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Association of Opioids and Nonsteroidal Anti-inflammatory Drugs With Outcomes in CKD: Findings From the CRIC (Chronic Renal Insufficiency Cohort) Study

Open AccessPublished:April 18, 2020DOI:https://doi.org/10.1053/j.ajkd.2019.12.010

      Rationale & Objective

      Safe analgesic choices are limited in chronic kidney disease (CKD). We conducted a comparative analysis of harm from opioids versus nonsteroidal anti-inflammatory drugs (NSAIDs) in CKD.

      Study Design

      Prospective cohort study.

      Setting & Participants

      3,939 patients with CKD in the Chronic Renal Insufficiency Cohort (CRIC) Study.

      Exposures

      30-day analgesic use reported at annual visits.

      Outcomes

      A composite outcome of 50% glomerular filtration rate reduction and kidney failure requiring kidney replacement therapy (KRT), as well as the outcomes of kidney failure requiring KRT, hospitalization, and pre–kidney failure death.

      Analytical Approach

      Marginal structural models with time-updated exposures.

      Results

      Participants were followed up for a median of 6.84 years, with 391 (9.9%) and 612 (15.5%) reporting baseline opioid and NSAID use, respectively. Time-updated opioid use was associated with the kidney disease composite outcome, kidney failure with KRT, death (HRs of 1.4 [95% CI, 1.2-1.7], 1.4 [95% CI, 1.1-1.7], and 1.5 [95% CI, 1.2-2.0], respectively), and hospitalization (rate ratio [RR], 1.7; 95% CI, 1.6-1.9) versus opioid nonusers. Similar results were found in an analysis restricted to a subcohort of participants reporting ever using other (nonopioid and non-NSAID) analgesics or tramadol. Time-updated NSAID use was associated with increased risk for the kidney disease composite (HR, 1.2; 95% CI, 1.0-1.5) and hospitalization (RR, 1.1; 95% CI, 1.0-1.3); however, these associations were not significant in the subcohort. The association of NSAID use with the kidney disease composite outcome varied by race, with a significant risk in blacks (HR, 1.3; 95% CI, 1.0-1.7). NSAID use was associated with lower risk for kidney failure with KRT in women and individuals with glomerular filtration rate < 45 mL/min/1.73 m2 (HRs of 0.63 [95% CI, 0.45-0.88] and 0.77 [95% CI, 0.59-0.99], respectively).

      Limitations

      Limited periods of recall of analgesic use and potential confounding by indication.

      Conclusions

      Opioid use had a stronger association with adverse events than NSAIDs, with the latter’s association with kidney disease outcomes limited to specific subgroups, notably those of black race.

      Index Words

      Pain is common among patients with all stages of chronic kidney disease (CKD), but safe treatment options are not well defined.
      • Pham P.C.
      • Dewar K.
      • Hashmi S.
      • et al.
      Pain prevalence in patients with chronic kidney disease.
      ,
      • Wu J.
      • Ginsberg J.S.
      • Zhan M.
      • et al.
      Chronic pain and analgesic use in CKD: implications for patient safety.
      Much literature describes the ill effects of nonsteroidal anti-inflammatory drugs (NSAIDs) on the kidney.
      • Clive D.M.
      • Stoff J.S.
      Renal syndromes associated with nonsteroidal antiinflammatory drugs.
      ,
      • Murray M.D.
      • Brater D.C.
      Adverse effects of nonsteroidal anti-inflammatory drugs on renal function.
      Nevertheless, the National Kidney Foundation endorses limited NSAID use for the management of occasional pain in CKD, but advises against long-term use.
      National Kidney Foundation
      Pain medicine and your kidneys.
      Other disease-specific guidelines exclude NSAIDs from chronic pain treatment algorithms.
      • Koncicki H.M.
      • Unruh M.
      • Schell J.O.
      Pain management in CKD: a guide for nephrology providers.
      However, recent studies demonstrate the renal safety of NSAIDs in some chronic diseases, adding to the controversy regarding their use in CKD.
      • Hiremath S.
      • Goldfarb D.S.
      • Juurlink D.N.
      Opioid overuse or NSAID underuse? A response to the pain guide.
      ,
      • Moller B.
      • Pruijm M.
      • Adler S.
      • Scherer A.
      • Villiger P.M.
      • Finckh A.
      Chronic NSAID use and long-term decline of renal function in a prospective rheumatoid arthritis cohort study.
      As a result, recommendations for NSAID avoidance have been challenged, even in stages 3 to 5 CKD.
      • Hiremath S.
      • Goldfarb D.S.
      • Juurlink D.N.
      Opioid overuse or NSAID underuse? A response to the pain guide.
      Coincident with the concern for NSAID use in CKD is acknowledgment of the opioid epidemic and recommendations to avoid long-term opioid use. In 2013, American health care providers wrote approximately 250 million opioid prescriptions,
      Substance Abuse and Mental Health Services Administration
      2014 National Survey on Drug Use and Health: detailed tables.
      and in 2014, almost 2 million persons either misused opioids or experienced an opioid use disorder.
      • Dowell D.
      • Haegerich T.M.
      • Chou R.
      CDC guideline for prescribing opioids for chronic pain--United States, 2016.
      About 1 in 4 people prescribed long-term opioid use for noncancer pain struggle with an opioid use disorder.
      • Boscarino J.A.
      • Rukstalis M.
      • Hoffman S.N.
      • et al.
      Risk factors for drug dependence among out-patients on opioid therapy in a large US health-care system.
      More than 183,000 adults died from opioid overdose between 1999 and 2015.
      • Dowell D.
      • Haegerich T.M.
      • Chou R.
      CDC guideline for prescribing opioids for chronic pain--United States, 2016.
      Government and health agencies have established pain management guidelines intent on directing prescribers toward more judicious opioid use. Notable examples include the World Health Organization 3-step analgesic ladder for cancer-related pain
      World Health Organization
      WHO's cancer pain ladder for adults.
      and the Centers for Disease Control and Prevention (CDC) guideline for prescribing opioids for chronic pain.
      • Dowell D.
      • Haegerich T.M.
      • Chou R.
      CDC guideline for prescribing opioids for chronic pain--United States, 2016.
      The CDC guideline for chronic pain management recommends nonpharmacologic and nonopioid therapies including acetaminophen, select antidepressants, anticonvulsants, and NSAIDs before long-term opioid use.
      • Dowell D.
      • Haegerich T.M.
      • Chou R.
      CDC guideline for prescribing opioids for chronic pain--United States, 2016.
      Prior work from the Chronic Renal Insufficiency Cohort (CRIC) Study revealed that 24% of study participants reported NSAID use at study entry or at least 1 follow-up visit.
      • Zhan M.
      • St Peter W.L.
      • Doerfler R.M.
      • et al.
      Patterns of NSAIDs use and their association with other analgesic use in CKD.
      In addition, initiation or discontinuation of NSAID treatment is often associated with supplementation or replacement, respectively, with opioids.
      • Zhan M.
      • St Peter W.L.
      • Doerfler R.M.
      • et al.
      Patterns of NSAIDs use and their association with other analgesic use in CKD.
      Hence these analgesic classes are both likely to be used and interchanged in CKD; however, comparative outcomes of using drugs from these analgesic classes are not known. In this analysis of the CRIC Study, our objective is to evaluate the association of opioid and NSAID use with clinical outcomes in patients with CKD not requiring kidney replacement therapy (KRT).

