Original Investigation | Nephrology
Association of Nonsteroidal Anti-inflammatory Drug Prescriptions
With Kidney Disease Among Active Young and Middle-aged Adults
D. Alan Nelson, MPAS, PhD; Eric S. Marks, MD; Patricia A. Deuster, PhD, MPH; Francis G. O’Connor, MD, MPH; Lianne M. Kurina, PhD
Abstract
IMPORTANCE Concern about the renal effects of nonsteroidand al anti-inflammatory drugs
(NSAIDs) among young, healthy adults has been limited, but more attention may be warranted given
the prevalent use of these agents.
OBJECTIVE To test for associations between dispensed NSAIDs and incident acute kidney injury and
chronic kidney disease while controlling for other risk factors.
Key Points
Question What is the association
between prescribed dosages of
nonsteroidal anti-inflammatory drugs
and later incident kidney disease among
active young and middle-aged adults?
Findings In this cohort study of
764 228 US Army soldiers, prescriptions
DESIGN, SETTING, AND PARTICIPANTS This retrospective, longitudinal cohort study used
of more than 7 daily defined doses of
deidentified medical and administrative data on 764 228 active-duty US Army soldiers serving
nonsteroidal anti-inflammatory drugs
between January 1, 2011, and December 31, 2014. Analysis was conducted from August 1 to
per month were associated with modest
November 30, 2018. All individuals new to Army service were included in the analysis. Persons
but significant increases in the adjusted
already serving in January 2011 were required to have at least 7 months of observable time to
hazard ratios of acute and chronic
eliminate those with kidney disease histories.
kidney disease diagnoses.
Meaning Prescribers should be
EXPOSURES Mean total defined daily doses of prescribed NSAIDs dispensed per month in the prior
6 months.
cognizant of potential kidney disease
risks associated with higher doses of
nonsteroidal anti-inflammatory drugs
MAIN OUTCOMES AND MEASURES Incident outcomes were defined by diagnoses documented in
health records and a military-specific digital system.
among active young and middle-aged
adults; dosage reduction represents an
approach that may decrease associated
RESULTS Among the 764 228 participants (655 392 [85.8%] men; mean [SD] age, 28.6 [7.9] years;
kidney disease outcome rates.
median age, 27.0 years [interquartile range, 22.0-33.0 years]), 502 527 (65.8%) were not dispensed
prescription NSAIDs in the prior 6 months, 137 108 (17.9%) were dispensed 1 to 7 mean total defined
daily doses per month, and 124 594 (16.3%) received more than 7 defined daily doses per month.
There were 2356 acute kidney injury outcomes (0.3% of participants) and 1634 chronic kidney
disease outcomes (0.2%) observed. Compared with participants who received no medication, the
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highest exposure level was associated with significantly higher adjusted hazard ratios (aHRs) for
acute kidney injury (aHR, 1.2; 95% CI, 1.1-1.4) and chronic kidney disease (aHR, 1.2; 95% CI, 1.0-1.3),
with annual outcome excesses per 100 000 exposed individuals totaling 17.6 cases for acute kidney
injury and 30.0 cases for chronic kidney disease.
CONCLUSIONS AND RELEVANCE Modest but statistically significant associations were noted
between the highest observed doses of NSAID exposure and incident kidney problems among active
young and middle-aged adults.
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Introduction
Nonsteroidal anti-inflammatory drugs (NSAIDs) are widely used in the United States in prescription
and over-the-counter forms,1 with more than 70 million NSAID prescriptions written annually.2 In
2010, more than 29 million US adults were estimated to be regular NSAID users—an increase of 41%
from 2005.3 A recent study of self-reported over-the-counter and prescribed ibuprofen therapy
noted that 90% of those using ibuprofen took it regularly, 37% took another NSAID in addition to
ibuprofen, and 11% exceeded the recommended daily limit of ibuprofen.4
Clinicians who prescribe or recommend NSAIDs should weigh the benefits vs the risks for
kidney health. Both selective and nonselective NSAIDs adversely affect the kidneys through
prostaglandin-related effects.5 Potential insults include impaired renal blood flow and clinically
significant cytotoxic effects.6 Signs and symptoms associated with NSAID use that can complicate
blood pressure management, such as hypertension and edema, are relatively infrequent5 but
important.
