Association of statins with aortic,peripheral,and visceral artery aneurysm development

Abstract

Objectives

Prior studies examining the effects of statins on arterial aneurysm development and progression yielded conflicting results due to their smaller size and presence of residual confounders. The objective of this study is to examine the association of statins with risk of being diagnosed with aortic, peripheral, and visceral artery aneurysm.

Methods

This was a retrospective cohort study of Tricare enrollees (from 1 October 2003 to 31 March 2012). Main outcomes were diagnosis of aortic, peripheral, or visceral artery aneurysm and undergoing aortic aneurysm repair procedure during follow-up period. Using 115 baseline characteristics, we generated a propensity score to match statin users and nonusers and examine the odds of outcomes (primary analysis). Secondary analysis examined outcomes at various subcohorts.

Results

Out of 10,910 statin users and 49,545 nonusers, we propensity score-matched 6728 pairs of statin users and nonusers. Statin users and nonusers had similar odds of being diagnosed with aortic, peripheral, and visceral artery aneurysms (odds ratio [OR]: 1.06, 95% confidence interval [95% CI]: 0.85–1.33) and of undergoing aortic aneurysm repair procedures (OR: 0.54, 95% CI: 0.22–1.35). Secondary analysis showed a tendency toward fewer aortic aneurysm procedures among statin users that did not reach statistical significance. However, high-intensity statin users in comparison to non-intensive statin users had higher adjusted odds of aortic, peripheral, and visceral artery aneurysms (OR: 1.76, 95% CI: 1.37–2.25, p < .0001).

Conclusions

This study does not support a clinically significant benefit or harm from statins regarding development of arterial aneurysm. However, secondary analyses may support the hypothesis proposed by previous research proposing a bidirectional role for statins.

Keywords

Aortic aneurysm arterial aneurysm observational study statins

Introduction

Arterial aneurysm, including abdominal aortic aneurysm (AAA), may remain dormant for prolonged periods allowing for an opportunity for interventions that may lower its devastating morbidity and mortality.¹ Therefore, there is interest to find therapies that prevent the development or slow disease progression. Although no randomized controlled trials have specifically examined the effect of statins on arterial aneurysm development and progression, statins have been recommended as a cornerstone of treatment for patients with arterial aneurysm that is presumed to be of atherosclerotic origin.² Extracellular matrix degradation and depletion of vascular smooth muscle cells in arterial walls secondary to inflammation are recognized as a main mechanism in aneurysmal formation and progression;³ therefore, statin anti-inflammatory effects have been proposed as a potentially beneficial therapy. While several observational studies noted statin beneficial effects in slowing progression and lowering risk of rupture of arterial aneurysm diseases,^4–6 other studies did not note such as effect.^7,8 A meta-analysis of 11 observational studies noted that statin therapy was associated with a significant reduction in AAA growth rate, yet the meta-analysis also acknowledged that selection bias, failure to adjust to confounders, and publication bias may have existed.⁹ Additionally, most studies were small in size (<250 patients) and of short duration.⁹ Similarly, two other meta-analyses noted several serious methodological limitations and significant heterogeneity of available observational studies concluding that there is no evidence of such beneficial effect.^10,11

On the other hand, statin effects on calcification and apoptosis was suspected to have a detrimental role on arterial aneurysm diseases. Using an organic phosphate model to stimulate calcification of in-vitro vascular smooth muscle cells, atorvastatin induced considerable apoptosis and subsequent calcification in smooth muscle cells;¹² smooth muscle apoptosis has been shown to result in aneurysm creation and progression.³ Additionally, several clinical studies have demonstrated that statins increase vascular atheroma calcifications.^13,14 While some studies noted that vascular calcification reduced AAA expansion rates and may be protective against aneurysm development,^15,16 other studies noted an opposite relationship.^17,18 One study, including 505 patients, noted that each 1-unit increment in the calcium score in the abdominal aorta and iliac arteries was associated with 0.13 mm increase in aortic diameter.¹⁷ Additionally, a recent observational study noted that statin use was associated with above median enlargement rate in AAA patients during the follow-up period, which averaged 2.6 years.⁸

The primary objective of this study was to compare the risk of being diagnosed with aortic, peripheral, and visceral artery aneurysm between statin users and nonusers, who were followed longitudinally within the same healthcare system.

