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Nonsteroidal Anti-inflammatory Drug Use and Acute Myocardial Infarction
Daniel H. Solomon, MD, MPH;
Robert J. Glynn, PhD, ScD;
Raisa Levin, MS;
Jerry Avorn, MD
Arch Intern Med. 2002;162:1099-1104.
ABSTRACT
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Background Although aspirin has been shown to protect patients from acute myocardial
infarction (AMI), the effect of nonaspirin nonsteroidal anti-inflammatory
drugs (NSAIDs) is not clear.
Objective To determine whether NSAIDs have a similar effect or whether they differ
in their effect on the risk of AMI.
Methods We performed a case-control study of AMI in a large health care database
containing information on all filled prescriptions, hospitalizations, diagnoses,
and procedures for all patients covered by the New Jersey Medicaid or Medicare
and Pharmaceutical Assistance for the Aged and Disabled programs. We identified
4425 patients hospitalized for AMI between January 1, 1991, and December 31,
1995, and 17 700 control subjects. Multivariate models were constructed
to control for potential confounders.
Results A quarter of the cases and controls had filled a prescription for an
NSAID in the 6 months before their AMI (cases) or a randomly assigned index
date (controls); 9% had filled a prescription for an NSAID that overlapped
with their date of AMI or index date. Overall, NSAID users had the same risk
of AMI as nonusers, whether such use was measured on the index date (adjusted
odds ratio, 1.04; 95% confidence interval, 0.92-1.18; P = .55) or at any time in the prior 6 months (adjusted odds ratio,
1.00; 95% confidence interval, 0.92-1.08; P = .92).
However, use of naproxen was associated with a significant reduction in the
risk of AMI (adjusted odds ratio, 0.84; 95% confidence interval, 0.72-0.98; P = .03).
Conclusions Although NSAIDs have anti-inflammatory and antiplatelet effects similar
to those of aspirin, we did not find that these drugs confer a protective
effect against AMI. However, use of one specific NSAID, naproxen, appeared
to be associated with a reduced rate of AMI, an effect recently suggested
by a large randomized controlled trial as well.
INTRODUCTION
RECENT PUBLICATION of the study by Bombardier et al1
has rekindled interest in the relationship between nonsteroidal anti-inflammatory
drug (NSAID) use and acute myocardial infarction (AMI). Despite the anti-inflammatory
and antiplatelet effects of NSAIDs, there has never been a randomized controlled
trial that examined whether these drugs confer the protective effects of aspirin
against AMI. In fact, in the study by Bombardier et al, patients with rheumatoid
arthritis randomized to receive rofecoxib had a significantly higher rate
of AMI than patients randomized to receive naproxen.1
Controversy has emerged as to whether this result was the consequence of a
protective effect of naproxen, an increase in the risk of AMI caused by rofecoxib,
or both.
Traditional NSAIDs inhibit cyclooxygenase-2 (COX-2) and thereby reduce
prostaglandin E2 production, resulting in their analgesic, anti-inflammatory,
and antipyretic effects.2 Nonsteroidal anti-inflammatory
drugs also inhibit COX-1, which in turn lowers the level of the platelet aggregating
factor thromboxane B2.3 A similar,
but irreversible, inhibition of thromboxane B2 is thought to underlie
the protective effect of aspirin against AMI,4-6
but the relation between traditional NSAIDs and AMI is unclear. One observational
study7 examined only women after menopause
and found no association between NSAIDs and AMI, but no attempt was made to
look at specific NSAIDs.
Understanding the relationship between NSAID use and the risk of AMI
is important for several reasons. Quantifying the association between specific
NSAIDs and AMI may help to clarify the controversial relationship between
selective COX-2 inhibitors and AMI. If 1 or several NSAIDs reduce the risk
of AMI, patients taking such agents might not also need to take aspirin, a
combination associated with increased risk of gastrointestinal bleeding.8 The goal of the present study was to measure the relation
between AMI and ongoing use of NSAIDs in a large, typical population of older
adults, and to examine whether specific NSAIDs, particularly naproxen, are
associated with a change in the risk of AMI.
