Background and Objectives The concomitant use of prescription opioids and skeletal muscle relaxants has been associated with opioid overdose, but little data exist on the head-to-head safety of these drug combinations. The objective of this study was to compare the risk of opioid overdose among patients on long-term opioid therapy who concurrently initiate skeletal muscle relaxants.
Methods We conducted an active comparator cohort study spanning 2000 to 2019 using healthcare utilization data from 4 US commercial and public insurance databases. Individuals were required to have at least 180 days of continuous enrollment and at least 90 days of continuous prescription opioid use immediately before and on the date of skeletal muscle relaxant initiation. Exposures were the concomitant use of prescription opioids and skeletal muscle relaxants, and the main outcome was the hazard ratio (HR) and bootstrapped 95% CI of opioid overdose resulting in an emergency department visit or hospitalization. The primary analysis quantified opioid overdose risk across 7 prescription opioid-skeletal muscle relaxant therapies and a negative control outcome (sepsis) to assess potential confounding by unmeasured illicit opioid use. Secondary analyses evaluated two-group and five-group comparisons in patients with similar baseline characteristics; individuals without previous recorded substance abuse; and subgroups stratified by baseline opioid dosage, benzodiazepine codispensing, and oxycodone or hydrocodone use.
Results Weighted HR of opioid overdose relative to cyclobenzaprine was 2.52 (95% CI 1.29–4.90) for baclofen; 1.64 (95% CI 0.81–3.34) for carisoprodol; 1.14 (95% CI 0.53–2.46) for chlorzoxazone/orphenadrine; 0.46 (95% CI 0.17–1.24) for metaxalone; 1.00 (95% CI 0.45–2.20) for methocarbamol; and 1.07 (95% CI 0.49–2.33) for tizanidine in the 30-day intention-to-treat analysis. Findings were similar in the as-treated analysis, 2-group and 5-group comparisons, and patients without previous recorded substance abuse. None of the therapies relative to cyclobenzaprine were associated with sepsis, and no subgroups indicated an increased risk of opioid overdose.
Discussion Concomitant use of prescription opioids and baclofen relative to cyclobenzaprine is associated with opioid overdose. Clinical interventions may focus on prescribing alternatives in the same drug class or providing access to opioid antagonists if treatment with both medications is necessary for pain management.
- hazard ratio;
- International Classification of Diseases, Ninth Revision, Clinical Modification;
- interquartile range;
- incidence rate;
- morphine milligram equivalent
Overdose deaths involving prescription opioids have quadrupled over the last 20 years in the United States.1 From 1999 to 2018, more than 232,000 people died of overdose related to opioid prescriptions.1,2 Over the time period, opioid overdose deaths involving other drug classes have increased. In 2016, the US Food and Drug Administration3 warned against the combined use of prescription opioids with CNS depressants due to an increased risk of sedation and other adverse events. However, there are few studies that have quantified these risks or identified alternatives for patients who require treatment with opioids and other CNS depressants.
Skeletal muscle relaxants are among the most commonly coprescribed medications with opioids for pain management.4 Between 2005 and 2016, 67.2% (95% CI 62.0%–72.5%) of office visits with a continuing skeletal muscle relaxant prescription also recorded concomitant use of an opioid.4 Although the mechanism of drug-drug interaction has not been fully elucidated, coprescription of baclofen and carisoprodol has been associated with opioid overdose and unintentional traumatic injury due to potential additive CNS depression.5,6 It is unclear whether all skeletal muscle relaxants, when used in combination with opioids, have the same degree of opioid overdose risk or whether there may be alternatives for patients who require treatment with both medications.
The objective of this study was to evaluate the comparative safety of skeletal muscle relaxants when used concomitantly with prescription opioids. We specifically focused on the risk of opioid overdose among patients on long-term opioid therapy.
We conducted an active comparator cohort study to quantify the comparative risk of opioid overdose for 7 prescription opioid and skeletal muscle relaxant combination therapies.
