Visual Overview
Abstract
Background and objectives Avoiding nonsteroidal anti-inflammatory drugs is important for safe CKD care. This study examined nonsteroidal anti-inflammatory drug use patterns and their association with other analgesic use in CKD.
Design, setting, participants, & measurements The Chronic Renal Insufficiency Cohort Study is an observational cohort study that enrolled 3939 adults ages 21–74 years old with CKD between 2003 and 2008 using age-based eGFR inclusion criteria. Annual visits between June of 2003 and December of 2011 were organized into 15,917 visit-pairs (with an antecedent and subsequent visit) for 3872 participants with medication information. Demographics, kidney function, and clinical factors were ascertained along with report of nonsteroidal anti-inflammatory drug or other analgesic use in the prior 30 days.
Results In our study, 24% of participants reported nonsteroidal anti-inflammatory drug use at baseline or at least one follow-up study visit. Having a 10 ml/min per 1.73 m2 higher eGFR level at an antecedent visit was associated with higher odds of starting nonsteroidal anti-inflammatory drugs at a subsequent visit (odds ratio, 1.44; 95% confidence interval, 1.34 to 1.56). Seeing a nephrologist at the antecedent visit was associated with lower odds of starting or staying on nonsteroidal anti-inflammatory drugs at a subsequent visit (odds ratio, 0.70; 95% confidence interval, 0.56 to 0.87 and odds ratio, 0.61; 95% confidence interval, 0.46 to 0.81, respectively). Starting and stopping nonsteroidal anti-inflammatory drugs were both associated with higher odds of increasing the number of other analgesics (odds ratio, 1.52; 95% confidence interval, 1.25 to 1.85 and odds ratio, 1.78; 95% confidence interval, 1.39 to 2.28, respectively) and higher odds of increasing the number of opioid analgesics specifically (odds ratio, 1.92; 95% confidence interval, 1.48 to 2.48 and odds ratio, 1.46; 95% confidence interval, 1.04 to 2.03, respectively).
Conclusions Nonsteroidal anti-inflammatory drug use is common among patients with CKD but less so among those with worse kidney function or those who see a nephrologist. Initiation or discontinuation of nonsteroidal anti-inflammatory drugs is often associated with supplementation with or replacement by, respectively, other analgesics, including opioids, which introduces possible drug-related problems when taking these alternative analgesics.
Introduction
Maintaining patient safety is important for quality CKD care. To ensure patient safety, CKD practice guidelines recommend avoidance of nephrotoxic medications, including nonsteroidal anti-inflammatory drugs (NSAIDs), given their recognized renal toxicity (1–3). Nonetheless, studies reveal a surprisingly high rate of NSAID use in CKD (4,5). Automated reporting of eGFR is associated with a decline in NSAID prescribing in CKD (6), but it has had limited effect on dosing errors of other drugs (7), and serum creatinine may be a stronger determinant of NSAID avoidance than eGFR (8).
The Chronic Renal Insufficiency Cohort (CRIC) Study is an observational study of persons with predialysis CKD who undergo annual visits and ascertainment of prescription and over-the-counter medication usage. Longitudinal follow-up of the CRIC Study participants permits determination of trends in NSAID usage and factors associated with changes in use. This study attempts to identify the frequency and patterns of NSAID usage, determine how kidney function influences NSAID usage, and examine how NSAIDs affect other analgesic use.
Materials and Methods
The CRIC Study enrolled 3939 individuals 21–74 years old with age-specific eGFR eligibility criteria of 20–70 ml/min per 1.73 m2 between June of 2003 and December of 2008 from seven United States centers with 13 clinical sites and Institutional Review Board approval at each site. Study design details were previously published (9,10) (ClinicalTrials.gov Identifier: NCT00304148). Briefly, the CRIC Study participants provided written consent for data collected at annual in-center visits, including demographics, medical history, vital signs, blood and urine samples, and other survey-based information. Kidney function was estimated using the abbreviated Modification of Diet in Renal Disease equation for eGFR, the prevailing clinical measure of kidney function at study commencement. The analysis included a question asking how much pain interfered with work in the prior 4 weeks and the broader SF12 Physical Health Composite Score (SF12-PCS), both derived from the Kidney Disease Quality of Life (KDQOL) assessment; the pain question was included in the composite score.