Most epidemiologic research on the association of NSAIDs and incident kidney disease has
involved older persons and/or those with chronic and serious conditions.7-13 Particularly regarding
chronic and end-stage kidney disease, NSAID-related research has often focused on specific areas,
such as disease progression.14,15 For younger healthy individuals, some studies provide statements of
reassurance about the overall risks of NSAIDs16 and, in particular, about their renal effects.17
However, evidence on this demographic group is relatively sparse. This limited information may be
because NSAID use is less common among young and middle-aged adults,1 and the expected
population rate of clinically significant kidney disease due to NSAIDs is less than 1%.18
Studying the NSAID-kidney disease association among working-aged adults therefore requires
a large group with robust NSAID use. United States Army soldiers are a useful study population given
recent research indicating that 69% or more of this sizable population may use NSAIDs.19 In addition,
prior studies have raised concerns about kidney disease risk among NSAID users who engage in
endurance exercise,20-22 as renal blood flow may fall to as little as 25% of resting values during
strenuous activity.23 The Army population is one in which endurance activities, such as running24 and
long-distance rucksack marching,25 are regularly undertaken, so this group provides a unique
window on NSAIDs and kidney disease among active persons. Other advantages of using a military
population include standardized, comprehensive administrative and medical data, as well as
preservice, annual, and combat duty–associated health screenings26 that facilitate recognition of
incident diseases.
We therefore used data on the total active-duty US Army to estimate the independent
associations between prescribed oral NSAID use and incident acute kidney injury (AKI) and chronic
kidney disease (CKD). Renal effects of NSAIDs have been shown to be dose dependent.18 Increased
frequency and duration of NSAID use amplify the risk of nonrenal adverse effects.18,27 Accordingly,
we devised methods to study NSAID exposure volume over time while controlling for major factors of
potential relevance to kidney dysfunction.
Methods
Population and Data
This retrospective cohort study was conducted with longitudinal data on the active-duty US Army
collected from January 1, 2011, to December 31, 2014. Data were combined from official sources
(eTable 1 in the Supplement) and stripped of identifiers. Analyses were conducted from August 1 to
November 30, 2018. The institutional review board of Stanford University approved this study, which
underwent secondary review by the Human Research Protections Office of the Defense Health
Agency. A waiver of consent was granted because the research (1) involves no more than minimal risk
to the participants, (2) does not affect the rights or welfare of the participants, and (3) could not
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practically be carried out without the waiver of consent. The study followed the Strengthening the
Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.28
To facilitate time-to-event analyses, we used a person-month–based data set in which each
participant was censored from further observation either after the incident outcome or, if applicable,
on discharge from military service. Owing to the health screening associated with initiating service,26
soldiers who began duty during 2011-2014 were considered at risk for outcomes for all of the
observed time because known kidney conditions would usually disqualify an applicant.
However, for soldiers already on duty in 2011, observation for incident outcomes began at the
earliest recorded health maintenance encounter in or after July 2011. We required at least 6 months
of observable time prior to the month of such examinations to increase detection of prior kidney
problems (a total of 7 months of observation). Only soldiers with no diagnoses of AKI prior to or at
the health maintenance encounter were included in the AKI analytic population. Similarly, only
soldiers with no indication of CKD prior to or at their health maintenance encounter were included in
the CKD analytic population.
Of 827 265 active Army soldiers who served during 2011-2014, a total of 764 228 met eligibility
criteria for at least 1 of the 2 end point–specific analyses. In the AKI analysis, there were 763 572
persons observed for 1 705 533 person-years (mean [SD], 2.1 [1.1] person-years; median, 2.4 personyears). The 763 654 participants included in the CKD analysis were observed for 1 705 944 personyears (mean [SD], 2.2 [1.1] person-years; median, 2.4 person-years). There were 763 178 participants
present in both analyses.