We used data spanning January 1, 2000, to December 31, 2014, from Medicaid Analytic eXtract (MAX); January 1, 2012, to December 31, 2017, from a Medicare fee-for-service cohort of beneficiaries with diabetes, heart failure, and/or stroke; January 1, 2004, to December 31, 2019, from Optum© Clinformatics Data Mart; and January 1, 2003, to December 31, 2018, from IBM MarketScan Research Database. The databases contain deidentified and longitudinal administrative pharmacy and medical claims for commercially insured individuals (Optum© Clinformatics Data Mart and IBM MarketScan Research Database), publicly insured individuals younger than 65 years (Medicaid), and beneficiaries aged 65 years and older or younger than 65 years with disabilities and/or end-stage renal disease (Medicare) across the United States. Patient-level ZIP codes in Medicaid were linked to the 2017 American Community Survey from the US Census Bureau to assess measures of socioeconomic status.7 ZIP codes were also linked to the 2013 rural-urban continuum codes from the US Department of Agriculture Economic Research Service to distinguish between metropolitan and nonmetropolitan areas.8
Eligible individuals were identified based on their first dispensing for a skeletal muscle relaxant at age 18 years or older (cohort entry date) immediately after at least 180 days of continuous health plan enrollment with no previous skeletal muscle relaxant dispensing and 90 days of continuous prescription opioid use (Figure 1). The skeletal muscle relaxants under study included baclofen, carisoprodol, cyclobenzaprine, metaxalone, methocarbamol, tizanidine, and chlorzoxazone or orphenadrine (evaluated as a single group). Continuous opioid use was defined by prescription fills for opioids with days’ supply that covered the 90 days immediately before and on the cohort entry date. Grace periods of up to 14 days were incorporated between opioid prescriptions to account for inaccuracies in the days’ supply estimation. Patients who experienced opioid overdose before or on the cohort entry date were excluded.
Outcome Assessment and Follow-up
Opioid overdose was defined using International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) and ICD, Tenth Revision, CM (ICD-10-CM) codes for an opioid overdose episode resulting in hospitalization or an emergency department visit (eTable 1, links.lww.com/WNL/C171). The ICD-9-CM codes used to define opioid overdose, together with codes for poisoning by heroin, have a specificity of 99.9%.9 The ICD-10-CM algorithm for opioid overdose unrelated to heroin poisoning has a positive predictive value of 79.4%.9,10
We used sepsis as a negative control outcome to evaluate potential confounding by illicit opioid use, which is undercaptured in claims data. Patients who use illicit opioids may be more likely to be prescribed certain opioid-skeletal muscle relaxant therapies, and intravenous drug use associated with illicit opioids may lead to sepsis. Different rates of sepsis across the 7 treatment strategies could suggest that illicit opioid use may have biased the findings in the primary outcome analyses.
We performed a 30-day intention-to-treat analysis to evaluate the acute risk of opioid overdose after initiation of concomitant therapy and to avoid bias from potential informative censoring. Follow-up began the day after cohort entry until outcome occurrence, end of continuous enrollment, death, nursing home admission, or end of the 30-day period immediately after the cohort entry date. In the as-treated analysis, patients could contribute follow-up time beyond 30 days but were, in addition, censored at prescription opioid discontinuation, skeletal muscle relaxant discontinuation, initiation of a skeletal muscle relaxant from another group, or end of the 365-day period immediately after the cohort entry date. We allowed grace periods of up to 14 days between prescriptions for both opioids and skeletal muscle relaxants, and the medication discontinuation date was defined as 14 days after the final prescription’s days’ supply.
We assessed demographic information, comorbidities, pain conditions, other prescription fills, previous prescription opioid utilization, and healthcare utilization over the 180 days immediately before and on the cohort entry date. We also used patient-level ZIP codes in Medicaid to capture socioeconomic status variables and type of metropolitan area.