SUBJECTS AND METHODS
CASES AND CONTROLS
Eligible patients were participants between January 1, 1991, and December
31, 1995, in the New Jersey Medicaid or Medicare and Pharmaceutical Assistance
for the Aged and Disabled programs. The latter is a state-run drug assistance
program for older adults with moderate incomes and provides prescription benefits
with no or minimal co-payment. We first identified all patients hospitalized
with a main diagnosis of AMI (diagnosis related groups9
121, 122, or 123 or an International Classification of Diseases,
Ninth Revision,10 code 410). In addition,
as in previous studies,11-13
we required that the hospitalization be no longer than 180 days, nor could
it be less than 3 days if the patient was discharged alive. In a recent study13 of more than 5000 persons, using similar data, these
criteria had a positive predictive value of 96.9% for AMI, as validated by
primary medical record reviews. Patients with AMI were considered cases, and
the date of hospital admission for the AMI was defined as the index date.
Potential control subjects were those who did not experience an AMI during
the study period. A random clinical encounter was selected as the index date
for these subjects. Controls were selected at a ratio of 4:1 to cases, with
the groups' frequency matched on the basis of age.
We further required that all potential study subjects demonstrate continuous
use of Medicaid or Medicare and Pharmaceutical Assistance for the Aged and
Disabled, by having a filled prescription, physician visit, or procedure during
the 1 to 180 days, 181 to 365 days, and more than 365 days before their index
date. To reduce confounding by other drugs, we excluded all cases and controls
who filled a prescription for any aspirin-containing compound or warfarin
sodium during the study. We also excluded patients likely to have been regularly
using aspirin, including those with evidence of prior AMI, angina, coronary
artery bypass graft, percutaneous transluminal coronary angioplasty, cerebrovascular
accident, transient ischemic attack, atrial fibrillation, migraine, other
chronic headaches, or rheumatoid arthritis.
Based on these criteria, we created a study-specific database that contained
information on the following: patient age, sex, race, physician visits, hospital
and nursing home use, all recorded diagnoses, all filled prescriptions, and
insurance program enrollment. During the study, essentially all prescribed
drugs were covered without formulary restrictions. Deductibles and co-payments
were absent or minimal, permitting comprehensive capture of medication use
for enrolled subjects. All traceable personal identifiers were erased and
converted to anonymous study codes to protect patient privacy.
NSAID EXPOSURE
Use of prescribed oral NSAIDs in the 6 months before the index date
was the exposure of interest. For each filled prescription, we identified
the National Drug Code (product identifier), date filled, dosage, quantity
dispensed, and days' supply. Several aspects of NSAID use were characterized.
Proximity
To determine the proximity of prescribed NSAID use to the index date,
we examined which days were covered by any NSAID prescriptions during the
prior 180 days. Three categories of proximity were defined: (1) a prescription
that extended through the index date; (2) a prescription that ended 1 to 60
days before the index date; and (3) a prescription that ended 61 to 180 days
before the index date.
Duration
The duration of prescription NSAID coverage in the prior 6 months included
the sum of days supplied for all NSAID prescriptions (subtracting duplicate
days). We created 3 categories of cumulative duration: 1 to 30 days, 31 to
90 days, and 91 to 180 days.
Dosage
The dosage of each NSAID prescription was standardized against the 100%
maximum anti-inflammatory dosage of each NSAID, based on a standard pharmacology
textbook.14 We then calculated the percentage
of maximum anti-inflammatory dosage for each day of each NSAID prescription.
If multiple NSAID prescriptions covered the same day, we summed the percentage
of the maximum anti-inflammatory dosage for each drug. An average was then
calculated by summing all daily percentage data and dividing by the total
number of days covered. This was divided into 3 categories: 50% or less, 51%
to 75%, and 76% or more of maximum anti-inflammatory dosage.