      Methods

       Study Design and Participants

      The CRIC Study commenced in 2003, with phase 1 and 2 enrollment completed in 2006, and continued follow-up to date with the design previously described.
      • Feldman H.I.
      • Appel L.J.
      • Chertow G.M.
      • et al.
      The Chronic Renal Insufficiency Cohort (CRIC) Study: design and methods.
      This analysis examined 3,939 participants who gave informed consent and were enrolled at 21 to 74 years of age with age-specific estimated glomerular filtration rate (eGFR) eligibility criteria of 20 to 70 mL/min/1.73 m2 from 7 US centers with 13 clinical sites and institutional review board approval at each site. Briefly, CRIC participants underwent annual in-center visits providing demographic information, medical history and status update, vital signs, blood and urine samples, and other survey-based information. GFR was estimated using the 4-variable Modification of Diet in Renal Disease (MDRD) Study equation, the prevailing clinical measure of kidney function at study commencement.
      • Levey A.S.
      • Greene T.
      • Kusek J.W.
      • Beck G.J.
      A simplified equation to predict glomerular filtration rate from serum creatinine [abstract].

       Medication Ascertainment

      Coordinators recorded participants’ prescription and over-the-counter medications, supplements, and vitamins from 30 days preceding the study visit. To reduce recall bias, participants were asked to maintain a list or bring medications to visits. The drug name, frequency, total daily dosage, dosage units, and administration route were documented. Individual medications and constituents of combinations were identified using the First Databank dictionary (First Databank, Inc).

       Classification of Analgesics

      The CRIC data file was closed in May 2014 to permit data cleaning and preparation for this analysis. The NSAID category included all oral NSAIDs and cyclooxygenase 2 (COX-2) inhibitors. Aspirin was classified as an NSAID if total daily dosage was >325 mg, dose frequency was more than once daily, or the drug was part of a combination analgesic (excluding aspirin and dipyridamole). Members of the opioid class included all orally administered narcotics as designated in First Databank, such as hydrocodone, codeine, and oxycodone. Methadone represented <0.1% of opioid entries and no buprenorphine/naloxone use was reported. Opioids used as cold or cough remedy were excluded. Members of the “other” (nonopioid non-NSAID) class included predominately acetaminophen. Because tramadol has overlapping but distinct pharmacologic properties from narcotics,
      • Grond S.
      • Sablotzki A.
      Clinical pharmacology of tramadol.
      it was considered as a separate class unless taken in combination with an NSAID or an opioid, in which case the medication was classified in the latter’s category. We defined the time-updated opioid and NSAID use at each clinical visit as whether a patient had reported NSAID or opioid use at that visit or any one of the previous CRIC visits. The class of other (nonopioid non-NSAID) analgesics included all other oral analgesics heretofore not classified. Of note, >90% of those entries were acetaminophen alone or in combination with another agent (eg, diphenhydramine). No intravenous or topical analgesics were included in the analysis.

       Outcomes

      We examined 4 clinical outcomes, including kidney failure requiring KRT, the composite of kidney failure with KRT and 50% reduction in eGFR from baseline, pre–kidney failure death, and number of pre–kidney failure hospitalizations between 2 consecutive annual visits. GFR was estimated annually.
      • Levey A.S.
      • Greene T.
      • Kusek J.W.
      • Beck G.J.
      A simplified equation to predict glomerular filtration rate from serum creatinine [abstract].
      Death was ascertained through report from next of kin, retrieval of death certificates or obituaries, review of hospital records, and linkage with the Social Security Mortality Master File.
      • Deo R.
      • Shou H.
      • Soliman E.Z.
      • et al.
      Electrocardiographic measures and prediction of cardiovascular and noncardiovascular death in CKD.
      Kidney failure with KRT was ascertained by CRIC Study personnel and cross-reference to the US Renal Data System.
      • Yang W.
      • Xie D.
      • Anderson A.H.
      • et al.
      Association of kidney disease outcomes with risk factors for CKD: findings from the Chronic Renal Insufficiency Cohort (CRIC) study.
      For kidney failure with KRT and the composite kidney disease outcome, participant follow-up was censored at the time of death, withdrawal, loss to follow-up, or end of the follow-up period, whichever occurred first. For pre–kidney failure death and number of hospitalizations, participant follow-up was censored at the time of KRT initiation, withdrawal, loss to follow-up, or end of the follow-up period, whichever occurred first.