Methods

We obtained Institutional Review Board approval at the Brooke Army Medical Center and the VA North Texas Health System that waived obtaining informed consents from patients since data were deidentified. Administrative data and medication fill histories for inpatient and outpatient medical encounters for patients enrolled at the San Antonio Military Multimarket area were retrieved. Protocol for data extraction, reliability, and reproducibility of the data was previously published.¹⁹ Extracted data included information regarding inpatient and outpatient medical encounters within Military Health system (MHS) and outside MHS (purchased care), and all dispensed medication transaction details within and outside MHS.

The study encompassed the period from 1 October 2003 to 31 March 2012 and included all patients who were 30 years of age or older, had ≥1 medical encounter during baseline period, and had ≥1 encounter during the follow-up period. Two treatment groups were identified:

Statin users: only patients newly initiated on statins were included. These patients had no prior statin prescription for at least two years from the date of study entry. This requirement also allowed two years of baseline period before starting statin therapy to adequately characterize patients at baseline (detailed later). Prevalent statin users (used statins within the first 2 years of date of study entry) were excluded.

Nonusers: this group were either patients who never used statins, or were nonusers before being prescribed statins. For example, if a patient started using statins at 1 January 2008, the patient was considered as nonuser from date of first medical encounter until 1 January 2008, and thereafter, the patient will be counted as statin user. Using this design mitigates immortal time bias.²⁰ Additionally, counting statin users as nonusers before they received statins minimizes confounding by indication.²¹

The study was divided into two periods: (1) Baseline period, defined as the two years preceding the index date, and was used to describe baseline characteristics and; (2) Follow-up period, started 90 days after the index date. We omitted the first 89 days after the index date from outcome assessment to minimize confounding by indication.^21–23 Since statin beneficial effects are expected to occur after at least 90 days, outcome events that take place during this period are likely due to preexisting confounders or chance. The follow-up period was used to capture outcomes of treatment groups.

For statin users, the index date was defined as the tenth day following the date of the first statin prescription. This was done to include events immediately following statin prescription in the baseline period, rather than the follow-up period. This strategy helped minimize confounding by indication. For example, patients with chest pain might start a statin immediately; however, they might not receive a diagnosis code for chest pain for a few days after that medical encounter. Alternatively, for nonusers, the index date was defined as two years after the first medical encounter.

Outcomes

An outcome was defined as an occurrence of an International Classification of Diseases, 9th Revision, Clinical Modification [ICD-9-CM] code of pre-specified diagnosis groups in inpatient or outpatient settings as follows:

Aortic, peripheral, and visceral artery aneurysms: as defined by the Agency for Health Research and Quality Clinical Classifications Software (AHRQ-CCS) category 115, which includes codes 4410, 44100, 44101, 44102, 44103, 4411, 4412, 4413, 4414, 4415, 4416, 4417, 4419, 4420, 4421, 4422, 4423, 44281, 44282, 44283, 44284, 44289, 4429, 44321, 44322, 44323, 44324, 44329, 44770, 44771, 44772, and 44773. The method of creation and validation of AHRQ-CCS was previously published.^24–28

Undergoing aortic aneurysm repair procedure, including open repair or endovascular repairs of AAA or thoracic aneurysm, as identified by ICD-9-CM procedure codes defined in AHRQ Quality Indicators, Version 4.5 in inpatient setting²⁹ (3834, 3864, 3844, 3971, 3978, and 3977) and codes 3973 and 3845. We also identified procedures that may be done in outpatient settings using Common Procedure Terminology codes 33880, 33881, 33883, 33884, 33886, 33889, 33891, 34800, 34802, 34803, 34804, 34805, 34812, 34813, 34820, 34825, 34826, 34839, 75952, 75953, 75956, 75957, 75958, and 75959.

Data and statistical analyses

Patients’ comorbidities were identified using ICD-9-CM codes, as defined by AHRQ-CCS diagnosis categories, and their Charlson comorbidity score was calculated using Deyo’s method.³⁰ Using 115 baseline characteristic variables, we created a propensity score to match statin users to nonusers. These variables included patient age, sex, social and family history, baseline period start date, follow-up duration, comorbidities, health care utilization, use of several medication classes, and undergoing invasive and noninvasive cardiovascular procedures at baseline (Table 1 and Appendix 1).

Table 1.