We used matching weights, an extension of propensity score–based weighting approaches, to adjust for covariates in this multigroup setting. Within each database, a multinomial logistic regression model was used to estimate the probability of treatment for each prescription opioid-skeletal muscle relaxant therapy as a function of the covariates. Each patient was subsequently assigned a matching weight, which is a ratio of the smallest conditional probability of treatment (of all probabilities estimated) and the conditional probability of receiving the treatment actually received.11 The estimand of this weighting method (i.e., the subgroup of patients that would theoretically be eligible to receive any of the combination therapies under study) is asymptotically equivalent to that of 1:1 propensity score matching across the treatment groups provided that common support holds.11
Within each database, we fit a Cox proportional hazards model weighted by matching weights to estimate the hazard ratios (HRs) and bootstrapped 95% CIs of opioid overdose for each treatment relative to a common reference group (i.e., cyclobenzaprine). To estimate a common HR of opioid overdose for each treatment group across all databases, we fit a Cox proportional hazards model stratified by database in the pooled data and weighted by matching weights. This approach allows the baseline hazard of opioid overdose to vary by database and assumes that the HR is constant across the databases. The p values were adjusted for multiple testing using the Bonferroni correction, which controls the probability of falsely rejecting 1 or more null hypotheses.12 We calculated adjusted p values by multiplying each nominal p value by the number of comparisons (6).
We conducted several additional analyses. Although in the same drug class, skeletal muscle relaxants have different indications for treatment. Baclofen is approved for spasticity (e.g., resulting from spinal cord diseases), whereas the other skeletal muscle relaxants are approved for muscle spasm (e.g., acute musculoskeletal conditions), and tizanidine is approved for both indications in the United States.13 We also observed that tizanidine initiators tended to be more similar to the baclofen initiators relative to the initiators of other skeletal muscle relaxants, and initiators of other skeletal muscle relaxants were quite similar to each other. We therefore conducted 2 subgroup analyses comparing: (1) baclofen and tizanidine and (2) carisoprodol, cyclobenzaprine, chlorzoxazone/orphenadrine, metaxalone, and methocarbamol. From the seven-group comparison, we also conducted a subgroup analysis restricted to patients without previous substance abuse as recorded by ICD codes for opioid dependence, opioid abuse, alcohol abuse, tobacco use, and other drug abuse in the baseline period to reduce potential confounding by unmeasured illicit opioid use. We separately stratified our analyses by baseline benzodiazepine use (binary); the median morphine milligram equivalents (MMEs) (above or equal to the median [high] or below the median [low] MMEs); oxycodone dispensing (binary); and hydrocodone dispensing (binary) on the cohort entry date to identify subgroups with an increased risk of opioid overdose. In Medicaid, we adjusted for socioeconomic status measures and rural-urban area to account for residual confounding that may not be captured by other demographic variables. We fit multinomial logistic regression models for each analysis to reestimate matching weights for each subgroup.
Standard Protocol Approvals, Registrations, and Patient Consents
This study was approved by the Institutional Review Board at Brigham and Women’s Hospital.
The data used in this study cannot be shared because of data use agreements for each of the 4 databases.
We identified 136,650 baclofen initiators; 117,633 carisoprodol initiators; 32,152 chlorzoxazone/orphenadrine initiators; 552,649 cyclobenzaprine initiators; 67,435 metaxalone initiators; 124,662 methocarbamol initiators; and 214,838 tizanidine initiators across the 4 databases (eFigure 1). The mean age at skeletal muscle relaxant initiation was 53 years (SD: 14.3 years), and 62% were females in the weighted population (Table 1; eTables 2 and 3, links.lww.com/WNL/C171). Before weighting, demographic characteristics varied between initiators of baclofen and tizanidine and those of other skeletal muscle relaxants. In the unweighted population, the baclofen and tizanidine groups tended to be older with a mean age of 59 years (SD: 14.8 years) relative to the other treatment groups. The baclofen group also included more patients from California compared with other skeletal muscle relaxants, which was most pronounced in Medicaid and persisted across all databases before weighting (eTables 4A-11). Comorbidities, pain conditions, other prescription fills, previous prescription opioid use, and healthcare utilization were otherwise similar across the treatment groups before and after weighting (eTables 2–11).14 The database-specific propensity score distributions for each treatment before and after weighting are presented in eFigures 2A-9F.