       Covariates

      We considered several clinically relevant covariates including baseline factors: sex, race, education level, and income reported at study entry. Time-dependent covariates included age, any alcohol drinking, comorbid conditions (diabetes, cardiovascular disease, hypertension, asthma, nonskin cancer, hyperkalemia, and arthritis), GFR, urinary protein-creatinine ratio (UPCR), response on the Beck Depression Inventory, symptom severity, and Kidney Disease Quality of Life 36 questionnaire (KDQOL-36) burden and symptoms subscales, 12-Item Short Form Health Survey (SF-12) physical composite (including a question asking how much pain impeded activities of daily living), SF-12 mental composite, nephrologist visits, and other analgesic use (nonopioid/non-NSAID analgesic and tramadol) collected at annual visits. Urinary protein and creatinine excretion were also measured using standard assays. UPCRs from 24-hour and spot urine specimens were combined to a single UPCR variable.

       Statistical Methods

      For descriptive analyses, χ2 tests and t tests compared discrete characteristics and continuous variables, respectively, across groups. We examined the association between time-updated opioid and NSAID use and the study outcomes while controlling for time-dependent covariates. We applied joint marginal structural models because several time-dependent covariates including eGFR could be both a consequence and a predictor for analgesic use. The challenges of making causal inferences from observational data have been previously discussed and illustrated with steps of fitting joint marginal structural models described.
      • Howe C.J.
      • Cole S.R.
      • Mehta S.H.
      • Kirk G.D.
      Estimating the effects of multiple time-varying exposures using joint marginal structural models: alcohol consumption, injection drug use, and HIV acquisition.
      In brief, we used a pooled logistic regression model to predict the probability of time-updated NSAID use at each visit based on NSAID use and opioid use at the previous visit and covariates at the previous visit. Another pooled logistic regression model was applied to predict the probability of time-updated opioid use at each visit based on NSAID use at both the current and previous visits, opioid use at the previous visit, and covariates at the previous visit. Inverse probability weights were computed and stabilized. To control for informative censoring, the inverse probability of censoring weight was also computed and stabilized. The final weight was the product of the NSAID and opioid exposure and the censoring weight. The final weight was also truncated at the 99th percentile. Finally, we fit a weighted discrete failure time model for each of the survival outcomes through generalized estimating equations and using the final weight developed from the logistic regression models. Only baseline covariates were included in the discrete failure time models. For hospitalizations, we fit a weighted Poisson regression model using generalized estimating equation and the final weight.
      We performed the analyses using the full cohort and a subcohort including participants who ever used another (nonopioid non-NSAID) analgesic or tramadol at baseline or during follow-up as a surrogate for need of pain relief. We also performed stratified analyses using demographic variables and key predictors of kidney outcomes: baseline age (<65 and ≥65 years), sex, race (nonblack and black), diabetes status, eGFR (≤45 vs >45 mL/min/1.73 m2), and UPCR dichotomized at the sample median.
      To demonstrate that our results were robust and not due to unmeasured confounding, we examined the association of opioids and NSAIDs with risk for incident diabetes as a negative control outcome among CRIC participants without diabetes at enrollment and using the joint marginal structural models as described.
      All analyses were performed using SAS, version 9.4 (SAS Institute Inc).