Half-life
The half-life for each NSAID was determined from a standard pharmacology
textbook.14 Half-life was also considered as
a continuous variable in 3 categories: shorter than 5 hours, including ibuprofen,
indomethacin, ketoprofen, diclofenac, fenoprofen, and mefenamic acid; 5 to
14 hours, including naproxen, sulindac, ketorolac tromethamine, flurbiprofen,
tolmetin, and etodolac; and longer than 14 hours, including piroxicam, oxaprozin,
and nabumetone.
COX Selectivity
Each agent's COX-1:COX-2 selectivity ratio was defined based on previously
published in vitro assays.15 This ratio was
examined as a continuous and categorical variable. Agents with COX-1:COX-2
selectivity ratios greater than 1.0 were considered COX-1 selective. This
group consisted of flurbiprofen, ketoprofen, fenoprofen, oxaprozin, tolmetin,
indomethacin, and ibuprofen. Preparations with a COX-1:COX-2 selectivity ratio
less than 0.25 were considered COX-2 selective, including etodolac and diclofenac.
(The newer selective COX-2 inhibitors, celecoxib and rofecoxib, were not in
use during the study.) Those NSAIDs with a COX-1:COX-2 ratio of 0.25 to 1.0
were considered nonselective agents; included in this group were naproxen,
piroxicam, ketorolac, nabumetone, and sulindac.
COX Inhibition
Each drug's absolute capacity to inhibit COX-1 and COX-2 was defined
separately, based on the concentration necessary to inhibit 50% of COX-1 or
COX-2 activity in vitro.15 The daily dosage
for each NSAID taken by every subject was converted into a concentration necessary
to inhibit 50% of activity in vitro for COX-1, and another for COX-2, based
on the peak serum concentration for a typical dosage.16
Separate continuous variables were calculated for COX-1 and COX-2 inhibition
for each person taking an NSAID, represented as multiples of the concentration
necessary to inhibit 50% of COX-1 or COX-2 activity in vitro; each was then
categorized into quintiles.
COVARIATES
Variables considered as potential confounders in multivariate models
included clinical, sociodemographic, and health care use characteristics.
Age, sex, ethnicity, and insurance status were defined from the enrollment
files of Medicaid or Medicare. We examined the 180 days before the index date
to determine whether patients had evidence of hypertension, diabetes mellitus,
or congestive heart failure. In addition, a comorbidity index was calculated
using inpatient and outpatient diagnoses, according to the method of Deyo
et al.17 Health care resource use was determined
for the 180 days before the index date, including the number of hospitalizations,
number of different drug prescriptions, and nursing home use. The year of
the index date was also considered.
STATISTICAL ANALYSIS
We initially compared the baseline characteristics of patients who experienced
an AMI (cases) with those who did not (controls) using  2 tests.
The characteristics of NSAID use were described for all patients and compared
for cases and controls. The risk of AMI in patients with and without NSAID
exposure was described by calculating odds ratios (ORs) and 95% confidence
intervals (CIs) from bivariate logistic models. P
values were examined to determine the significance of each OR. Crude ORs were
calculated for each NSAID exposure category and for individual preparations.
We then used multivariate logistic models that included all covariates to
calculate adjusted ORs. No variable selection programs were used. In each
of these analyses, nonuse of NSAIDs was the reference exposure. Stratified
analyses were performed to compare male vs female naproxen users, and naproxen
users aged 65 years or older vs those younger than 65 years.
To further compare NSAIDs with one another, similar analyses were conducted
in a subsample of subjects who used NSAIDs. We calculated crude and adjusted
ORs, 95% CIs, and P values from logistic models to
determine if specific aspects of NSAID exposure or use of specific NSAIDs
was associated with AMI. The reference exposure in these calculations was
ibuprofen use, which represented the largest group of NSAID users other than
naproxen users.