Medication Ascertainment
Study coordinators recorded the CRIC Study participants’ prescription and over-the-counter medications, herbal and dietary supplements, and vitamins for the 30 days preceding the study visit. To reduce recall bias, participants were asked to maintain a medication list or bring medications to visits. The drug name, frequency, total daily dosage, dosage units, and administration route were documented. Individual medications were identified using the First Databank (11) dictionary for common medications and supplements available on the market.
Classification of NSAIDs and Other Analgesics
The CRIC Study data file was closed on December 8, 2011 for this analysis. The NSAID classification included all NSAIDs and cyclooxygenase-2 inhibitors. Additional drug categories were created for opioids, including tramadol, and nonopioid analgesics. Aspirin was classified as a nonopioid analgesic if total daily dosage was >325 mg, frequency was more than once a day, or the drug was part of a combination analgesic. Combination medications were separated into individual constituents, with each individually classified.
Visit-Pairings
For trends in NSAID use, visits were assembled into rolling consecutive pairs to determine changes in use patterns and examine whether factors identified at the antecedent visit were associated with NSAID use at the subsequent visit of each pair and how a change or continuation of NSAIDs affected other analgesic use. The visit-pairs were categorized into four groups: (1) no NSAIDs (stay off), (2) switching from no NSAIDs to NSAID use (start), (3) switching from NSAID use to nonuse (stop), and (4) persistent NSAID use ( stay on).
Definition of a Drug-Related Problem
We considered analgesic use as either appropriate or a drug-related problem (DRP) defined as follows (12). All NSAID use was classified as a DRP. The use of other nonopioid and opioid analgesics was classified as a DRP if excessively dosed or inappropriately given for the participant’s eGFR. We used dosing guidance from multiple medication guideline references, including Lexi-Comp online; the Directory of Drug Dosage in Kidney Disease; Micromedex; the article “Drug prescribing in renal failure: Dosing guidelines for adults”; and the American Hospital Formulary Service (13–18). The most commonly used recommendation was selected as the dosing guidance. DRP flags were generated for the subsequent visit using the eGFR from the antecedent visit, because this eGFR was available at the time of a provider’s prescription at a subsequent visit.
Statistical Methods
For descriptive analyses, chi-squared tests and t tests compared discrete characteristics and continuous variables, respectively, across groups. Generalized estimating equations (GEEs) compared the odds of starting or stopping NSAIDs across visit-pairs. A logistic transition model was used to assess if factors at the antecedent visit were associated with change in NSAID use at the subsequent visit, conditional on NSAID use at the antecedent visit (19). The factors included eGFR, urine protein, seeing a nephrologist, and pain interfering with work. The logistic transition models were of first-order binary Markov chain type, with two transition probabilities, π01 and π10, of starting NSAIDs and stopping NSAIDs at the subsequent visit, respectively. The models included interaction terms between covariates and NSAID use at the antecedent visit to distinguish their associations with the two different transition probabilities. Demographic (age, sex, and race) and case mix factors, including body mass index, diabetes, cardiovascular disease, hypertension, arthritis, and years from baseline visit to current visit, were included as confounders in multivariate models. All except sex and race were updated at each antecedent visit for analysis. A robust variance estimator accounted for potential correlations in NSAID use by individuals at different visits.
To determine whether change in NSAID use across a visit-pair was associated other analgesic use, we used a binary outcome (whether there was an increase in the total number of non-NSAID analgesics) in a GEE regression with binomial distribution and a logit link function. In addition to NSAID use at both antecedent and subsequent visits, only those covariates significantly associated with the outcome were included in the final model. The same approach was used for examining the association of the switch in NSAID use with the change in the number of opioid analgesics and pain as measured with the KDQOL at subsequent visits. GEE regressions with a normal distribution and an identity link were used for change in eGFR and the broader KDQOL SF12-PCS at subsequent visits. Adjusted odds ratios (ORs) and their 95% confidence intervals (95% CIs) were computed. Analyses were performed using SAS 9.3 (SAS Institute Inc., Cary, NC).
Results
Of 3939 CRIC Study participants with a baseline visit, 67 were excluded due to lack of baseline medication information. The remaining 3872 subjects underwent 19,789 predialysis visits with 15,917 visit-pairs. The majority of the visit-pairs (97%) were consecutive annual visits, but 2% and 0.7% of the pairs had one or two or more missing visits between paired visits, respectively. Nine hundred forty (24%) participants reported NSAID use at one or more visits and 2170 (11%) visits overall, with 487 (13%) reporting NSAID use at the baseline visit and 453 initiating NSAID use at a later visit.