Selected baseline characteristics of propensity score matched statin users and nonusers.^a

	Nonusers (N = 6728)	Statin users (N = 6728)	Standardized differences
Age in years: mean (SD)	52 (14)	52 (12)	0.002
Male sex: n (%)	3560 (52.9)	3574 (53.1)	0.004
Health care use
Follow-up duration in years: mean (SD)	4.0 (2.1)	4.0 (1.6)	−0.009
Baseline period start date: n (%)
FY 2004–2006	5181 (77.0)	5166 (76.8)
FY 2007–2009	1492 (22.2)	1504 (22.4)
FY 2009–end of study	55 (0.8)	58 (0.9)	0.006
Number of inpatient admissions during baseline period: mean (SD)	0.65 (1.64)	0.62 (1.98)	−0.013
Number of outpatient medical encounters during baseline period: mean (SD)	66 (105)	65 (86)	−0.014
Social and family history: n (%)
Smoking^b	1816 (27.0)	1821 (27.1)	0.002
Family history of cardiovascular diseases^c	342 (5.1)	366 (5.4)	0.015
Illicit drug use	48 (0.7)	50 (0.7)	0.003
Alcohol abuse/dependence	99 (1.5)	92 (1.4)	−0.009
Comorbid conditions/diseases^d: n (%)
Charlson comorbidity score: mean (SD)^e	0.74 (1.33)	0.73 (1.31)	0.003
Obese-overweight	1732 (25.7)	1735 (25.8)	0.001
Diabetes mellitus	1321 (19.6)	1354 (20.1)	0.011
Diabetes mellitus with complications	475 (7.1)	487 (7.2)	0.006
Cataract	1016 (15.1)	1015 (15.1)	<0.001
Valvular heart disease	519 (7.7)	501 (7.4)	−0.009
Hypertension	3556 (52.9)	3510 (52.2)	−0.014
Hypertension with complication or secondary hypertension	217 (3.2)	205 (3.0)	−0.008
Coronary artery disease	418 (6.2)	439 (6.5)	0.010
Cardiac dysrhythmias	823 (12.2)	759 (11.3)	−0.028
Congestive heart failure	142 (2.1)	129 (1.9)	−0.012
Cerebrovascular disease	186 (2.8)	185 (2.7)	−0.001
Peripheral vascular disease	197 (2.9)	186 (2.8)	−0.008
Embolism or thrombosis	20 (0.3)	14 (0.2)	−0.016
Chronic obstructive pulmonary disease and bronchiectasis	722 (10.7)	729 (10.8)	0.003
Abdominal pain	885 (13.2)	874 (13.0)	−0.005
Chronic kidney disease	113 (1.7)	121 (1.8)	0.006
Osteoarthritis and other non-traumatic joint disorders	2714 (40.3)	2653 (39.4)	−0.018
Rehabilitation care, fitting of prostheses, and adjustment of devices	1193 (17.7)	1179 (17.5)	−0.006
Malignancy^e	386 (5.7)	389 (5.8)	0.002
Medications during baseline period: n (%)
Smoking cessation medication	181 (2.7)	176 (2.6)	−0.004
Beta-blocker	976 (14.5)	973 (14.5)	−0.001
Diuretic	1846 (27.4)	1785 (26.5)	−0.20
ACE/ARB	2478 (36.8)	2470 (36.7)	−0.002
Calcium channel blocker	906 (13.5)	889 (13.2)	−0.007
Other antihypertensive medication	285 (4.2)	278 (4.1)	−0.005
Aspirin	1369 (20.3)	1367 (20.3)	−0.001
Warfarin	200 (3.0)	179 (2.7)	−0.018
Hormone replacement therapy	750 (11.1)	760 (11.3)	0.005
Cardiovascular procedures during baseline period: n (%)
Electrocardiography	2308 (34.3)	2258 (33.6)	−0.015
Echocardiography	785 (11.7)	761 (11.3)	−0.010
Stress test	625 (9.3)	617 (9.2)	−0.004
Cardiac catheterization	96 (1.4)	107 (1.6)	0.007
Percutaneous coronary intervention	11 (0.2)	19 (0.3)	0.011
Coronary artery bypass graft surgery	3 (0.0)	6 (0.1)	0.004
Peripheral arterial revascularization procedure	9 (0.1)	9 (0.1)	<0.001
Outcomes of interest during baseline
Aortic, peripheral, and visceral artery aneurysm	68 (1.0)	66 (1.0)	−0.002

ACE/ARB: angiotensin-receptor blocker and/or angiotensin converting enzyme inhibitor; FY: fiscal year; SD: standard deviation.