Finally, we used several approaches to examine the relationship between
AMI and relative COX selectivity and absolute COX inhibition. First, COX selectivity
and COX inhibition were assessed in models that included these (as defined
in this section) as continuous variables and quintiles. A follow-up analysis
considered only subjects taking a single NSAID throughout the study, plotting
the log of the COX-1:COX-2 ratio against the OR of AMI. Because this relationship
was nonlinear, curves were fit using cubic splines in Stata.18
All other analyses were performed using SAS statistical software.19
RESULTS
Table 1 presents the baseline
characteristics of cases and controls. Because the ages of the 2 groups were
frequency matched, the distributions are almost identical. Cases were more
likely to be male and white. Slightly more persons with AMI than controls
were covered by Medicaid, a marker of low-income status. As expected, patients
with an AMI were more likely than controls to have a history of hypertension,
diabetes mellitus, or congestive heart failure. They were also more likely
to have been diagnosed as having any of the comorbid conditions studied. A
larger proportion of cases than controls had been hospitalized or had filled
a prescription in the prior 180 days.
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Table 1. Baseline Patient Characteristics*
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We then compared use of any NSAID in the prior 180 days in persons who
had an AMI vs controls (Table 2).
Twenty-five percent of cases and of controls had filled a prescription for
an NSAID during this period, and the characteristics of exposure were similar.
An equal percentage had prescriptions covering their index date. Cases and
controls also had equal distributions of duration and dosage of NSAIDs. The
distribution of persons exposed to most NSAIDs was comparable across cases
and controls.
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Table 2. Nonsteroidal Anti-inflammatory Drug (NSAID) Exposure*
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Multivariate logistic models that included all covariates and NSAID
exposure in the prior 180 days were examined. No relationship was observed
between NSAID use in the prior 180 days and AMI (OR, 1.00; 95% CI, 0.92-1.08; P = .92)
(Figure 1),
or NSAID use on the index date and AMI (OR, 1.04; 95% CI, 0.92-1.18; P = .55). Likewise, no relationship was found for the proximity
of NSAID use to the index date, the duration of NSAID exposure in the prior
180 days, or the dosage of NSAID.
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Figure 1. Relative risk of acute myocardial
infarction (AMI). For Figures 1 and 2, the reference group is persons who
did not fill any nonsteroidal anti-inflammatory drug (NSAID) prescriptions
before the index date. Models were adjusted for all covariates listed in Table
2, including age, sex, ethnicity, Medicaid enrollment, nursing home use, diabetes
mellitus, hypertension, congestive heart failure, Charlson Comorbidity Index,
number of different drug prescriptions, and number of hospitalizations.
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We next focused on comparison of specific NSAID preparations in the
180 days before the index date (Table 3). In multivariate analyses, naproxen use was significantly less
common among cases compared with controls; it was associated with a 16% reduction
in the risk of AMI (OR, 0.84; 95% CI, 0.72-0.98; P
= .03) (Figure 1). By contrast,
etodolac (OR, 1.28; 95% CI, 1.00-1.64; P = .05) and
fenoprofen (OR, 1.95; 95% CI, 1.16-3.30; P = .01)
appeared to be associated with an increased risk of AMI. Ibuprofen use had
no association with AMI (OR, 1.02; 95% CI, 0.88-1.18). Similar results were
found when the analyses were restricted to NSAID users alone, with ibuprofen
as the reference exposure. A reduced risk of AMI in naproxen users was seen
in both sexes and all ages. However, there was no relationship between AMI
risk and longer duration, higher dosage, or closer proximity to the index
date for naproxen exposure (Table 4).