Table 1 shows the baseline characteristics of the CRIC Study participants on the basis of whether they ever reported NSAID use. Being older than 65 years old or having advanced CKD stages, urine protein >0.5 g/d, diabetes, cardiovascular disease, hypertension, or report of seeing a nephrologist were associated with a lower chance of ever reporting NSAID use. Being a woman, having arthritis, and having pain interfering with work moderately or greater were associated with ever reporting NSAID use.
Baseline characteristics of the Chronic Renal Insufficiency Cohort Study participants on the basis of whether they ever reported nonsteroidal anti-inflammatory drug use at a study visit (n=3872)
Pattern of Change in NSAID Use
Among the 487 participants reporting baseline NSAID use, 25 had a baseline visit only, 233 did not report NSAID use at the first follow-up visit, and an additional 162 stopped reporting NSAID use at a later visit.
Figure 1 shows the distribution of subsequent visits from a pair on the basis of NSAID use pattern over 8 study years. The proportion of participants starting NSAIDs was between 4% and 6%, whereas the proportion of participants staying on an NSAID from the prior visit was between 5% and 7%. The proportion of participants who either started or stayed on an NSAID was relatively stable. The proportion of participants stopping NSAIDs was the highest at the first annual visit (7%) and between 5% and 6% at the second to seventh visits before dropping to 2% at the eighth visit (P<0.001 for comparing the proportions of stopping NSAIDs among visits).
The distribution of nonsteroidal anti-inflammatory drug switch patterns at each follow-up annual visit indicates the proportion of participants starting or staying on NSAID was relatively stable.
Association of Antecedent Visit Characteristics with Switch in NSAID Use at Subsequent Visit
Table 2 displays the associations of the antecedent visit factors (eGFR, urine protein excretion, nephrologist contact, and pain) with change (starting or stopping) in NSAID use at the subsequent visit in a pair. Higher eGFR level at the antecedent visit was associated with higher odds of starting NSAIDs, but eGFR at an antecedent visit was not associated with stopping NSAIDs. Report of nephrologist contact at the antecedent visit was associated with lower odds of starting NSAIDs and higher odds of stopping NSAIDs. Proteinuria was not a significant factor associated with reported NSAIDs. Pain interfering moderately or greater with work was associated with higher odds of starting an NSAID.
Adjusted odds ratio of nonsteroidal anti-inflammatory drug start (or stay on) with eGFR, proteinuria, and nephrology visit (visit-pair n=15,917)
Association of Switch in NSAID Use with Other Analgesic Use
Table 3 shows how change in reported usage of NSAID was associated with changes in use of other analgesics. Compared with visit-pairs with no NSAID use, starting NSAIDs was associated with higher odds of increasing the number of all non-NSAIDs and opioid analgesic use specifically (adjusted OR, 1.52; 95% CI, 1.25 to 1.85 and OR, 1.92; 95% CI, 1.48 to 2.48, respectively; both P<0.001). Similarly, compared with visit-pairs where participants stayed on NSAIDs, stopping NSAIDs was associated with a higher odds of increasing the number of both all non-NSAID analgesics used and opioid analgesics used specifically (adjusted OR, 1.78; 95% CI, 1.39 to 2.28 and OR, 1.46; 95% CI, 1.04 to 2.03; P=0.001 and P=0.03, respectively).
Associations of nonsteroidal anti-inflammatory drug switch with change in other analgesic and opioid use (n=15,917)
Table 4 displays the most common NSAIDs, opioid and nonopioid analgesics by participant-visit, and proportion of visits where each analgesic was reported with DRPs. Ibuprofen was the most frequently reported NSAID, and hydrocodone was the most frequently reported opioid medication, with only a minority of visits with hydrocodone dosed high enough to classify the drug as a DRP. Several opioids were reported less commonly but with a higher proportion of visits where doses were high enough to classify as DRPs. These included methadone, propoxyphene, and fentanyl, with at least one quarter of visits where the opioid use was classified as a DRP. Acetaminophen was the most frequently used nonopioid analgesic (27% of visits), but the proportion of acetaminophen entries with a DRP was very low (0.3%). Aspirin, the second most common nonopioid, was only used in 3% of the visits at a dose high enough to classify as an analgesic, but 15% of the entries were classified as a DRP. The remaining nonopioid analgesics all had variable proportions of entries with a DRP but with low total use.