In the first 30 days of follow-up, 887 opioid overdose events requiring emergent care occurred across the 7 treatment groups. The highest absolute number of events occurred in the cyclobenzaprine (n = 278) and baclofen (n = 266) groups across the 4 databases. The crude incidence rate (IR) of opioid overdose varied by database but was high among baclofen initiators (e.g., crude IR of opioid overdose for baclofen ranged from 14.91 events per 1,000 person-years (95% CI 11.02–20.18) in IBM MarketScan Research Database to 45.78 events per 1,000 person-years (95% CI 38.70–54.16) in Medicare (eTable 12, links.lww.com/WNL/C171). After adjustment, the pooled weighted HR for opioid overdose relative to cyclobenzaprine was 2.52 (95% CI 1.29–4.90; adjusted p value = 0.04) for baclofen; 1.64 (95% CI 0.81–3.34; adjusted p value > 0.99) for carisoprodol; 1.14 (95% CI 0.53–2.46; adjusted p value > 0.99) for chlorzoxazone/orphenadrine; 0.46 (95% CI 0.17–1.24; adjusted p value = 0.75) for metaxalone; 1.00 (95% CI 0.45–2.20; adjusted p value > 0.99) for methocarbamol; and 1.07 (95% CI 0.49–2.33; adjusted p value > 0.99) for tizanidine (Figure 2).
A total of 1,420 opioid overdose events were captured across the 7 treatment groups in the as-treated analysis, with most occurring in the baclofen (n = 403) and cyclobenzaprine (n = 388) groups. The median length of follow-up varied by treatment group and database, ranging from 23 days for chlorzoxazone/orphenadrine initiators (interquartile range [IQR]: 24 days) to 43 days for baclofen (IQR: 40 days), carisoprodol (IQR: 72 days), and tizanidine initiators (IQR: 43 days) (eTable 13, links.lww.com/WNL/C171). After adjustment, the pooled weighted HR for opioid overdose relative to cyclobenzaprine was 2.07 (95% CI 1.18–3.64; adjusted p value = 0.07) for baclofen; 1.66 (95% CI 0.94–2.94; adjusted p value = 0.49) for carisoprodol; 0.90 (95% CI 0.45–1.81; adjusted p value > 0.99) for chlorzoxazone/orphenadrine; 0.74 (95% CI 0.35–1.56; adjusted p value > 0.99) for metaxalone; 0.87 (95% CI 0.43–1.75; adjusted p value > 0.99) for methocarbamol; and 1.15 (95% CI 0.62–2.14; adjusted p value > 0.99) for tizanidine (Figure 2).
Negative Control Outcome Analysis
In the first 30 days of follow-up, 4,324 sepsis events occurred across the 7 treatment groups. The highest absolute number of events occurred among cyclobenzaprine (n = 1,810) and baclofen (n = 907) initiators across the 4 databases (eTable 14, links.lww.com/WNL/C171). After adjustment, the pooled weighted HR for sepsis relative to cyclobenzaprine was 1.09 (95% CI 0.78–1.52; adjusted p value > 0.99) for baclofen; 0.80 (95% CI 0.56–1.15; adjusted p value > 0.99) for carisoprodol; 1.06 (95% CI 0.76–1.49; adjusted p value > 0.99) for chlorzoxazone/orphenadrine; 0.85 (95% CI 0.60–1.22; adjusted p value > 0.99) for metaxalone; 0.90 (95% CI 0.63–1.27; adjusted p value > 0.99) for methocarbamol; and 0.72 (95% CI 0.50–1.05; adjusted p value = 0.50) for tizanidine (Figure 2).