      Results

      The 3,939 participants had a median follow-up of 6.84 years. There was a total of 24,838 visits for time to kidney failure with KRT or pre–kidney failure death, and 24,552 visits for the composite outcome of kidney failure with KRT and 50% reduction in eGFR. Tables 1 and 2 show the overall baseline characteristics of CRIC participants grouped by reported baseline opioid and NSAID use. Comparing the 391 (9.9%) participants who reported baseline opioid use with the 3,548 (90.1%) who did not, the former group was more likely to be female; be black; have an annual income of ≤$50,000; and have a history of rheumatoid arthritis, cardiovascular disease, asthma, and nonskin cancer and were less likely to report alcohol drinking. Compared with the 3,327 (84.5%) participants who did not report baseline NSAID use, the 612 (15.5%) who did were more likely to be aged 45 to 64 years, female, nonblack, a college graduate or with higher education, and with an income >$50,000, and report drinking alcohol. Those reporting baseline NSAID use also were more likely to have a history of asthma, have higher eGFRs, and less likely to have diabetes, cardiovascular disease, hypertension, previous hyperkalemia, and/or prior visit with a nephrologist. Opioid users were more likely to have depressive symptoms than nonusers and lower scores for the KDQOL-36 and its components domains (Table 2). However, NSAID users had higher KDQOL-36 scores compared with nonusers.
      Table 1Baseline Characteristics of CRIC Participants Overall and by Opioid and NSAID Use
      Opioid Use at BaselinePNSAID Use at BaselineP
      No (n = 3,548)Yes (n = 391)No (n = 3,327)Yes (n = 612)
      Age, y0.30.003
       21-<45494 (13.9%)44 (11.3%)462 (13.9%)76 (12.4%)
       45-<652,025 (57.1%)236 (60.4%)1,872 (56.3%)389 (63.6%)
       ≥651,029 (29.0%)111 (28.4%)993 (29.8%)147 (24.0%)
      Male sex2,004 (56.5%)157 (40.2%)<0.0011,908 (57.3%)253 (41.3%)<0.001
      Black race1,472 (41.5%)186 (47.6%)0.021,432 (43.0%)226 (36.9%)0.005
      Diabetes1,720 (48.5%)188 (48.1%)0.91,668 (50.1%)240 (39.2%)<0.001
      Hypertension3,062 (86.3%)329 (84.1%)0.22,892 (86.9%)499 (81.5%)<0.001
      Any cardiovascular disease1,159 (32.7%)157 (40.2%)0.0031,156 (34.7%)160 (26.1%)<0.001
      Rheumatoid arthritis
      There were 197 missing.
      411 (12.2%)81 (22.3%)<0.001404 (12.8%)88 (15.1%)0.1
      Asthma
      There were 69 missing.
      419 (12.0%)79 (20.5%)<0.001401 (12.3%)97 (16.1%)0.01
      Cancer (excluding nonmelanoma skin cancer)168 (4.7%)28 (7.2%)0.04167 (5.0%)29 (4.7%)0.8
      Drinking alcohol743 (20.9%)50 (12.8%)<0.001649 (19.5%)144 (23.5%)0.02
      Prior visit with nephrologist2,328 (65.6%)273 (69.8%)0.12,295 (69.0%)306 (50.0%)<0.001
      Education
      There was 1 missing.
      0.06<0.001
       <High school752 (21.2%)76 (19.4%)739 (22.2%)89 (14.6%)
       High school graduate660 (18.6%)81 (20.7%)631 (19.0%)110 (18.0%)
       Some college1,015 (28.6%)131 (33.5%)955 (28.7%)191 (31.3%)
       ≥College graduate1,120 (31.6%)103 (26.3%)1,002 (30.1%)221 (36.2%)
      Income0.0060.001
       ≤$20,0001,102 (31.1%)138 (35.3%)1,082 (32.5%)158 (25.8%)
       $20,001-$50,000847 (23.9%)111 (28.4%)809 (24.3%)149 (24.3%)
       $50,001-$100,000673 (19.0%)61 (15.6%)603 (18.1%)131 (21.4%)
       >$100,000369 (10.4%)23 (5.9%)311 (9.3%)81 (13.2%)
       Do not wish to answer557 (15.7%)58 (14.8%)522 (15.7%)93 (15.2%)
      Nonopioid/non-NSAID analgesic use560 (15.8%)114 (29.2%)<0.001532 (16.0%)142 (23.2%)<0.001
      Tramadol use72 (2.0%)18 (4.6%)0.00173 (2.2%)17 (2.8%)0.4
      Anxiolytic use
      There were 28 missing.
      107 (3.0%)38 (9.7%)<0.001109 (3.3%)36 (5.9%)0.002
      Antiepileptic use
      There were 28 missing.
      289 (8.2%)95 (24.3%)<0.001315 (9.5%)69 (11.3%)0.2
      Note: N = 3,939. Values given as count (percent). Missing values not included in the denominators for computing percents.
      Abbreviations: CRIC, Chronic Renal Insufficiency Cohort; NSAID, nonsteroidal anti-inflammatory drug.
      a There were 197 missing.
      b There were 69 missing.
      c There was 1 missing.
      d There were 28 missing.
      e There were 28 missing.
      Table 2Baseline Characteristics by Opioid and NSAID Use
      All ParticipantsOpioid UseNSAID Use
      NoYesNoYes
      NMean ± SDNMean ± SDNMean ± SDNMean ± SDNMean ± SD
      eGFR, mL/min/1.73 m23,93943 ± 133,54843 ± 1439143 ± 143,32742 ± 1361248 ± 13
      UPCR, μg/mg3,7721 ± 23,3971 ± 2.43750.7 ± 23,1851 ± 25870.6 ± 2
      Beck score3,8898 ± 83,5068 ± 838311 ± 93,2888 ± 86018 ± 8
      Symptom severity score3,919151 ± 1773,531144 ± 173388220 ± 1993,307150 ± 176612159 ± 184
      KDQOL Burden of Kidney Disease3,91382 ± 243,52783 ± 2338678 ± 263,30681 ± 2460787 ± 22
      KDQOL Symptoms3,92183 ± 153,53484 ± 1438777 ± 173,31284 ± 1560983 ± 14
      SF-12 physical composite3,84741 ± 123,46442 ± 1138333 ± 103,24541 ± 1260241 ± 12
      SF-12 mental composite3,84750 ± 113,46451 ± 1038347 ± 113,24550 ± 1160250 ± 11
      Note: N = 3,939.
      Abbreviations: eGFR, estimated glomerular filtration rate; KDQOL, Kidney Disease Quality of Life; NSAID, nonsteroidal anti-inflammatory drug; SD, standard deviation; SF-12, 12-Item Short Form Health Survey; UPCR, urinary protein-creatinine ratio.
      Table 3 displays crude rates of outcomes in the year following observed visits classified by opioid and NSAID use alone, in combination, or use of neither class of analgesic. The crude incidence of death was highest in the opioid-only group and opioid and NSAID group, with crude rates (per 100 person-years) of 3.5 (95% confidence interval [CI], 2.8-4.3) and 3.5 (95% CI, 2.2-5.5), respectively. The crude incidence of kidney failure with KRT in the opioid and other (nonopioid non-NSAID) groups were 4.2 (95% CI, 3.4-5.2) and 4.3 (95% CI, 4.0-4.6) per 100 person-years, respectively, appearing to be higher than the crude rates in the NSAID-only group (1.9 [95% CI, 1.4-2.5] per 100 person-years) and the opioid and NSAID group (2.5 [95% CI, 0.1-1.5] per 100 person-years). A similar pattern was observed for the composite kidney disease outcome, with crude rates in the opioid and other analgesic groups of 5.9 (95% CI, 5.3-6.3) and 5.9 (95% CI, 5.5-6.3) per 100 person-years, respectively. For hospitalizations, the opioid-only group had the highest crude rate of hospitalizations, while the NSAID-only group had the lowest crude rate (108.6 [95% CI, 99.1-118.9] vs 58.0 [95% CI, 51.5-65.3] per 100 person-years).
      Table 3Crude Rate of Events (per 100 person-years) Following Annual Visits Classified by Reported Opioid and NSAID Use
      Analgesic UsePre–Kidney Failure DeathKidney Failure With KRTComposite Kidney Disease OutcomePre–Kidney Failure Hospitalization
      EventsTotal VisitsRate per 100 Visits (95% CI)EventsTotal VisitsRate per 100 Visits (95% CI)EventsTotal VisitsRate per 100 Visits (95% CI)EventsTotal VisitsRate per 100 Visits (95% CI)
      Opioid (no NSAID)852,4203.5 (2.8-4.3)841,9984.2 (3.4,5.2)1141,9425.9 (5.3-6.3)2,1691,998108.6 (99.1-118.9)