Top nonsteroidal anti-inflammatory drugs, opioid analgesic medications, and nonopioid analgesic medications by frequency of visits with a report of medication and proportion of those visits with a drug-related problem
Intervisit Changes on the Basis of NSAID Use Patterns
Kidney function did not change significantly between paired visits in any of the usage groups (Supplemental Table 1), even with adjustment for kidney function at antecedent visit and other factors. Compared with visit-pairs with no NSAID use, starting NSAIDs was associated with higher odds of pain interfering moderately or greater with work and a lower SF12-PCS at the subsequent visit (Supplemental Table 2, A and B, respectively). Participants who stayed on NSAIDs also had a higher odds of such pain and a lower SF12-PCS at the subsequent visit relative to those who stopped an NSAID.
Discussion
In this analysis, we showed that a substantial portion of patients with CKD reported NSAID use over time. Although most CRIC Study participants reporting baseline NSAID use stopped them during follow-up, additional participants initiated NSAIDs at a follow-up visit, resulting in a relatively constant proportion of the cohort reporting NSAID use annually. Better kidney function at an antecedent visit was associated with a greater likelihood of starting NSAIDs at the subsequent visit but not stopping them. Hence, kidney function was more likely to be a factor associated with starting NSAIDs versus whether they were continued. Seeing a nephrologist at the antecedent visit was associated with either ceasing or avoiding an NSAID, which indicates that nephrologists tend to acknowledge the risks of NSAID in CKD. Pain interfering with work was associated with higher odds of starting an NSAID, confirming that NSAID use is an underpinning to pain management. Participants either starting or stopping NSAID use were more likely to increase non-NSAID analgesic use, including opioids, versus those remaining NSAID free or with sustained NSAID use, highlighting non-NSAID analgesics’ role as supplements or alternatives for CKD pain management. Participants reported a notable portion of these additional analgesics, especially opioids, at excessive doses for their kidney function.
Other reports recognized the increasing use of analgesics, particularly opioids, in the general and ESRD populations (20–22). Our data extend these findings by showing a linkage between NSAID and opioid use in nondialysis-dependent CKD, with a significant proportion of analgesics inappropriately dosed for kidney function at the time of drug use (23). The comingling of NSAIDs and other analgesics, particularly opioid use, in CKD puts focus on a previously under-recognized safety concern in this disease population.
The estimated prevalence of NSAID use in the CRIC Study participants was consistent with several prior reports of 9%–36% of patients with CKD using NSAIDs (5,6,8,24–26). One study from the National Health and Nutrition Examination Survey suggested that the frequency of NSAID use was slightly higher in United States adults with moderate to severe versus mild CKD (27), a reverse trend to that reported here. Differences in sampling methods to identify patients with CKD and determine NSAID use may account for the differences. Previous studies also provide some evidence on the association of NSAIDs and other analgesics with decline of kidney function (4,28,29), supporting the likelihood of harm with use of these agents. However, higher cumulative doses of NSAIDs may be required to increase the risk of accelerated CKD progression (30).
Few studies have looked at longitudinal changes in NSAID use in CKD. Wei et al. (6) showed that patients with CKD in Scotland who stopped NSAIDs had significant improvement in kidney function up to 180 days after cessation, but long-term kidney function effects were not reported. In another study, approximately 20% of patients on dialysis have been reported to use NSAIDs consistently for an average of 40 days over each of 3 years before initiating kidney replacement therapy (31).
This study is unique in reporting on the frequency and trends in NSAID use over time, examining factors associated with change in NSAID use, and describing the relationship between changes in NSAID use and non-NSAID analgesic use in CKD. The observed association between either cessation or initiation of NSAIDs and greater opioid use is significant given the problem of growing dependency on the latter class of agents among some patients (32).
One possible explanation for frequent use of NSAIDs and other analgesics among patients with CKD is the preponderance of chronic pain in this population (25). About 61% of patients with CKD in a recent study reported chronic pain (33). Approximately 13% of the CRIC Study participants had arthritis at baseline, and more than one third had pain interfering moderately or greater with work; hence, they may have required multiple analgesics to manage their pain. Ill-advised use of NSAIDs may be exacerbated by low recognition of CKD (34), although the awareness of CKD might be higher in the CRIC Study than in patients with CKD who are not study participants. The observed higher use of non-NSAID analgesics both with persistent NSAID use and as a substitute for NSAIDs may reflect countervailing provider tactics, with intensification of analgesics in patients having difficulty managing pain and efforts to identify alternatives to NSAID use in patients for whom these agents are identified as ill advised.