In the two-group comparison, baclofen relative to tizanidine was associated with opioid overdose in the weighted analysis (pooled weighted HR 2.50, 95% CI 1.95–3.21) (eTable 15, links.lww.com/WNL/C171). In the five-group comparison, none of the skeletal muscle relaxants relative to cyclobenzaprine were associated with opioid overdose after adjustment (eTable 16). In a separate analysis of patients without previous recorded substance abuse, baclofen relative to cyclobenzaprine was associated with opioid overdose in the weighted analysis (pooled weighted HR 2.48, 95% CI 1.02–6.04), whereas the other skeletal muscle relaxants relative to cyclobenzaprine were unassociated with opioid overdose (Table 2; eTable 17). We did not observe increased risks of opioid overdose among patients prescribed high opioid dosages at baseline; individuals coprescribed benzodiazepines; individuals on oxycodone therapy on the cohort entry date; or individuals on hydrocodone therapy on the cohort entry date (Figure 3; eTables 18–25).
In a sensitivity analysis, we adjusted for measures of socioeconomic status and rural-urban area using individual-level ZIP codes in Medicaid. Patients initiating baclofen were of higher socioeconomic status and more likely to live in metropolitan areas compared with initiators of other skeletal muscle relaxants before weighting (eTables 5A-5B, links.lww.com/WNL/C171). Adjustment for these variables did not substantially change the HRs and 95% CIs of opioid overdose relative to the primary analysis in the Medicaid database (eTable 26).
In this comparative safety study of 7 skeletal muscle relaxants used concomitantly with prescription opioids, baclofen relative to cyclobenzaprine was associated with an increased risk of opioid overdose. Other skeletal muscle relaxants relative to cyclobenzaprine were unassociated with opioid overdose in the 30-day intention-to-treat and as-treated analyses. We observed similar results in patients without previous recorded substance abuse and in the 2-group and 5-group comparisons among patients with similar baseline characteristics. None of the skeletal muscle relaxants relative to cyclobenzaprine were associated with sepsis, which may suggest a lower risk of unmeasured confounding by illicit opioid use in our head-to-head comparison of the 7 medication combinations. No increased risk of opioid overdose was observed across subgroups stratified by baseline opioid dosage, benzodiazepine coprescription, or oxycodone or hydrocodone therapy on the cohort entry date.
Our cohort study evaluated a potentially harmful medication combination that has recently been associated with adverse events in other settings. In 2 claims-based screening studies of administrative claims data, baclofen particularly increased the risks of opioid overdose and unintentional traumatic injury when codispensed with opioids.5,6 A separate population-based cohort study using claims data from 2005 to 2015 found that patients coprescribed baclofen (HR 1.83, 95% CI 1.11–3.04) or carisoprodol (HR 1.84, 95% CI 1.34–2.54) had an increased risk of opioid overdose compared with patients prescribed opioids alone, particularly among prevalent opioid users.15 Our results are in line with previous findings in a larger study population of commercially and publicly insured individuals in the United States. We also used an active comparator design that evaluates the comparative safety of prescription opioid-skeletal muscle relaxant therapies to identify alternatives when both medications are necessary for treatment. This approach allows for improved adjustment of measured and unmeasured confounding and other sources of bias that are frequent in observational studies using claims data.16
In our stratified analyses, high prescription opioid dosages, concomitant benzodiazepine use, and oxycodone or hydrocodone therapy on the cohort entry date did not suggest an increased risk of opioid overdose for the skeletal muscle relaxant groups. Previous studies have identified elevated risks of opioid overdose with high vs low opioid dosages and separately with benzodiazepine coprescription relative to prescription opioid use alone.17,–,19 We may not have observed similar results due to limited power to detect these associations, particularly in stratified analyses with small numbers of events. The findings for the oxycodone and hydrocodone subgroups may also indicate lack of power or no true change in risk between users and nonusers based on dispensings on the cohort entry date.
Although we cannot determine the cause of each opioid overdose event, our findings have important implications for clinical practice. Greater awareness among clinicians about the adverse effects of these medications is necessary to encourage prescribing of alternatives within the same drug class, especially in the absence of evidence suggesting another advantage to choosing one skeletal muscle relaxant over another. Because individuals on long-term opioid therapy tend to take multiple medications, discussions with patients may be warranted to evaluate the risks of concomitant medication use and modify treatment strategies. For patients who require treatment with prescription opioids and baclofen, clinicians may consider providing access to opioid antagonists to prevent complications of opioid overdose.
