all drug classes, we considered those exposed who had taken at least 1000 defined daily doses during the last 5 years before the index date. ...

Discussion

The main finding of our study was a weak association between ARB/ACEI use and cancer. However, we found a similar association with all other major classes of antihypertensives. Within the ranges studied here, there was no consistent dose–response or duration–response effect in the association between ARBs and ACEIs.

Several other studies indicate that the risk of cancer may be influenced by long term exposure to drugs that have an effect on the RAS, but the results are not conclusive. A protective effect of ACEIs was first suggested by Lever et al. who observed a significantly reduced risk of incident (OR 0.72) and fatal (OR 0.65) cancer in patients undergoing long term treatment with ACEIs [8]. A study by Jick et al. provided some support for the cancer protective effect of ACEIs with a 20–30% reduced risk of cancer in users of ACEIs compared with users of β-adrenoceptor blockers [9]. Other epidemiological studies, however, have failed to support the evidence of a cancer protective effect of ACEIs [10][19] In contrast, Grossman et al. reported an increased risk of cancer in users of ACEIs [20]. An increased risk of cancer (OR 1.59) was also observed in the prospective Studies of Left Ventricular Dysfunction (SOLVD) among patients exposed to the ACEI, enalapril, compared with the placebo group [31].

The main strength of our study was the use of comprehensive data resources covering a large population base, the entire Danish population followed for at least 11 years. The validity of the diagnoses in the DCR is generally high [24], and the sensitivity and predictive values of cancer diagnoses in the DNRP are also acceptable [32], [33]. By use of the DNRP register, the ARB and ACEI prescription data were based on a population-wide reimbursement coverage. There would little be incentive for anyone to redeem ARB or ACEI prescriptions on behalf of someone else. The use of comprehensive data sources allowed us to adjust for some variables that might have confounded the ARB/ACEI-cancer association. Among the weaknesses of the study is that we do not have data on the indication for using the drugs. ARBs, ACEIs and β-adrenoceptor blockers are all used to treat heart failure, and several other indication may be relevant for β-adrenoceptor blockers and calcium channel blockers. However, the majority of users take them to treat hypertension, as indicated, among other things, by the mostly young age of users [34].

Why did we find a weak association with cancer for all antihypertensives? Pharmacologically, they have little in common, and it is unlikely that the observations reflect a genuine biological effect of them all. Since this is an observational study with no randomization, it is vulnerable to confounding-by-indication. It is conceivable that our observations largely reflect clinician or patient behaviour in relation to hypertension. For example, the prevalence of borderline hypertension is high [35], and among such patients, the indication for pharmacological treatment is conditional on other factors than the blood pressure itself [36]. Possibly, persons with low grade hypertension are more often treated if they have an unhealthy lifestyle than if they have not, thus creating a non-causal association between antihypertensive treatment and cancer. Ideally, we should have accounted for these lifestyle factors, e.g. smoking, in our analysis. However, given the size of our material and the particular conditions for data access in Statistics Denmark, it would have been prohibitively expensive or plain impossible to collect the data by, for example, questionnaire. We used COPD as a crude marker for smoking. However, not all subjects with COPD have a diagnosis of COPD, not all heavy smokers develop COPD and some develop COPD without having smoked. We thus cannot rule out that there was some residual confounding by smoking. Another possibility for the association found for all antihypertensives was that having hypertension entails frequent physician contact, particularly early in the course. This may facilitate early cancer diagnosis and might explain why the apparent risk was high with low cumulative doses for both ARBs and ACEIs.

The OR reported in the meta-analysis by Sipahi et al. was 1.08 [7]. As it is based on randomized trials their finding cannot be explained by an imbalance of lifestyle factors between users and non users of ARBs. Some have questioned whether observational studies such as ours can reliably detect and elaborate weak associations [37], [38], as it is difficult to rule out residual confounding of this magnitude. The Sipahi meta-analysis described outcomes with a mean or median treatment duration of 1.9–4.8 years. We could provide data for at least 5 years of follow-up and a cumulative dose of more than 3000 DDDs, without finding any signs of a dose- or duration dependent effect. Given the strengths of our material, we find it unlikely that we would have overlooked strong effects, three fold increases or more, within the ranges studied in our paper.

From a clinical viewpoint, ARBs should not be dismissed. A recent meta-analysis of clinical trials came to the conclusion that ARBs do not increase the cancer risk [39]. One possible explanation of the discrepancy with the earlier meta-analysis [7] is in the choice of design. The meta-analysis by Sipahi et al. [7] was based only on trials comparing ARBs with placebo [7], while the new meta-analysis by Bangalore et al. [39] is a network meta-analysis thereby including both direct and indirect estimates of the ARB-cancer association. Even if the results from Sipahi et al.'s meta-analysis are taken at face value, the cancer risk for the individual user is only slightly increased and the increment is of a magnitude that we accept for some other drugs, e.g. oral contraceptives and hormone therapy [40], [41]. Also, it should be pointed out that although the cancer incidence was elevated among ARB users in the Sipahi et al.'s study, the cancer mortality was not. Finally, if ARBs are given for a proper indication, the gain in life-expectancy by far outweighs the possible cancer risk entailed.

From a pharmacological viewpoint, animal studies suggest the key to carcinogenesis is modulation of angiogenesis via the RAS and angiotensin II receptors [4], [5]. If it is indeed a question of response at the angiotensin-receptor we should expect a class effect of ARBs and possibly also some cancerogenic effect of ACEIs. As this has been reported in at least one trial [31], the next obvious step would be to conduct a formal meta-analysis on cancer risk in placebo-controlled ACEI trials.

Competing Interests

Jesper Hallas, Morten Andersen and Søren Friis have received fees for teaching from the Danish Association of the Pharmaceutical Industry. Jesper Hallas has received research grants from Nycomed, MSD and Pfizer. Morten Andersen has participated in research projects funded by AstraZeneca, Lundbeck, Merck Sharp & Dohme, Novartis, Nycomed and Pfizer with grants paid to the institutions where he has been employed. Lars Bjerrum has received funds for research from the European Commission. All the other authors have no competing interests to declare.

Appendix

The Anatomic Chemical Therapeutic (ATC) code and defined daily dose of angiotensin converting enzyme inhibitors and angiotensin receptor blockers on the Danish market during the study period.

ATC codeDrugDefined daily dose (mg)
C09AA01Captopril50
C09AA02Enalapril10
C09AA03Lisinopril10
C09AA04Perindopril4
C09AA05Ramipril2.5
C09AA06Quinapril15
C09AA07Benazepril7.5
C09AA09Fosinopril15
C09AA10Trandolapril2
C09AA13Moexipril15
C09CA01Losartan50
C09CA02Eprosartan600
C09CA03Valsartan80
C09CA04Irbesartan150
C09CA06Candesartan8
C09CA07Telmisartan40
C09CA08Olmesartan20

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