Complete description of baseline characteristics was previously published.¹⁹

Smoking was defined using ICD-9-CM codes 3051 and V1582.

Family history of cardiovascular disease was defined using ICD-9-CM codes V171, V1749, V174, V1741, and V173.

Diagnoses were defined by the Agency for Health Research and Quality (AHRQ) Clinical Classifications Software disease categories.

The Deyo et al. method was used to calculate the Charlson comorbidity score from administrative data. We also matched the cohort on the 17 components of the Charlson comorbidity score (not all of which are listed in this table).

We used a logistic regression model to create the propensity score using 1:1 nearest neighbor matching with a caliper of 0.01 and testing the balance of covariates as previously described.^31–34 After matching, we assessed the balance of covariates based on standardized differences.

Primary analysis

We estimated the odds of outcomes in statin users and nonusers in the propensity score-matched cohort using conditional logistic regression analysis; no adjustment was introduced in this analysis since treatment groups were well balanced in all measured characteristics at baseline. Considering confounders that might be introduced during follow-up period, we then created multivariable, repeated logistic regression models that incrementally adjusted for several key potential confounders that may occur during follow-up, including:

Administration of beta-blocker medications during the follow-up period: beta-blockers may lower risk of aneurysm progression (Table 2); statin users may be more likely to receive these medications because of a health-conscious bias or more exposure to health care provider.³⁵

Diagnosis of hypertension, and undergoing coronary revascularization procedures during follow-up period: hypertension is a risk factor for aneurysm development and progression. Undergoing coronary revascularization procedures can serve as a marker of atherosclerotic burden and, therefore, can serve to adjust for any residual confounding by indication.

Number of inpatient admissions and outpatient encounters during the follow-up period: more medical visits may result in ascertainment bias. Statin users may have more frequent visits due to healthy-user bias or due to recurrent laboratory investigations resulting in higher likelihood for capturing outcomes.³⁵

Table 2.

Odds of aneurysmal diseases in the propensity score matched cohort of statin users and nonusers.

Variable	Nonusers (N = 6728) N (%)	Statin users (N = 6728) N (%)	Odds ratio	95% CI	p Value
Unadjusted odds ratio (patients were balanced for all baseline characteristics)
Aortic, peripheral, and visceral artery aneurysm	148 (2.2%)	157 (2.3%)	1.06	0.85–1.33	0.60
Aortic aneurysm repair procedure	13 (0.2%)	7 (0.1%)	0.54	0.22–1.35	0.19
Adjusted odds ratio (for receiving beta-blocker medications during the follow-up period)
Aortic, peripheral, and visceral artery aneurysm			1.06	0.84–1.33	0.63
Aortic aneurysm repair procedure			0.53	0.21–1.34	0.18
Adjusted odds ratio (for receiving beta-blocker medications, diagnosis of hypertension, and undergoing coronary revascularization procedures during follow-up period)
Aortic, peripheral, and visceral artery aneurysm			0.98	0.78–1.23	0.87
Aortic aneurysm repair procedure			0.49	0.19–1.23	0.13
Adjusted odds ratio (for receiving beta-blocker medications, diagnosis of hypertension, and number of inpatient admissions and outpatients encounters during follow-up period)
Aortic, peripheral, and visceral artery aneurysm			1.02	0.81–1.28	0.88
Aortic aneurysm repair procedure			0.51	0.20–1.29	0.16

Secondary analyses

We examined risks of outcomes in the following cohorts using multivariable repeated logistic regression. We used two models of adjustment in each cohort: (1) Propensity score-adjusted model: adjusting for the propensity score only; and (2) Fully adjusted model: adjusting for propensity score and the aforementioned potential confounders during follow-up. The following cohorts derived from the basic cohort (all patients who met the study criteria) were used in our secondary analysis:

Basic cohort: all patients who met the study inclusion and exclusion criteria.

Aneurysm incident cohort: this cohort excluded patients who had a diagnosis of aortic, peripheral, and visceral artery aneurysm at baseline.

Aneurysm cohort: this cohort only included cohort patients who had a diagnosis of aortic, peripheral, and visceral artery aneurysm at baseline.

Patients with diabetes cohort: this cohort only included patients who had diabetes at baseline.

Patient without diabetes cohort: this cohort excluded patients who had diabetes at baseline.