      NSAID (no opioid)382,7801.4 (1.0-1.9)462,4651.9 (1.4-2.5)602,4542.4 (1.9-3.2)1,4292,46558.0 (51.5-65.3)
      Other (nonopioid non-NSAID)40219,0972.1 (1.9-2.3)68315,9604.3 (4.0-4.6)93015,7445.9 (5.5-6.3)9,78615,96061.3 (58.6-64.2)
      Opioid & NSAID195413.5 (2.2-5.5)124762.5 (1.4-4.4)114732.3 (1.2-4.2)42647689.5 (75.2-106.6)
      Note: Total number of visits used for pre–kidney failure death is 24,838. Total number of visits for kidney failure with KRT and pre–kidney failure hospitalization is 20,899. Total number of visits for the composite kidney disease outcome is 20,613.
      Abbreviations: CI, confidence interval; KRT, kidney replacement therapy; NSAID, nonsteroidal anti-inflammatory drug.
      Table 4 shows the association of time-updated opioid and NSAID exposure with outcomes in the full cohort with the risk estimates expressed as hazard ratios (HRs) for kidney disease outcomes and as rate ratios (RRs) for hospitalization. Time-updated opioid use was associated with increased adjusted risk for all 4 outcomes relative to never using opioids during CRIC participation, with HRs of 1.4 (95% CI, 1.2-1.7), 1.4 (95% CI, 1.1-1.7), and 1.5 (95% CI, 1.2-2.0) and RR of 1.7 (95% CI, 1.6-1.9) for the kidney disease composite, kidney failure with KRT, death, and hospitalization, respectively. Time-updated NSAID use was associated with a modestly increased hazard of the kidney disease composite and risk for hospitalizations relative to never using NSAID with HR of 1.2 (95% CI, 1.0-1.5) and RR of 1.1 (95% CI, 1.0-1.3). However, there was no significant association between time-updated NSAID use and kidney failure with KRT or death.
      Table 4Associations of Time-Updated Cumulative NSAID and Opioid Exposure With Outcomes, Adjusting for Time-Dependent Covariates in the Full Cohort and a Subcohort Comprising Participants Who Ever Used Other Analgesics or Tramadol During CRIC Study
      OutcomeFull CohortSubcohort
      HR
      HR except for hospitalization, which is a rate ratio.
      (95% CI)
      PHR
      HR except for hospitalization, which is a rate ratio.
      (95% CI)
      P
      Composite kidney disease outcome
      50% reduction in GFR from baseline or kidney failure with KRT.
       Opioid use1.4 (1.2-1.7)<0.0011.6 (1.3-2.0)<0.001
       NSAID use1.2 (1.0-1.5)0.041.1 (0.9-1.4)0.2
      Kidney failure with KRT
       Opioid use1.4 (1.1-1.7)0.0051.5 (1.2-2.0)<0.001
       NSAID use1.1 (0.8-1.3)0.61.0 (0.7-1.3)0.9
      Pre–kidney failure death
       Opioid use1.5 (1.2-2.0)0.0021.6 (1.1-2.2)0.009
       NSAID use0.9 (0.7-1.1)0.31.2 (0.8-1.7)0.5
      Hospitalization
       Opioid use1.7 (1.6-1.9)<0.0011.7 (1.5-1.9)<0.001
       NSAID use1.1 (1.0-1.3)0.011.1 (0.9-1.3)0.08
      Note: Other analgesics are nonopioid non-NSAID.
      Abbreviations: CI, confidence interval; CRIC, Chronic Renal Insufficiency Cohort; HR, hazard ratio; KRT, kidney replacement therapy; NSAID, nonsteroidal anti-inflammatory drug.
      a HR except for hospitalization, which is a rate ratio.
      b 50% reduction in GFR from baseline or kidney failure with KRT.
      Table 4 demonstrates the associations of time-updated opioid and NSAID exposure with outcomes in the subcohort comprising participants ever exposed to other (nonopioid non-NSAID) analgesics or tramadol during the study. The strength of association between opioid use and the outcomes was comparable to the full cohort. The association between NSAID use and hospitalization, kidney failure with KRT, the kidney disease composite, and death was no longer significant.
      Forest plots (Fig 1; Table S1) display the varying HRs for the association of each analgesic group and the outcomes within subgroups designated by age, sex, race, diabetes, GFR, and UPCR at baseline. The association between time-updated NSAID use and the composite kidney disease outcome was stronger in blacks versus nonblacks (HRs of 1.31 [95% CI, 1.01-1.69] and 0.83 [95% CI, 0.64-1.09], respectively; P = 0.02 for effect modification). The association of time-updated NSAID use and kidney failure with KRT also varied across sex and baseline eGFRs with a higher HR for males versus females (HRs of 1.21 [95% CI, 0.91-1.61] and 0.63 [95% CI, 0.45-0.88], respectively; P = 0.004 for effect modification) and significantly lower risk for kidney failure with KRT in the lower versus higher eGFR subgroups (HRs of 0.77 [95% CI, 0.56-1.0] and 1.38 [95% CI, 0.89-2.14], respectively, for eGFR ≤45 and >45 mL/min/1.73 m2; P = 0.02 for effect modification). The association of pre–kidney failure hospitalization with opioid use (Fig S1A; Table S1) was higher in the lower versus higher baseline UPCR subgroups (RRs of 1.90 [95% CI, 1.66-2.17] and 1.54 [95% CI, 1.36-1.74], respectively, for UPCRs below and above the median; P = 0.02 for effect modification). Varying association between NSAID use and pre–kidney failure hospitalization had no significant effect modification (Fig S1B; Table S1).
      Figure thumbnail gr1
      Figure 1Forest plots of adjusted hazard ratios of the composite kidney disease outcome, kidney failure with kidney replacement therapy (KRT), death, comparing time-updated opioid use in the past versus none, and time-updated nonsteroidal anti-inflammatory drug (NSAID) use versus none, stratified by key demographic and case-mix subgroups and adjusted for all other covariates in primary analysis. Abbreviations: eGFR, estimated glomerular filtration rate; PCR, protein-creatinine ratio.
      Sensitivity analyses examined 1,442 CRIC participants without diabetes at enrollment. In this subgroup, neither opioid nor NSAID use were associated with incident diabetes (HRs of 1.27 [95% CI, 0.87-1.84] and 1.03 [95% CI, 0.73-1.45], respectively).
      To further explore the impact of potential unmeasured confounders on the associations between opioids and NSAIDs and outcomes, we computed E values for potential unmeasured confounders for each risk estimate and the corresponding CI (Table S2).
      • Haneuse S.
      • VanderWeele T.J.
      • Arterburn D.
      Using the E-value to assess the potential effect of unmeasured confounding in observational studies.
      ,
      • VanderWeele T.J.
      • Ding P.
      Sensitivity analysis in observational research: introducing the E-value.
      E values ranged from 2.2 to 2.8 for the risk estimates determined for the associations between opioids and all outcomes and between 1.4 and 2.6 for the corresponding lower CIs. E values were in the higher portion of that range for the subcohort risk estimates but closer to the null for the weaker associations reported for NSAIDs and outcomes.
      We also explored potential confounding of other drug groups that may be used as analgesics, including anxiolytics and antiepileptics (Table 1). However, only antiepileptics were associated with the outcome of death. Hence, we repeated the analysis including antiepileptics with the time-dependent covariates input to the marginal structural models for death. The results were essentially unchanged from those reported in Table 4.