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Table 3. Relative Risk of Myocardial Infarction Associated With Specific
NSAIDs*
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Table 4. Adjusted Risk of Myocardial Infarction for Persons Taking
Naproxen
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To attempt to understand the relationship between specific NSAID preparations
and AMI, we examined whether half-life, COX selectivity, or specific COX-1
or COX-2 inhibitory potency was associated with AMI. No trend was seen between
half-life and risk of AMI. Patients taking more COX-1 or COX-2 selective agents
appeared to be at a slightly increased risk of AMI, while those taking the
nonselective agents appeared to have a slightly lower risk of AMI (Figure 2) (P = .01
for the cubic spline in multivariate analyses). However, these findings were
affected by data from groups with the largest sample sizes, naproxen and ibuprofen
users. Finally, we assessed the absolute degree of COX-1 and COX-2 inhibition
(regardless of selectivity). There was no consistent relationship between
COX-1 inhibition and AMI, but patients taking NSAID regimens with higher COX-2
inhibitory capacity appeared to be at a slightly higher risk of AMI. Patients
in the highest quintile of COX-2 inhibition had a 25% increased risk of AMI
compared with NSAID nonusers (OR, 1.25; 95% CI, 1.08-1.45; P = .01).
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Figure 2. Relationship between cyclooygenase
(COX) selectivity and acute myocardial infarction (AMI). This curve was fit
using nonlinear assumptions and displays a cubic spline. The solid line represents
the log of the odds ratio (OR) of sustaining an MI based on the log of the
COX-1:COX-2 ratio for each nonsteroidal anti-inflammatory drug (NSAID) regimen
of cases and controls. The dashed lines represent the 95% confidence interval.
Subjects using multiple NSAIDs were excluded from these analyses. Zero on
the x-axis represents nonselective NSAIDs, whereas positive values represent
NSAIDs with COX-1:COX-2 selectivity greater than 1, and negative numbers are
ratios less than 1. On the y-axis, the log of 0.0 signifies an OR of 1.0 for
acute MI, and values below this signify ORs less than 1.0.
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COMMENT
After controlling for different potential confounders, NSAID use in
general was not associated with an increase or decrease in the risk of AMI.
However, naproxen use was associated with an apparent 16% to 20% reduction
in AMI risk. This finding persisted in different subgroups of naproxen users
and in patients using different dosages and durations of this agent, but there
was no relationship between AMI risk and longer duration, higher dosage, or
closer proximity to the index date. Overall, patients using agents that were
nonselective with respect to COX-1:COX-2 specificity had a somewhat lower
risk of AMI, and those taking NSAIDs with the highest COX-2 inhibition appeared
to have a small increased risk of AMI.
A potential limitation associated with this study is the possibility
of misclassification of NSAID exposure because of unmeasured over-the-counter
use of NSAIDs or aspirin, or their use on an as-needed basis. Over-the-counter
or as-needed drug use is not captured in the study database of filled prescriptions.
However, the study was conducted in the context of prescription benefit programs
for low-income and moderate-income patients, through which prescription NSAIDs
were available for free or a minimal co-payment. As a result, over-the-counter
use of NSAIDs, requiring out-of-pocket payment, was less likely than in the
general population. In addition, the study was conducted using data from the
first half of the 1990s, when over-the-counter NSAID use was less common.
More important, because we found similar results after restricting the analyses
to only NSAID users, if over-the-counter NSAID use was substantial, one would
have to postulate that there was differential use of such preparations, depending
on the prescription NSAID.
We attempted to limit over-the-counter aspirin use as a source of unmeasured
confounding by excluding all patients with any diagnoses that might have been
managed with aspirin, such as coronary artery disease, cerebrovascular disease,
atrial fibrillation, rheumatoid arthritis, and chronic headaches, as well
as evidence of prescribed aspirin-containing compounds. If any residual confounding
occurred as a result of undetected aspirin use, it is unlikely that it would
differentially affect only one NSAID, naproxen. Recently presented data from
a detailed patient survey20 suggest that there
is not differential use of aspirin between persons taking prescription NSAIDs,
further supporting the validity of our conclusions.