Our study has several limitations. We defined concomitant use of prescription opioids and skeletal muscle relaxants based on dispensing dates and days’ supply, but we were unable to assess whether patients took these medications concurrently. We also could not determine whether opioid overdose events were due to true drug-drug interactions, an increase in the number of prescription opioid pills taken, illicit opioid use, or other factors. Based on the findings from the negative control outcome analysis, subgroup of patients without previous recorded substance abuse, and sensitivity analysis adjusting for socioeconomic status measures and metropolitan area in Medicaid, substantial confounding due to illicit opioid use may be unlikely in our primary analyses. However, there may be confounding by other social-level and family-level environmental factors that are not captured in claims data. Although we adjusted for several covariates, there could be differences in pain severity, alcohol and other drug use, and drug metabolism across the treatment groups that may contribute to opioid overdose. Our study included prevalent opioid users, which may have introduced bias; however, all patients were required to have at least 90 days of prescription opioid use before the start of follow-up. In addition, it is unlikely that indications for prevalent opioid use differ across the treatment groups. To the extent possible, we adjusted for pain conditions associated with long-term opioid therapy. The outcome definition includes opioid overdoses that required emergent care, and it is possible that fatal events or events treated with naloxone outside of hospitals were not recorded. The lack of sensitivity is unlikely to bias our relative measures of association due to the high specificity of the ICD code algorithm (99.9%).9 Bias from competing risks, such as suicide due to severe pain, is possible; however, this bias is unlikely due to the rarity of potential competing events. We were likely underpowered to detect clinically relevant changes in opioid overdose risk, particularly in the stratified analyses, due to the small numbers of patients concurrently taking these medications. Larger follow-up studies are needed to investigate additional risk factors that may predispose patients to opioid overdose while on skeletal muscle relaxant therapy.
The results of this large, nationwide US cohort study in 4 large administrative claims databases suggest that concomitant use of baclofen while on prescription opioids may increase the risk of opioid overdose relative to cyclobenzaprine. Greater awareness among clinicians about the risks of concomitant baclofen use may motivate discussions regarding prescribing of alternatives or ensuring access to opioid antagonists in patients for whom baclofen is the only option available.
The authors report no targeted funding.
K. Bykov has served as a consultant on evidence-based management of chronic pain, including opioids, for Alosa Health Foundation that develops academic detailing programs; R.J. Glynn has received funding from grants to the Brigham and Women’s Hospital from AstraZeneca, Kowa, Novartis Pharmaceuticals Corporation, and Pfizer; M.L. Barnett has been retained as an expert witness for government plaintiffs in lawsuits against opioid manufacturers; J.J. Gagne has received salary support from grants from Eli Lilly and Company and Novartis Pharmaceuticals Corporation to the Brigham and Women’s Hospital and has been a consultant to Optum, Inc., all for unrelated work. The other authors report no relevant disclosures. Go to Neurology.org/N for full disclosures.
Go to Neurology.org/N for full disclosures. Funding information and disclosures deemed relevant by the authors, if any, are provided at the end of the article.
Submitted and externally peer reviewed. The handling editors were Rebecca Burch, MD and José Merino, MD, MPhil, FAAN.
CME Course: NPub.org/cmelist
- Received October 28, 2021.
- Accepted in final form May 16, 2022.
- © 2022 American Academy of Neurology
Centers for Disease Control and Prevention. Prescription opioids overview; 2021. Accessed October 28, 2021. cdc.gov/drugoverdose/data/prescribing/overview.html.
Agency for Healthcare Research and Quality. Race, ethnicity, and language data: standardization for health care quality improvement; 2018. Accessed October 28, 2021. ahrq.gov/research/findings/final-reports/iomracereport/reldata3.html.