Dependent Variables
During 2011-2014, the Army used the International Classification of Disease, Ninth Revision, Clinical
Modification (ICD-9-CM) system. We identified outcomes from diagnoses in outpatient and inpatient
care by using ICD-9-CM codes for AKI (584.x, 586, 580.9) and CKD (581.x, 583.x, 585.x, 587),
following the convention of prior studies.6,9,29-31 A dedicated data system (eProfile) is an additional
repository outside the health record per se in which soldiers' duty-limiting health conditions are
tracked.32 We therefore also defined outcomes by using eProfile entries noting relevant kidney
conditions.
Independent Variables
Demographic Factors
Multiple demographic factors were included to control for potential confounding. Sex and Hispanic
ethnicity were binary variables. Running age in years and self-reported race were categorical
covariates.
Administrative Factors
We controlled for socioeconomic status by using each participant's running military pay grade.33
Total service time was updated each person-month. Combat duty was included as a covariate
because of the associated potential for an increase in outcome risk due to injury or surgery.
Biomedical Factors
We used an NSAID exposure variable based on dispensed prescription medications and agentspecific World Health Organization–defined daily doses (DDDs),34 which represent estimates of
typical maintenance doses for adults.35 The categorical variable represented the mean of the total
monthly NSAID DDDs dispensed in the 6 months preceding each observation. This rolling window
was used to capture exposures that were sufficiently long but also recent with regard to expected
kidney effects; the present month was excluded to reduce the potential for overdose as a causal
mechanism.
The ICD-9-CM codes were used to identify histories of the potentially contributory conditions
hypertension36 (401.x, 402.x, 405) and type 1 or 2 diabetes37 (250.x). We included a covariate for a
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remote history of rhabdomyolysis (728.88, 791.3; ⱖ6 months in the past), as its immediate
association with kidney injury appears to be well established.38 We further controlled for body mass
index39 by using its standard categories,40 plus a category for missing data. Other potentially
contributory conditions (eg, systemic lupus erythematosus41) were explored, but were deemed too
infrequent in this population for inclusion.
Statistical Analysis
To characterize the types and quantities of NSAID exposures, we tabulated counts of specific agent
classes dispensed to study participants and percentages thereof. Preregression analyses included χ2
tests of distribution differences for selected covariates. To estimate the independent associations of
NSAIDs with the kidney outcomes, we used dedicated Cox proportional hazards regression models
for AKI and CKD. We also computed the adjusted risk of each outcome for participants in each of the
NSAID exposure categories. These figures were calculated by totaling the products of the Cox
regression coefficients and the covariate values, which permitted a computation of the absolute risk
differences among the NSAID exposure groups. We additionally performed Wald tests for the
interaction between selected medical conditions and NSAID use. In all analyses, 2-sided α < .05
defined statistical significance. All analyses were conducted using Stata statistical software, version
14.2 (StataCorp).
Results
Of the 764 228 total participants, 655 392 (85.8%) were men; mean (SD) age was 28.6 (7.9) years
(median, 27.0 years; interquartile range [IQR], 22.0-33.0 years); and 238 168 (31.2%) were new to the
military during 2011-2014. There were 1 630 694 distinct NSAID prescriptions dispensed to
participants during the total observation period, or a mean (SD) 2.1 (2.7) total prescriptions per
person (median, 1). A total of 502 527 participants (65.8%) were not dispensed prescription NSAIDs
in the prior 6 months, 137 108 (17.9%) were dispensed 1 to 7 mean total DDDs per month, and
124 594 (16.3%) received more than 7 DDDs per month. The mean (SD) DDD per prescription was 1.6
(1.0) (median, 2; IQR, 1.0-2.0). Ibuprofen and naproxen were the most commonly prescribed
preparations and together accounted for 1 180 549 (72.4%) of the NSAIDs dispensed (Table 1). Of the
804 471 ibuprofen prescriptions, 78.3% were for 800-mg tablets, and 88.4% allowed for 3 or more
daily doses. Of the 376 078 naproxen prescriptions, 95.7% were for 500-mg or stronger tablets, and
93.8% allowed for at least twice-daily use.