Healthy cohort: this cohort excluded patients with any of the following conditions during baseline period: Charlson comorbidity index >0.0; diabetes mellitus; acute or chronic ischemic heart diseases; valvular, endocardial, pericardial, or myocardial heart diseases; complications of hypertension; arrhythmia or conduction abnormalities; cerebrovascular diseases; peripheral vascular diseases including aneurysms; chronic obstructive lung diseases or respiratory failure; chronic kidney diseases; rheumatoid arthritis or systemic lupus erythromatosis; schizophrenia and psychotic disorders; history of suicide attempts; malignancy; and liver diseases.

Statin nonusers vs. high-intensity statin users in the basic cohort: in this cohort, we included only statin users who used high-intensity statins for ≥120 days. Statin intensity was defined according to the American College of Cardiology/American Heart Association (ACC/AHA) guidelines,³⁶ with a modification to include simvastatin 80 mg as a high-intensity statin.

Statin users’ cohort: this cohort only included statin users from the basic cohort. In this analysis, we examined odds of outcomes between high-intensity statin users versus moderate/low-intensity statin users.

Baseline characteristics for comparator groups were assessed using chi-square for categorical variables and Student’s t-test for continuous variables. Comparisons were considered to be statistically significant at p < 0.05. Statistical analyses were performed using SPSS version 21 (IBM, Armonk, NY, USA).

Results

A total of 60,455 patients (10910 statin users and 49545 nonusers) met study criteria. Statin users were older, had higher proportions of comorbidities, and utilized more medications. Simvastatin was the most commonly prescribed statin (72%), followed by atorvastatin (22%), pravastatin (3%), rosuvastatin (2%), and lovastatin and fluvastatin (<1%).

Propensity score-matched analysis

We successfully matched 6728 pairs of statin users and nonusers with no significant differences in baseline characteristics between groups (Table 1). Full description of the matched cohort characteristics was previously published.¹⁹ The cumulative duration of statin use among statin users was: mean (SD) = 3.5 (1.5) years and median (interquartile range) = 3.7 (1.9–4.9) years. Among statin users, 21% received a high-intensity statin for ≥120 days and 73% received a moderate intensity statin for ≥120 days.³⁶ Statin users differed in their health care utilization during the follow-up period; the mean (SD) number of inpatient admissions during the follow-up period for nonusers and statin users was 1.96 (4.64) and 1.73 (4.05), respectively (p = 0.003), and of outpatient medical encounters was 181 (267) and 193 (261), respectively (p = 0.008).

Primary analysis

In the propensity score-matched cohort, 157 statin users and 148 nonusers were diagnosed with aortic, peripheral, and visceral artery aneurysms, but only 20 patients underwent aortic aneurysm repair procedure. Statin users and nonusers had similar odds of being diagnosed with aortic, peripheral, and visceral artery aneurysms (odds ratio [OR]: 1.06, 95% confidence interval [95% CI]: 0.85–1.33) and similar odds of undergoing aortic aneurysm repair procedures (OR: 0.54, 95% CI: 0.22–1.35).

After incremental adjustment for receiving beta-blocker medications, diagnosis of hypertension, undergoing coronary revascularization procedures, and number of inpatient admissions and outpatients encounters during follow-up period, statin users had similar adjusted odds of outcomes compared to nonusers (Table 2).

Secondary analyses

Table 3 depicts the results of our secondary analyses. Although the number of patients diagnosed with aortic, peripheral, and visceral artery aneurysms was relatively large (789 patients), the number of patients undergoing aortic aneurysm repair procedures was small (39 patients).

Table 3.

Odds of outcomes in statin users and nonusers in secondary analyses.