      Discussion

      In this cohort of adults with CKD, we demonstrated that reported opioid use within 30 days of ascertainment and treated as a time-updated exposure was associated with a substantial risk for adverse kidney disease outcomes, death, and hospitalization. This was in contrast with the unexpected and modest relationship of NSAID use with adverse outcomes. The association between NSAID use and adverse kidney disease events was most prominent in blacks, with a potentially beneficial association with outcomes observed in subgroups including women and those with lower eGFRs.
      Physicians have long reported associations between various analgesics and kidney disease. “Analgesic nephropathy” is characterized by papillary necrosis, chronic interstitial nephritis, and progressive decreases in GFRs.
      • Buckalew Jr., V.M.
      • Schey H.M.
      Analgesic nephropathy: a significant cause of morbidity in the United States.
      Phenacetin was implicated as the principal causative agent, followed by aspirin and NSAIDs. The addition of caffeine to analgesic formulations may also exacerbate kidney injury.
      • Buckalew Jr., V.M.
      • Schey H.M.
      Analgesic nephropathy: a significant cause of morbidity in the United States.
      ,
      • Dubach U.C.
      • Rosner B.
      • Sturmer T.
      An epidemiologic study of abuse of analgesic drugs. Effects of phenacetin and salicylate on mortality and cardiovascular morbidity (1968 to 1987).
      Reports of analgesic nephropathy led to the worldwide ban of phenacetin and several combination analgesics.
      • Noels L.M.
      • Elseviers M.M.
      • de Broe M.E.
      Impact of legislative measures on the sales of analgesics and the subsequent prevalence of analgesic nephropathy: a comparative study in France, Sweden and Belgium.
      ,
      • Henrich W.L.
      • Agodoa L.E.
      • Barrett B.
      • et al.
      Analgesics and the kidney: summary and recommendations to the Scientific Advisory Board of the National Kidney Foundation from an Ad Hoc Committee of the National Kidney Foundation.
      However, epidemiologic studies examining analgesics and kidney failure have revealed mixed findings.
      • Dubach U.C.
      • Rosner B.
      • Sturmer T.
      An epidemiologic study of abuse of analgesic drugs. Effects of phenacetin and salicylate on mortality and cardiovascular morbidity (1968 to 1987).
      ,
      • Elseviers M.M.
      • De Broe M.E.
      A long-term prospective controlled study of analgesic abuse in Belgium.
      The Physician Health Study showed no risk for decreased GFRs among moderate users of aspirin, acetaminophen, or NSAIDs.
      • Rexrode K.M.
      • Buring J.E.
      • Glynn R.J.
      • Stampfer M.J.
      • Youngman L.D.
      • Gaziano J.M.
      Analgesic use and renal function in men.
      ,
      • Kurth T.
      • Glynn R.J.
      • Walker A.M.
      • et al.
      Analgesic use and change in kidney function in apparently healthy men.
      Several case-control studies found that substantial consumption of acetaminophen, aspirin, and NSAIDs was associated with increased risk for kidney failure.
      • Pommer W.
      • Bronder E.
      • Greiser E.
      • et al.
      Regular analgesic intake and the risk of end-stage renal failure.
      ,
      • Perneger T.V.
      • Whelton P.K.
      • Klag M.J.
      Risk of kidney failure associated with the use of acetaminophen, aspirin, and nonsteroidal antiinflammatory drugs.
      A study of adults with CKD and comparable controls found acetaminophen, but not aspirin, to be associated with incident disease.
      • Sandler D.P.
      • Smith J.C.
      • Weinberg C.R.
      • et al.
      Analgesic use and chronic renal disease.
      Another study of advanced CKD not requiring KRT revealed that cumulative acetaminophen and aspirin exposure was associated with a risk for CKD.
      • Fored C.M.
      • Ejerblad E.
      • Lindblad P.
      • et al.
      Acetaminophen, aspirin, and chronic renal failure.
      However, another study of patients with rheumatoid arthritis using COX-2 inhibitors showed no harmful effects from these analgesics except in advanced CKD.
      • Moller B.
      • Pruijm M.
      • Adler S.
      • Scherer A.
      • Villiger P.M.
      • Finckh A.
      Chronic NSAID use and long-term decline of renal function in a prospective rheumatoid arthritis cohort study.
      NSAID use in a large cohort of active healthy US soldiers demonstrated a dose-dependent increased but modest risk for both acute kidney injury and CKD.
      • Nelson D.A.
      • Marks E.S.
      • Deuster P.A.
      • O'Connor F.G.
      • Kurina L.M.
      Association of nonsteroidal anti-inflammatory drug prescriptions with kidney disease among active young and middle-aged adults.
      Studies, including this group’s, reveal a higher frequency (9%-36%) of NSAID use in CKD than one might expect given recommendations against their use.
      • Gooch K.
      • Culleton B.F.
      • Manns B.J.
      • et al.
      NSAID use and progression of chronic kidney disease.
      • Hull S.
      • Mathur R.
      • Dreyer G.
      • Yaqoob M.M.
      Evaluating ethnic differences in the prescription of NSAIDs for chronic kidney disease: a cross-sectional survey of patients in general practice.
      • Plantinga L.
      • Grubbs V.
      • Sarkar U.
      • et al.
      Nonsteroidal anti-inflammatory drug use among persons with chronic kidney disease in the United States.
      • Patel K.
      • Diamantidis C.
      • Zhan M.
      • et al.
      Influence of creatinine versus glomerular filtration rate on non-steroidal anti-inflammatory drug prescriptions in chronic kidney disease.
      Approximately 20% of dialysis patients are found to have used NSAIDs consistently during the years preceding KRT initiation.
      • Kristensen S.L.
      • Fosbol E.L.
      • Kamper A.L.
      • et al.
      Use of nonsteroidal anti-inflammatory drugs prior to chronic renal replacement therapy initiation: a nationwide study.
      In our report of NSAID use in the CRIC Study, a quarter of study participants reported NSAID use at baseline or at least 1 annual visit, with a substantial proportion of users reporting treatment over the study.
      • Zhan M.