There were 763 752 participants eligible for the AKI analysis, among whom 2356 (0.3%)
experienced incident AKI events. Among the AKI outcomes, 13 (0.6%) were detected from eProfile
data rather than diagnoses in the electronic health record. Of 763 654 individuals eligible for the CKD
Table 1. Top NSAIDs Dispensed to 764 228 Study Participants
Agenta
NSAID Class
Prescriptions, No. (%)b
Ibuprofen
Propionic acid derivative
804 471 (49.3)
Naproxen
Propionic acid derivative
376 078 (23.1)
Meloxicam
Enolic acid derivative
176 638 (10.8)
Celecoxib
Selective COX-2 inhibitor
119 680 (7.3)
Acetylsalicylic acid
Salicylate (aspirin)
35 949 (2.2)
Diclofenac
Acetic acid derivative
34 118 (2.1)
Ketorolac
Acetic acid derivative
27 236 (1.7)
Indomethacin
Acetic acid derivative
24 795 (1.5)
Piroxicam
Enolic acid derivative
18 237 (1.1)
Etodolac
Acetic acid derivative
7142 (0.4)
Other
Multiple
6350 (0.4)
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Abbreviations: COX-2, cyclooxygenase 2; NSAIDs,
nonsteroidal anti-inflammatory drugs.
a
Suffix elements and compounds associated with the
active component of applicable agents (eg, sodium)
were omitted for simplicity.
b
There were 1 630 694 prescriptions dispensed in
total during the observed time. Percentages may not
total 100 owing to rounding.
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analysis, 1634 (0.2%) experienced incident CKD, including 9 cases (0.6%) solely detected via
eProfile.
Histories of diabetes or rhabdomyolysis were present among fewer than 1% of the participants,
while hypertension was more prevalent at up to 8.8%. We did, however, observe statistically
significant differences in the distributions of biomedical and demographic factors comparing groups
with and without NSAID exposure (Table 2). The proportion of women increased from 12.5% of
those without NSAID use to 18.3% of those in the highest use group. Individuals who received the
Table 2. Description of the 764 228 Participants at the Final Observationa
No. (%)
NSAID DDDs
Factorb
No NSAID
1-7
>7
Total
502 527 (65.8)
137 107 (17.9)
124 594 (16.3)
Male
439 916 (87.5)
113 708 (82.9)
101 768 (81.7)
Female
62 611 (12.5)
23 399 (17.1)
22 826 (18.3)
P Value for χ2 Testc
Sex
<.001
Race
White
356 886 (71.0)
91 898 (67.0)
83 813 (67.3)
African American
98 650 (19.6)
31 848 (23.2)
28 520 (22.9)
Asian/Pacific Islander
24 818 (4.9)
6635 (4.8)
5025 (4.0)
Native American
3969 (0.8)
1102 (0.8)
1077 (0.9)
Other or unknown
18 204 (3.6)
5624 (4.1)
6159 (4.9)
No
441 914 (87.9)
120 208 (87.7)
110 027 (88.3)
Yes
60 613 (12.1)
16 899 (12.3)
14 567 (11.7)
≤22
177 029 (35.2)
41 811 (30.5)
29 278 (23.5)
23-27
135 509 (27.0)
37 912 (27.7)
30 355 (24.4)
28-35
104 630 (20.8)
29 672 (21.6)
28 020 (22.5)
36-41
49 478 (9.8)
15 206 (11.1)
18 488 (14.8)
42-49
30 793 (6.1)
10 335 (7.5)
15 241 (12.2)
≥50
5088 (1.0)
2171 (1.6)
3212 (2.6)
No
501 176 (99.7)
136 590 (99.6)
124 106 (99.6)
Yes
1351 (0.3)
517 (0.4)
488 (0.4)
<.001
Hispanic ethnicity
<.001
Age, y
<.001
Experienced acute kidney injury
<.001
Experienced chronic kidney disease
No
501 664 (99.8)
136 737 (99.7)
124 193 (99.7)
Yes
863 (0.2)
370 (0.3)
401 (0.3)
<18.5 (Underweight)
1623 (0.3)
529 (0.4)
452 (0.4)
18.5-24.99 (Normal)
155 863 (31.0)
44 472 (32.4)
33 110 (26.6)
25.0-29.99 (Overweight)
205 591 (40.9)
62 586 (45.7)
58 806 (47.2)
≥30.0 (Obese)
62 075 (12.4)
24 305 (17.7)
29 361 (23.6)
Unknown
77 375 (15.4)
5215 (3.8)
2865 (2.3)
No
484 500 (96.4)
128 523 (93.7)
113 605 (91.2)
Yes
18 027 (3.6)
8584 (6.3)
10 989 (8.8)
500 814 (99.7)
135 976 (99.2)
123 516 (99.1)
<.001
BMI
<.001
Any observed history of hypertension
<.001
Abbreviations: BMI, body mass index (calculated as
weight in kilograms divided by height in meters
squared); DDDs, defined daily doses; NSAID,
nonsteroidal anti-inflammatory drug.