Variable	Nonusers N (%)	Statin users N (%)	PS-adjusted model^a				Fully adjusted model^b
Variable	Nonusers N (%)	Statin users N (%)	OR	95% CI	p Value		OR	95% CI		p Value
Basic cohort
	N = 49545	N = 10910
Aortic, peripheral, and visceral artery aneurysm	499 (1.0%)	290 (2.7%)	1.15	0.93–1.43		0.21	1.12		0.92–1.38		0.27
Aortic aneurysm repair procedure	26 (0.1%)	13 (0.1%)	0.47	0.18–1.22		0.12	0.52		0.21–1.30		0.16
Aneurysm incident cohort: excluded patients who had a diagnosis of aortic, peripheral, or visceral artery aneurysm at baseline
	N = 49406	N = 10747
Aortic, peripheral, and visceral artery aneurysm	437 (0.9%)	206 (1.9%)	1.13	0.88–1.44		0.33	1.10		0.87–1.38		0.43
Aortic aneurysm repair procedure	20 (0.0%)	7 (0.1%)	0.45	0.13–1.54		0.20	0.51		0.16–1.62		0.25
Aneurysm cohort: included only patients who had a diagnosis of aortic, peripheral, or visceral artery aneurysm at baseline
	N = 139	N = 163
Aortic aneurysm repair procedure	6 (3.6%)	6 (1.8%)	0.55	0.12–2.48		0.44	0.56		0.13–2.40		0.44
Patients with diabetes cohort: only included patients who had diabetes at baseline
	N = 2735	N = 3058
Aortic, peripheral, and visceral artery aneurysm	47 (1.7%)	74 (2.4%)	0.80	0.51–1.26		0.34	0.80		0.51–1.25		0.33
Aortic aneurysm repair procedure	7 (0.2%)	4 (0.1%)	0.40	0.10–1.53		0.18	0.42		0.11–1.56		0.19
Patient without diabetes cohort: excluded patients who had diabetes at baseline
	N = 46810	N = 7852
Aortic, peripheral, and visceral artery aneurysm	452 (1.0%)	216 (2.8%)	1.26	0.99–1.62		0.06	1.22		0.97–1.54		0.09
Aortic aneurysm repair procedure	19 (0.0%)	7 (0.1%)	0.60	0.17–2.13		0.43	0.64		0.19–2.15		0.47
Healthy cohort: excluded patients with comorbidities that may adversely affect mortality or physical activity
	N = 35783	N = 4563
Aortic, peripheral, and visceral artery aneurysm	217 (0.6%)	46 (1.0%)	0.83	0.54–1.29		0.40	0.80		0.52–1.22		0.29
Aortic aneurysm repair procedure	9 (0.0%)	2 (0.0%)	1.72	0.24–12.34		0.59	1.64		0.26–10.44		0.60
Basic cohort: high-intensity statin users vs. nonusers
	N = 49545	N = 2470
Aortic, peripheral, and visceral artery aneurysm	499 (1.0%)	99 (4.0%)	1.10	0.82–1.49		0.52	1.12		0.83–1.50		0.47
Aortic aneurysm repair procedure	26 (0.1%)	4 (0.2%)	0.32	0.09–1.14		0.08	0.33		0.09–1.18		0.09
Statin users only: high-intensity statin users vs. moderate/low-intensity statin users
	Moderate/ low-intensity	High-intensity
	N = 8440	N = 2470
Aortic, peripheral, and visceral artery aneurysm	191 (2.3%)	99 (4.0%)	1.76	1.37–2.25		<0.0001	1.48		1.14–1.92		0.003
Aortic aneurysm repair procedure	9 (0.1%)	4 (0.2%)	1.49	0.46–4.85		0.51	1.20		0.36–4.00		0.77

Adjusted for propensity score.

Adjusted for propensity score, use of beta-blockers, diagnosis of hypertension, undergoing coronary revascularization procedures, and number of inpatient admissions and outpatients encounters during the follow-up period.

PS = Propensity score.

In the vast majority of our secondary subgroup analyses, statin users and nonusers had similar outcomes. However, the OR of aortic aneurysm repair procedures in most secondary analyses was lower in statin users in comparison to nonusers but did not reach statistical significance. On the other hand, restricting the analysis to the statin users group only, high-intensity statin users had significantly higher OR of being diagnosed with aortic, peripheral, and visceral artery aneurysms (OR: 1.76; 95% CI: 1.37–2.25; p < .0001), which persisted after full adjustment (OR: 1.48; 95% CI: 1.14–1.92, p = .003).