As with all retrospective studies, this analysis has limitations to consider when interpreting the findings. Recording of NSAID and other analgesic use was on the basis of self-report and hence, subject to recall bias. However, only medication use in the 30 days before visits was recorded, and participants were asked to maintain a list of medications or bring them to visits as a means of optimizing recall. Although we did not validate the approach of collecting self-reported medication use, in a study comparing self-reported analgesic use with detection of urinary ibuprofen and acetaminophen metabolites, the overall rate of concordance was 81%–84% (35). Although herbal medications and other supplements were recorded as part of the CRIC Study medication assessment, reliable determination of the quantity of constituents, which might be categorized as NSAIDs like (e.g., cyclooxygenase-2 inhibitory activity), was not feasible. The 30-day reporting period also limited the assessment of cumulative exposure between visits; however, our use of transition models to examine visit-pairs takes advantage of this study structure to assess factors associated with changes in analgesic use. As an observational study, confounding by either measured or unmeasured factors is possible. In addition, some participants missed several annual visits before returning for follow-up, and the NSAID use status at missed visits was assumed unchanged from the last annual visit. As reported, only a small proportion of visit-pairs was spaced more than a year apart. Finally, the CRIC Study annual visits did not include pain assessment beyond that included in the SF12-PCS or motivations for NSAID switch, which could illuminate the identified trends or patterns in NSAID and other analgesic usage. However, we used pain affecting work, which was ascertained from the KDQOL, as a proxy for general pain and identified a positive association of this report of pain with NSAID switch patterns. In addition, the identification of persistent analgesic users, including those individuals with intensification of other analgesic usage, can offer some valuable insight into the proportion of patients with CKD and chronic pain and their needs. In conclusion, our study showed that higher levels of kidney function were associated with a greater likelihood of starting NSAIDs, whereas contact with a nephrologist lowered the likelihood of either starting NSAIDs or staying on NSAIDs. Both initiating and stopping an NSAID were linked to increased use of other analgesics, most notably opioids. Starting and staying on NSAIDs were also associated with worse pain and physical health. The safety consequences of interchanging or supplementing NSAIDs with non-NSAID analgesics, especially opioid toxicity and dependency, need to be explored further in CKD. Future studies will need to examine the association of NSAID use with long-term CKD progression in conjunction with the unintended consequences or tradeoffs related to concomitant or alternative use of non-NSAID analgesics.
Disclosures
None.
Acknowledgments
M.Z., R.M.D., and J.C.F. were supported by National Institutes of Health (NIH)/National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) grant R01 DK090008. J.B.B. was supported by the Geriatric Research, Education and Clinical Center at the Baltimore Veterans Affairs Medical Center. Funding for the Chronic Renal Insufficiency Cohort (CRIC) Study was obtained under a cooperative agreement from the NIDDK (grants U01DK060990, U01DK060984, U01DK061022, U01DK061021, U01DK061028, U01DK060980, U01DK060963, and U01DK060902). In addition, this work was supported, in part, by Perelman School of Medicine at the University of Pennsylvania Clinical and Translational Science Award NIH/National Center for Advancing Translational Sciences (NCATS) grant UL1TR000003, Johns Hopkins University grant UL1 TR-000424, University of Maryland General Clinical Research Center grant M01 RR-16500, the Clinical and Translational Science Collaborative of Cleveland, grant UL1TR000439 from the NCATS component of the NIH and the NIH Roadmap for Medical Research, Michigan Institute for Clinical and Health Research grant V 2014.07.28 UL1TR000433, University of Illinois at Chicago Center for Clinical and Translational Science grant UL1RR029879, Tulane University Translational Research in Hypertension and Renal Biology grant P30GM103337, and Kaiser Permanente NIH/National Center for Research Resources University of California, San Francisco–Clinical and Translational Science Institute grant UL1 RR-024131.
The CRIC Study Investigators are Lawrence J. Appel (The Johns Hopkins University), Harold I. Feldman (University of Pennsylvania), Alan S. Go (Kaiser Permanente of Northern California), Jiang He (Tulane University), John W. Kusek (National Institute of Diabetes, and Digestive, and Kidney Diseases), Mahboob Rahman (Case Western Reserve University School of Medicine), Panduranga Rao (University of Michigan), and Raymond R. Townsend (University of Pennsylvania).
Footnotes
Published online ahead of print. Publication date available at www.cjasn.org.
This article contains supplemental material online at http://cjasn.asnjournals.org/lookup/suppl/doi:10.2215/CJN.12311216/-/DCSupplemental.
- Received December 1, 2016.
- Accepted July 7, 2017.
- Copyright © 2017 by the American Society of Nephrology
References
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