a
Column percentage totals may not total 100 owing
to rounding.
b
eTable 2 in the Supplement provides other
descriptive data on military service time, pay grade,
and combat experience.
c
The P values indicate results of χ2 tests comparing
factor distributions for those that were and were not
found in each NSAID exposure category.
Any observed history of diabetes
No
Yes
1713 (0.3)
1131 (0.8)
1078 (0.9)
No
501 714 (99.8)
136 854 (99.8)
124 340 (99.8)
Yes
813 (0.2)
253 (0.2)
254 (0.2)
<.001
History of rhabdomyolysis ≥6 mo prior
.003
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greatest NSAID volumes were twice as likely to be obese, composing 23.6% and 12.4% of the highest
and lowest NSAID categories, respectively. Individuals who received the greatest NSAID volumes
were also twice as likely to have histories of hypertension (8.8% vs 3.6% of the highest and lowest
NSAID categories) and diabetes (0.9% vs 0.3% of the highest and lowest NSAID categories). African
American participants were more highly represented among those who received the highest level
of prescription NSAIDs than those who received none (22.9% vs 19.6%) (Table 2). Statistically
significant differences in distributions were also observed for each of the military-specific factors. For
example, increasing duration of military service was associated with increased NSAID use.
Specifically, those with greater than 12 years of service made up 19.4% of the no NSAIDs group and
30.4% of the highest NSAIDs group (eTable 2 in the Supplement).
Results of analyses addressing the primary study aim are reported in Table 3. NSAID exposure
Table 3. Analysis of Associations Between NSAID Use and Kidney Diseasea
aHR (95% CI)
Factor
Acute Kidney Injury
Chronic Kidney Disease
Total DDDs prescribed per month in the prior 6 mo, mean
0
1 [Reference]
1 [Reference]
1-7
1.1 (1.0-1.2)
1.1 (0.9-1.3)
>7
1.2 (1.1-1.4)b
1.2 (1.0-1.3)c
<18.5 (Underweight)
1.1 (0.5-2.7)
2.0 (0.7-5.3)
18.5-24.99 (Normal)
1 [Reference]
1 [Reference]
25.0 to 29.99 (Overweight)
1.2 (1.1-1.4)
1.1 (1.0-1.3)b
BMI
b
1.6 (1.3-1.8)b
b
0.7 (0.5-0.8)
0.4 (0.3-0.6)b
Yes
3.2 (2.9-3.6)b
4.5 (4.0-5.1)b
No
1 [Reference]
1 [Reference]
Yes
1.8 (1.4-2.4)b
1.8 (1.4-2.2)b
No
1 [Reference]
1 [Reference]
Yes
2.9 (1.9-4.7)b
2.7 (1.7-4.4)b
No
1 [Reference]
1 [Reference]
Male
2.3 (2.0-2.7)b
1.6 (1.4-1.9)b
Female
1 [Reference]
1 [Reference]
≥30.0 (Obese)
Unknown
1.5 (1.3-1.7)
History of hypertension
History of diabetes
History of rhabdomyolysis >6 mo
Sex
Race
White
1 [Reference]
1 [Reference]
African American
1.6 (1.4-1.7)b
2.3 (2.0-2.5)b
Asian/Pacific Islander
0.9 (0.8-1.2)
1.1 (0.9-1.4)
Native American
0.9 (0.6-1.5)
0.3 (0.1-1.0)
Other or unknown
1.1 (0.9-1.4)
1.1 (0.8-1.4)
Yes
0.8 (0.6-0.9)d
1.0 (0.8-1.2)
No
1 [Reference]
1 [Reference]
Hispanic ethnicity
Age, y
≤22
1 [Reference]
1 [Reference]
23-27
1.3 (1.1-1.5)d
1.5 (1.1-2.0)d
28-35
b
2.1 (1.6-3.0)b
b
3.7 (2.7-5.2)b
b
36-41
1.5 (1.2-1.7)
1.8 (1.5-2.2)
Abbreviations: aHR, adjusted hazard ratio; BMI, body
mass index (calculated as weight in kilograms divided
by height in meters squared); DDDs, defined daily
doses; NSAID, nonsteroidal anti-inflammatory drug.