      • St Peter W.L.
      • Doerfler R.M.
      • et al.
      Patterns of NSAIDs use and their association with other analgesic use in CKD.
      Relatively few reports describe opioid use in non–KRT-requiring CKD, with most data coming from KRT patients.
      • Wyne A.
      • Rai R.
      • Cuerden M.
      • Clark W.F.
      • Suri R.S.
      Opioid and benzodiazepine use in end-stage renal disease: a systematic review.
      One study revealed that almost a third of patients with non–KRT-requiring CKD were prescribed an opioid, with the likelihood increasing with declining GFRs.
      • Novick T.K.
      • Surapaneni A.
      • Shin J.I.
      • et al.
      Prevalence of opioid, gabapentinoid, and NSAID use in patients with CKD.
      This is in contradistinction to NSAID prescriptions, which diminished with declining GFRs.
      • Novick T.K.
      • Surapaneni A.
      • Shin J.I.
      • et al.
      Prevalence of opioid, gabapentinoid, and NSAID use in patients with CKD.
      Besides the well-documented hazards of opioid use in the general population, including mortality
      • Hall A.J.
      • Logan J.E.
      • Toblin R.L.
      • et al.
      Patterns of abuse among unintentional pharmaceutical overdose fatalities.
      ,
      • Gomes T.
      • Tadrous M.
      • Mamdani M.M.
      • Paterson J.M.
      • Juurlink D.N.
      The burden of opioid-related mortality in the United States.
      and lack of a beneficial treatment effect versus nonopioid analgesics,
      • Krebs E.E.
      • Gravely A.
      • Nugent S.
      • et al.
      Effect of opioid vs nonopioid medications on pain-related function in patients with chronic back pain or hip or knee osteoarthritis pain: the SPACE randomized clinical trial.
      their risks are compounded in CKD, for which dosing of many opioids is affected by decreased clearance. Accumulation of both parent drugs’ metabolites
      • Osborne R.J.
      • Joel S.P.
      • Slevin M.L.
      Morphine intoxication in renal failure: the role of morphine-6-glucuronide.
      ,
      • Conway B.R.
      • Fogarty D.G.
      • Nelson W.E.
      • Doherty C.C.
      Opiate toxicity in patients with renal failure.
      and enhanced adverse effects with the use of these drugs in CKD make the adverse outcomes described here highly plausible.
      • Kurella M.
      • Bennett W.M.
      • Chertow G.M.
      Analgesia in patients with ESRD: a review of available evidence.
      ,
      • Dean M.
      Opioids in renal failure and dialysis patients.
      Interpretation of the findings warrant consideration of the limitations inherent to its design. With observational analyses, one cannot overlook confounding by indication whereby use or nonuse of one or the other analgesic is driven by factors that may be associated with the outcome of interest rather than the primary exposure, in this case, analgesic choice. To minimize confounding by indication, we used causal inference models with inverse probability weighting by expected analgesic use in the examination of the association of analgesics with outcomes. More extensive characterization of the time-updated exposure including variations in dosage and drug discontinuation was limited by the modest sample size. Additionally, the CRIC Study was limited by its lack of a detailed pain assessment including measures of severity and type of pain. However, we used a wide array of available measures of severity of illness and function embedded in the KDQOL-36 and SF-12, which include a gauge of pain’s impedance of work and ability to perform activities of daily living.
      Notably, analgesic use exposure ascertainment in CRIC was restricted to self-report, limited to the 30 days preceding an annual visit, and did not necessarily reflect actual use over more distant intervals. Previous studies have examined the fidelity of self-report of NSAID and acetaminophen use when compared with urine drug screening.
      • Loo R.L.
      • Chan Q.
      • Brown I.J.
      • et al.
      A comparison of self-reported analgesic use and detection of urinary ibuprofen and acetaminophen metabolites by means of metabonomics: the INTERMAP Study.
      Although the study evaluated the use of NSAIDs and opioids versus nonusers of these drugs and the subgroup who were ever treated with any analgesics including the broader range of pain modulators such as acetaminophen, it did not assess the independent effect of the latter because this group served as the analysis reference group. Also, one cannot rule out the possibility that analgesic choice may have been different during the years of this cohort before the opioid epidemic was more broadly recognized. However, we expect the reported associations would only be minimally influenced by secular trends in use.
      Of note, this is the first study we are aware of examining the comparative harm of NSAID versus opioid use in CKD. Both classes of agents have recognized risk profiles that are likely amplified in CKD, justifying close consideration of their risk versus benefit. Perhaps most importantly, the equipoise may be avoided with consideration of nonpharmacologic analgesic interventions that often show promising effectiveness in pain syndromes.
      • Chou R.
      • Deyo R.
      • Friedly J.
      • et al.
      Nonpharmacologic therapies for low back pain: a systematic review for an American College of Physicians Clinical Practice Guideline.
      ,
      • Bonakdar R.A.
      Integrative pain management.
      In conclusion, our study findings suggest that opioid use is associated with greater harm in CKD than NSAIDs, with a substantial increase in risk for death and poor kidney outcomes. The adverse effects of NSAIDs appear to be less consistent across subgroups with evidence for patient strata in which NSAID use is at least neutral and possibly beneficial. Further studies are needed to confirm such variable findings. Although a prospective trial comparing analgesics in patients with CKD with comparable degrees of pain and indications for analgesics is desirable, such a study is unlikely. Future guidance for strategies for patients with non–KRT-requiring CKD therefore will be based on comparative harm studies such as this and further studies are needed to verify the reported findings.