Discussion

To our knowledge, this study is the largest observational study that has examined the association of statin use with risk of being diagnosed with aortic, peripheral, and visceral artery aneurysms, as well as the risk of undergoing aortic aneurysm repair procedures. Our primary analysis demonstrates that statin users and nonusers had similar odds of outcomes. However, the number of patients who underwent aortic aneurysm repair procedures was very small (only 20 patients); therefore, our study was underpowered to detect differences in procedures. While the vast majority of secondary subgroup analyses showed no statistically significant associations, consistent with the primary analysis, secondary analyses suggested some intriguing associations. For example, there was a trend toward lower odds of undergoing an aortic aneurysm repair procedure among statin users in comparison to nonusers in most secondary analyses, although it did not reach statistical significance. Such trend must be viewed with caution due to the small number of events (only 39 patients). This trend is consistent with findings of another observational study of patients with thoracic aortic aneurysm (147 statin users and 502 nonusers) that found statin therapy to be associated with reduction in risk of repair procedures, but not death, rupture, or dissection.³⁷

On the other hand, within the statin users’ group, high-intensity statin users had a 76% increased odds of being diagnosed with aortic, peripheral, or visceral artery aneurysms (p < .0001), and this increased risk continued to be significant even after multivariable adjustments. High-intensity statins have been shown to exert the greatest increase in calcium deposition in comparison on low-intensity statins or no statins.¹² If we used a more conservative alpha-level to accommodate for multiple statistical comparisons (0.01, for example, instead of 0.05), the latter finding would still be statistically significant.

If the contradictory findings of our secondary analyses (more risk of being diagnosed with arterial aneurysm but less risk of aneurysm procedural intervention) are to be used to generate a hypothesis, it would be to support a bidirectional role of statins on aneurysmal development and progression as suggested by other researchers.³⁸ In a female rate model subjected to hypertension, increased hemodynamic stress, and estrogen deficiency, a smaller daily dose of pravastatin increased endothelial nitric oxide synthase levels, reduced endothelial damage, and inhibited cerebral aneurysm formation. A higher dose of pravastatin or simvastatin increased apoptotic caspase-3 levels, promoted aneurysmal growth, and induced aneurysmal rupture.³⁸ Therefore, statin effects on arterial aneurysm may have a complex bidirectional effect. Indeed, a study analyzing gene expression and protein concentrations of metalloproteinases and their inhibitors in AAA indicated that statin effects are not unidirectional, but rather more complex, affecting both metalloproteinases and their inhibitors.³⁹

Whereas observational studies examined the effects of statins on arterial aneurysm progression, there is a scarcity of studies that have examined the association of statin therapy with aneurysm development. A retrospective observational study (680 bicuspid aortic valve patients who underwent aortic valve or wall surgery) noted that being on preoperative statin use was associated with less risk of having aortic root diameter >4.5 cm at time of surgery.⁴⁰

Our study has limitations, including its retrospective observational design, which may suffer from unrecognized confounders. Using ICD-9-CM codes, which may lack sensitivity toward some variables, may result in under-correction for divergent baseline characteristics. Despite all the limitations of using ICD-9-CM codes as a method in identifying baseline characteristics and outcomes, we do not know of any reason for differential ascertainment bias between statin users vs. nonusers. We also lacked data on aneurysm size and we used aortic aneurysm repair procedures as a surrogate marker for having severe disease; hence, we lacked accurate information on disease severity. Another limitation of our study is that the population age is relatively young (mean age of 52); however, other risks factors for arterial diseases were common at baseline (over half had hypertension, 27% were smoker, 25% were obese or overweight, and 20% had diabetes).

The results of this study should not be interpreted to mean that statin is not beneficial in patients with arterial aneurysm disease since we did not examine the overall effects of statins on mortality or other cardiovascular outcomes in those patients; rather, we examined the effects of statin use on risk of being diagnosed with an arterial aneurysm.

In conclusion, this large study does not support a clinically significant beneficial or harmful role of statins in development of arterial aneurysm disease, contrary to widely held belief. However, our secondary analyses may support a bidirectional role for statins that warrants further investigation.

Footnotes

Declaration of conflicting interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: The views expressed herein are those of the authors and do not reflect the official policy or position of the Department of the Army, Department of Defense, Department of Veterans Affairs, or the U.S. Government. The authors are employees of the U.S. government. This work was prepared as part of their official duties and, as such, there is no copyright to be transferred.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: CRF was supported by the U.S. National Institutes of Health (NIH) in the form of a NIH/KL2 career development award (RR025766) during the conduct of this study. In addition, CRF’s institution has received research grants from Allergan, Bristol Myers Squibb, and Pharmacyclics, outside the submitted work, in the last three years. EMM and EAH were supported in part by a grant from the Agency for Healthcare Research and Quality (R24 HS022418) and the University of Texas Southwestern Center for Patient-Centered Outcomes Research.

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