a
Cox proportional hazards regression models used in
analyses. The models additionally controlled for
military service time, pay grade, and combat
experience. eTable 3 in the Supplement provides
related findings.
b
P < .001.
42-49
2.1 (1.7-2.6)
5.0 (3.5-7.1)b
c
P < .05.
≥50
3.1 (2.3-4.1)b
7.1 (4.8-10.4)b
d
P < .01.
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of 7 or more DDDs per month was associated with significant increases in the adjusted hazard ratios
(aHRs) of both AKI (aHR, 1.2; 95% CI, 1.1-1.4) and CKD (aHR, 1.2; 95% CI, 1.0-1.3). Based on
postregression-adjusted risk computations, the highest NSAID exposure level was associated with
annual case excesses per 100 000 exposed individuals of 17.6 cases for AKI and 30.0 cases for CKD.
Mean NSAID exposure of 1 to 7 DDDs was associated with smaller hazard increases that were not
significant.
Obesity was associated with significant increases in the hazard of each outcome (AKI: aHR, 1.5;
95% CI, 1.3-1.7; CKD: aHR, 1.6; 95% CI, 1.3-1.8), and overweight status was also associated with a
modest, significant increase in the hazard of AKI (aHR, 1.2; 95% CI, 1.1-1.4). Histories of hypertension
(AKI: aHR, 3.2; 95% CI, 2.9-3.6; CKD: HR, 4.5; 95% CI, 4.0-5.1) and rhabdomyolysis (AKI: aHR, 2.9;
95% CI, 1.9-4.7; CKD: aHR, 2.7; 95% CI, 1.7-4.4) were each associated with greater than 2-fold
increases in the adjusted hazard of both outcomes, while diabetes conferred smaller increases (AKI:
aHR, 1.8; 95% CI, 1.4-2.4; CKD: aHR, 1.8; 95% CI, 1.4-2.2) (Table 3). Statistically significant associations
with kidney outcomes were also observed for multiple demographic factors. Male sex was associated
with more than twice the adjusted hazard of AKI (aHR, 2.3; 95% CI, 2.0-2.7) and a smaller but
significant increase in the CKD hazard (aHR, 1.6; 95% CI, 1.4-1.9). African American participants had
more than twice the hazard of CKD (aHR, 2.3; 95% CI, 2.0-2.5) compared with white participants,
and a smaller, significant increase for AKI (aHR, 1.6; 95% CI, 1.4-1.7). Participants of Hispanic ethnicity
had a lower adjusted hazard of AKI (aHR, 0.8; 95% CI, 0.6-0.9) relative to other ethnicities.
Participants older than 22 years had a higher adjusted hazard of each outcome compared with
younger participants. The association with age was strongest in the CKD analysis, where those aged
42 to 49 years experienced a 5.0-fold hazard increase (95% CI, 3.5-7.1), and individuals 50 years or
older experienced a 7.1-fold increase (95% CI, 4.8-10.4). Statistically significant hazard increases were
also found in association with some military-specific factors (eTable 3 in the Supplement).