      Article Information

      CRIC Study Investigators

      Lawrence J. Appel, MD, MPH, Harold I. Feldman, MD, MSCE, Alan S. Go, MD, Jiang He MD, PhD, John W. Kusek, PhD, James P. Lash, MD, Panduranga S. Rao, MD, Mahboob Rahman, MD, and Raymond R. Townsend, MD.

      Authors’ Full Names and Academic Degrees

      Min Zhan, PhD, Rebecca M. Doerfler, PhD, Dawei Xie, PhD, Jing Chen, MD, Hsiang-Yu Chen, MS, Clarissa J. Diamantidis, MD, Mahboob Rahman, MD, Ana C. Ricardo, MD, James Sondheimer, MD, Louise Strauss, BSN, Lee-Ann Wagner, MD, Matthew R. Weir, MD, and Jeffrey C. Fink, MD, MS.

      Authors’ Contributions

      Research idea and study design: MZ, JCF; data acquisition: DX, HYC; data analysis/interpretation: MZ, MR, ACR, JS, LS, L-AW, JCF; data curation: RMD, JCF; data visualization: RMD, JCF, JC; statistical analysis: MZ; supervision or mentorship: CJD, MRW. Each author contributed important intellectual content during manuscript drafting or revision and agrees to be personally accountable for the individual’s own contributions and to ensure that questions pertaining to the accuracy or integrity of any portion of the work, even one in which the author was not directly involved, are appropriately investigated and resolved, including with documentation in the literature if appropriate.

      Support

      Drs Fink, Doerfler, and Zhan were supported by National Institutes of Health (NIH)/ National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) R01 DK090008 . Funding for the CRIC Study was obtained under a cooperative agreement from NIDDK ( U01DK060990 , U01DK060984 , U01DK061022 , U01DK061021 , U01DK061028 , U01DK060980 , U01DK060963 , and U01DK060902 ). In addition, this work was supported in part by the Perelman School of Medicine at the University of Pennsylvania Clinical and Translational Science Award (CTSA) NIH/ National Center for Advancing Translational Sciences (NCATS) UL1TR000003 , Johns Hopkins University UL1 TR-000424 , University of Maryland GCRC M01 RR-16500 , Clinical and Translational Science Collaborative of Cleveland , UL1TR000439 from the NCATS component of the NIH and NIH Roadmap for Medical Research, Michigan Institute for Clinical and Health Research (MICHR) V 2014.07.28 UL1TR000433 , University of Illinois at Chicago CTSA UL1RR029879 , Tulane COBRE for Clinical and Translational Research in Cardiometabolic Diseases P20 GM109036 , Kaiser Permanente NIH/ National Center for Research Resources UCSF-CTSI UL1 RR-024131 . The funders did not have a role in study design; data collection, analysis, or reporting; or the decision to submit for publication.

      Financial Disclosure

      The authors declare that they have no relevant financial interests.

      Peer Review

      Received July 5, 2019. Evaluated by 3 external peer reviewers and a statistician, with editorial input from an Acting Editor-in-Chief (Editorial Board Member Jane Schell, MD). Accepted in revised form December 11, 2019. The involvement of an Acting Editor-in-Chief to handle the peer-review and decision-making processes was to comply with AJKD’s procedures for potential conflicts of interest for editors, described in the Information for Authors & Journal Policies.

      Supplementary Material

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