Although the database that was used for this study presented some potential
limitations, we know of no better sources of data for such a study. Clinical
databases that contain information on electrocardiographic results and serum
cardiac markers generally do not contain detailed drug exposure information
that is based on filled prescriptions for large numbers of patients. The algorithm
we used for identification of AMIs has been previously validated.13
The apparent lack of a dose-response, duration-response, or proximity-response
relationship between naproxen exposure and AMI raises the possibility that
naproxen itself is not involved in the causal pathway reducing the risk of
AMI, but may be a marker for some other factor associated with a reduced risk
of AMI. Furthermore, because we considered many potential relationships and
performed multiple tests of association, there is the possibility of a chance
finding.
In the study by Bombardier et al,1 in
which patients with rheumatoid arthritis were randomized to receive rofecoxib
or naproxen, the rates of AMI were 4-fold higher in patients taking rofecoxib.
These findings could have resulted from a protective effect of naproxen, a
risk-enhancing effect of rofecoxib, or both. The selective COX-2 inhibitors
were not available during the period we studied, and these findings do not
clarify the role of rofecoxib. However, the data presented herein are consistent
with a possible protective effect of naproxen.
It is not clear from the data why naproxen may lower the risk of AMI.
Although a potent COX-1 inhibitor might protect against AMI through inhibiting
thromboxane B2 production and thus reducing platelet aggregation,
naproxen is not a strong inhibitor of COX-1,15, 21-22
and NSAIDs with greater COX-1 inhibition did not demonstrate this effect.
Alternatively, an NSAID with strong COX-2 inhibition might reduce the inflammatory
component of coronary disease by blocking prostaglandin E2 production23; however, naproxen is also not a potent COX-2 inhibitor.15, 21-22 Naproxen is a nonselective
inhibitor of COX-1 and COX-2; several other NSAIDs in this category (piroxicam
and sulindac) also appeared to be associated with a slightly reduced risk
of AMI, although not statistically significant. The effect does not appear
to be related to naproxen's long half-life, because other NSAIDs with equally
long or longer half-lives did not show this effect.
If confirmed in other populations, the findings of this study suggest
that most NSAIDs are not associated with an increased or decreased risk of
AMI. This has substantial clinical implications, indicating that patients
who regularly use most NSAIDs also require the cardioprotective effect of
aspirin. Aspirin may negate the gastrointestinal protective effects of the
selective COX-2 inhibitors.24 The data reported
herein are also compatible with the possibility that naproxen use is associated
with a small reduction in the risk of AMI. To place the effect of naproxen
in perspective, in a large randomized trial of daily aspirin use in primary
prevention, patients in the intervention arm experienced a 44% reduction in
the risk of AMI.5 Therefore, it would be false
to equate the more modest effect of naproxen suggested in this study with
the cardioprotection afforded by aspirin. Cyclooxygenase selectivity and specific
potency may be associated with AMI risk, with nonselective agents possibly
related to a reduced risk, and agents with higher COX-2 inhibition potentially
conferring a slight risk. Other data suggest that selective COX-2 inhibitors
may be associated with an increased risk of thrombosis and AMI.25-26
Although our study does not lend evidence to the mechanisms for this potential
relationship, it is known that eicosanoids are important regulators of vascular
homeostasis and that the COX-2 gene is preferentially
expressed in areas of high endovascular shear stress.27-28
More research is needed to explore the relationship between specific nonselective
and selective NSAIDs and the risk of AMI.
AUTHOR INFORMATION
Accepted for publication January 31, 2002.
Dr Solomon received an Investigator Award from the Arthritis Foundation,
Atlanta, Ga. This work was also supported by grant RO3-AG18395 from the National
Institute on Aging, Bethesda, Md. No support from any pharmaceutical company
was received for this research.
Corresponding author and reprints: Daniel H. Solomon, MD, MPH, Division
of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital,
Harvard Medical School, 221 Longwood Ave, Suite 341, Boston, MA 02115 (e-mail: dhsolomon{at}partners.org).
From the Divisions of Pharmacoepidemiology and Pharmacoeconomics (Drs
Solomon, Glynn, and Avorn and Ms Levin) and Rheumatology, Immunology, and
Allergy (Dr Solomon), Brigham and Women's Hospital, Harvard Medical School,
Boston, Mass.
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