To address the issue of whether the selected medical condition covariates might interact with
NSAID use, we conducted a formal test of the statistical significance of each such interaction
(hypertension, diabetes, and rhabdomyolysis). Only the interaction between prior hypertension and
NSAIDs in the CKD analysis was statistically significant (aHR, 0.7; 95% CI, 0.5-0.9). This finding
provides some evidence that, in this population, the association between NSAIDs and CKD is
significantly weaker among those with prior hypertension than those without.
Discussion
In this study we identified modest but statistically significant associations between the highest level
of dispensed NSAIDs and incident AKI and CKD in a large military population. Specifically, the
adjusted hazard of each outcome was approximately 20% higher among participants who received
more than 7 total NSAID DDDs per month compared with those who did not receive prescription
NSAIDs. This level of use was associated with 17.6 and 30.0 additional cases per exposed 100 000
persons per year for AKI and CKD, respectively. These potentially preventable cases are of particular
concern in a population in which medical readiness is a foundation of national security. Because most
participants were younger than 35 years and free of hypertension, diabetes, and/or rhabdomyolysis,
this study provided an unusual opportunity to evaluate young, healthy, active adults who received
relatively high NSAID doses (mean, 1.6 DDDs per prescription). No significant elevation in risk was
observed among soldiers prescribed between 1 and 7 DDDs of NSAIDs per month.
The NSAID-related risk estimates for AKI in other studies have ranged from approximately 2- to
8-fold increases,8-10 which are higher than what we found in our analysis. Our risk estimates for CKD
associated with NSAIDs were relatively similar to those seen in one analysis,12 but lower than the
doubling of risk reported elsewhere.7 Direct comparison with past studies is challenging because
most have focused on older patients and those with comorbidities, and also because of varying
outcome and exposure definitions.
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Other findings included elevated hazards of incident AKI and CKD with increasing age and
among men and African American participants. Our CKD findings differed from those seen in the
United States Renal Data System, where women demonstrated a higher CKD rate.42 Hispanic soldiers
had a lower hazard of AKI compared with non-Hispanic individuals.
Strengths and Limitations
Strengths of this study include the use of standardized, detailed data on a large population and the
ability to exclude those with prior disease. Our results may generalize reasonably well to nonmilitary
adults of similar ages, but exposures among service members might differ substantially from those
of civilians. In addition to required physical exertion, the life of most Army soldiers includes regular
field training in outdoor settings. Most US Army installations are in the warm US south,43 and recent
combat deployments have taken place in largely hot and arid regions. Therefore, intermittent
dehydration that further depletes fluid volume and increases the strain on the kidneys44 may be
unusually frequent or substantial among soldiers. Our study's results may most closely apply to
civilians with strenuous, potentially dehydration-producing occupations, such as athletes,
firefighters, and farm, construction, and industrial workers.
This research was subject to the limitations of diagnosis coding, including general imprecision.
One concern associated with diagnosis code validity could be case underdetection,45,46 which may
arise when procedure codes, such as for kidney transplantation, are entered rather than kidney
disease codes.47 This issue is likely less important in our study population because early and accurate
identification of serious conditions is a key duty of military clinicians to ensure adherence to medical
service standards for training and duty.26 A diagnosis would usually occur well before advanced
procedures, such as hemodialysis or transplantation, are required. Also, our data sets afforded
somewhat augmented event detection owing to clinician entries in the eProfile record system.
We nonetheless acknowledge that our CKD case detection mechanisms may have been
reduced by our relatively short follow-up times, as clinical diagnoses and eProfile entries may have
occurred afterward for some participants. Misclassification of AKI as CKD and vice versa constitutes
another specific possible form of potential imprecision in our data, but the similar findings for the
outcomes reduce this concern. We also acknowledge that the sensitivity and specificity of diagnosis
codes may further vary in unknown ways, such as across exposure strata. More generally, as in any
observational study, residual confounding is possible. However, the wide array of demographic,
job-related, and health-related control variables used should reduce concerns.
Other limitations of the study arise from our reliance on dispensed NSAID prescriptions to
quantify drug exposure. Whereas our data captured clinicians' instructions, there was no mechanism
to observe the details of individual NSAID use. We would expect this approach to have created
conservative association estimates because if prescription NSAID intake varied from the total
quantity prescribed, it was presumably lower. However, we were unable to account for over-thecounter NSAID use, which could have offset this phenomenon.
Of the participants, 238 168 (31.2%) were new to the Army during the observation period.
These individuals differed in gross exposure to the military environment from those with greater
total service times. Furthermore, the presence of experienced soldiers in the data set represents a
possible selection sieve, as these soldiers have served for potentially many years. We included the
covariates for age, service time, and combat experience specifically to provide control for
these factors.
Recently, a more cautious tone has permeated the discussion about NSAID use,45,48,49 with
concerns including the potential delayed or inhibited healing associated with pain management.50
Nonpharmacologic interventions are increasingly emphasized,51 and research evidence on such
options is available.52 Our findings provide additional support for the need for expanded research on
alternative treatment options for pain and a greater focus on patient education about the risks and
benefits of higher doses of NSAIDs.
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Conclusions
We have identified modest but statistically significant associations between the highest level of
observed NSAID exposure and incident AKI and CKD among active, largely healthy adults in the
military. While recognizing that the pain burden in such active populations must be managed using
the best-available measures, given the relatively high mean DDD per prescription we observed,
providing lower doses is one approach to those with pain and/or inflammation. The increases in
kidney disease risk that we observed for modifiable factors, such as body mass index and
hypertension, reinforce the established importance of managing these conditions, regardless of
patient age.
ARTICLE INFORMATION
Accepted for Publication: December 16, 2018.
Published: February 15, 2019. doi:10.1001/jamanetworkopen.2018.7896
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2019 Nelson DA
et al. JAMA Network Open.
Corresponding Author: Lianne M. Kurina, PhD, Division of Primary Care and Population Health, Department of
Medicine, Stanford University School of Medicine, 450 Serra Mall, Bldg 20, Stanford, CA 94305 (lkurina@
stanford.edu).
Author Affiliations: Division of Primary Care and Population Health, Department of Medicine, Stanford University
School of Medicine, Stanford, California (Nelson, Kurina); Division of Nephrology, Department of Medicine,
Uniformed Services University, Bethesda, Maryland (Marks); Consortium for Health and Military Performance,
Department of Military and Emergency Medicine, Uniformed Services University, Bethesda, Maryland (Deuster,
O’Connor).
Author Contributions: Drs Nelson and Kurina had full access to all of the data in the study and take responsibility
for the integrity of the data and the accuracy of the data analysis.
Concept and design: Nelson, Kurina.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Nelson, Marks.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Nelson, Kurina.
Obtained funding: Nelson, Deuster, Kurina.
Administrative, technical, or material support: Nelson.
Supervision: Nelson, Deuster, Kurina.
Conflict of Interest Disclosures: Dr Kurina reported a grant from National Heart, Lung, and Blood Institute during
the conduct of the study. No other disclosures were reported.
Funding/Support: The National Heart, Lung, and Blood Institute funded this project in collaboration with the
Uniformed Services University of the Health Sciences (grant Y01 L14007001/HL/NHLBI).
Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study;
collection, management, analysis, and interpretation of the data; preparation, review, or approval of the
manuscript; and decision to submit the manuscript for publication.
Disclaimer: The content of this article was produced by the authors and does not represent the position of the US
government, the US Department of Defense, or any subordinate agencies thereof.
Additional Contributions: David V. Nelson, BS Pharm (Publix pharmacy manager), provided input on nonsteroidal
anti-inflammatory drug classes and real-world clinician prescribing patterns. There was no financial compensation.
All data used in the study were provided under cooperative agreements with the US Army Medical Command.
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SUPPLEMENT.
eTable 1. Descriptions of the Data Sources Leveraged to Produce the Research Datasets
eTable 2. Raw Counts (Percentages) of Subjects (N = 764,228) Organized by Traits, Outcomes and Drug Exposure
at the Last Observation
eTable 3. Adjusted Hazard Ratios (HRs) and Statistical Significance Indicators From Cox Proportional Hazards
Regression Models
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