Abstract
This cohort study examines trends in concurrent gabapentin and opioid prescribing in the US, overall and by prescriber, patient, and county characteristics, between 2006 and 2018.
Gabapentin is a substance that is approved by the US Food and Drug Administration to treat partial seizures, pain due to damaged nerves, fibromyalgia, and restless legs syndrome; concurrent use with opioids can enhance the analgesic effect and produce a euphoric state. Ninety-five percent of gabapentin prescriptions are for off-label pain management, despite studies questioning its pain management effectiveness and reporting its misuse with concurrent opioid therapy. We examined 2006 to 2018 US trends in concurrent gabapentin and opioid prescribing, overall and by prescriber, patient, and county characteristics.
Methods
In this cohort study, we used 2006 to 2018 national deidentified pharmacy claims data from the IQVIA Real World Data Longitudinal Prescription Data capturing approximately 90% of prescriptions filled at retail pharmacies. Opioid analgesic (OA) and gabapentin episodes are defined by the first prescription fill date through the last day of supply; subsequent prescriptions within 60 days extend the episode by the amount of overlap; prescriptions filled after 60 days begin a new episode. Concurrent OA and gabapentin episodes (OACGs) are defined by any overlap. The specialty of the OACG primary prescriber is defined by the prescriber responsible for the most OA episode days. The IQVIA database describes patient sex and age cohort and prescriber location (state and county) and specialty; county urban/rural status, percentage of non-Hispanic White population (to examine variations in trends by race and ethnicity), and poverty rate were obtained from the Area Health Resource File. Additional details are provided in eMethods 1 and 2 in the Supplement. This study was conducted from March 17, 2021, to July 14, 2022, approved with a waiver of consent by RAND’s Institutional Review Board, and followed the STROBE reporting guideline.
Results
In 2006, OA episodes numbered 37.4 million and plateaued between 50.0 and 56.0 million before decreasing to 42.1 million in 2018. Gabapentin episodes numbered 1.5 million in 2006 and continually increased to 8.1 million in 2018. The percentage of OACGs increased from 1.9% in 2006 to 7.6% in 2018 (relative increase, 344%). Between 2006 and 2018, 18.1% of all OACGs consisted of OA and gabapentin episodes starting in the same week; the remainder were increasingly characterized as OA episodes starting more than 1 week prior to gabapentin episodes or gabapentin episodes started first, from 18.9% in 2006 to 62.9% in 2018 (Figure).
Figure. Prescribing Trends for Opioid Analgesics, Gabapentin, and Concurrent Use.
OACG indicates overlapping opioid analgesic and gabapentin episodes.
Overlapping OA and gabapentin episodes grew between 2006 and 2018 among all prescribers and patient groups, but were consistently most common among (1) pain specialist prescribers (19.2% compared with 4.2% among all other specialties) (2) female patients (5.2% compared with 4.2% among male patients); (3) patients 66 years or older (8.0% compared with 3.9% among all other age groups); (4) patients residing in rural counties (5.8% compared with 4.6% in urban counties); (5) patients residing in counties with the highest quartiles of non-Hispanic White population (6.2% compared with 4.7% in all other counties; and (6) patients residing in counties with the highest quartile of poverty (5.5% compared with 4.6% in all other counties) (Table).
Table. Annual Percentages of OACG Between 2006 and 2018 by Select Patient, Physician, and County Characteristics.
| Characteristic | OACG, % | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018 | |
| Overall | 4.8 | 1.9 | 2.4 | 2.7 | 3.2 | 3.5 | 4.3 | 4.5 | 5.2 | 5.7 | 6.3 | 6.8 | 7.4 | 7.6 |
| Physician specialty | ||||||||||||||
| Pain specialist | 19.2 | 9.8 | 11.4 | 12.6 | 14.7 | 16.6 | 19.0 | 19.6 | 21.9 | 23.1 | 24.4 | 25.4 | 26.0 | 24.4 |
| Psychiatrist | 7.6 | 3.8 | 4.3 | 4.7 | 5.4 | 6.0 | 6.8 | 8.1 | 9.5 | 10.9 | 13.0 | 15.9 | 17.1 | 15.1 |
| Oncologist | 6.7 | 3.0 | 3.5 | 3.8 | 4.5 | 5.2 | 5.6 | 6.4 | 7.2 | 8.0 | 9.1 | 10.3 | 11.4 | 11.8 |
| Adult primary care physician | 6.5 | 2.9 | 3.5 | 4.0 | 4.6 | 5.1 | 6.2 | 6.4 | 7.4 | 8.0 | 8.8 | 9.5 | 10.2 | 10.3 |
| Advanced practice clinician | 6.2 | 2.3 | 2.7 | 3.1 | 3.5 | 3.8 | 4.8 | 4.9 | 5.8 | 6.5 | 7.3 | 8.1 | 9.1 | 9.7 |
| Surgeon | 3.4 | 1.0 | 1.4 | 1.7 | 2.0 | 2.3 | 2.7 | 3.1 | 3.6 | 4.1 | 4.7 | 5.3 | 6.0 | 6.7 |
| Other specialty | 2.7 | 1.1 | 1.4 | 1.7 | 1.9 | 2.0 | 2.3 | 2.5 | 2.9 | 3.2 | 3.5 | 4.0 | 4.4 | 5.0 |
| Emergency physician | 1.5 | 0.3 | 0.4 | 0.6 | 0.7 | 0.8 | 1.0 | 1.2 | 1.5 | 1.9 | 2.4 | 2.8 | 3.4 | 3.9 |
| Dentist | 1.0 | 0.2 | 0.3 | 0.4 | 0.5 | 0.6 | 0.6 | 0.8 | 0.9 | 1.2 | 1.4 | 1.7 | 1.9 | 2.1 |
| Patient sex | ||||||||||||||
| Female | 5.2 | 2.1 | 2.6 | 3.0 | 3.5 | 3.9 | 4.7 | 4.9 | 5.6 | 6.1 | 6.8 | 7.4 | 8.0 | 8.3 |
| Male | 4.2 | 1.7 | 2.1 | 2.4 | 2.8 | 3.1 | 3.8 | 3.9 | 4.5 | 5.0 | 5.6 | 6.1 | 6.6 | 6.8 |
| Patient age, y | ||||||||||||||
| 12-17 | 0.5 | 0.2 | 0.3 | 0.3 | 0.3 | 0.3 | 0.4 | 0.5 | 0.5 | 0.6 | 0.6 | 0.7 | 0.8 | 0.9 |
| 18-25 | 0.9 | 0.4 | 0.5 | 0.5 | 0.6 | 0.7 | 0.8 | 0.9 | 0.9 | 1.1 | 1.2 | 1.2 | 1.3 | 1.4 |
| 26-35 | 2.2 | 0.9 | 1.1 | 1.3 | 1.6 | 1.8 | 2.1 | 2.1 | 2.4 | 2.7 | 2.9 | 3.1 | 3.2 | 3.2 |
| 36-45 | 3.9 | 1.8 | 2.1 | 2.4 | 2.8 | 3.0 | 3.7 | 3.8 | 4.3 | 4.8 | 5.3 | 5.6 | 5.9 | 5.9 |
| 46-55 | 5.7 | 2.5 | 3.0 | 3.4 | 4.0 | 4.4 | 5.3 | 5.4 | 6.2 | 6.9 | 7.6 | 8.2 | 8.7 | 8.8 |
| 56-65 | 7.0 | 2.9 | 3.6 | 4.0 | 4.6 | 5.1 | 6.3 | 6.4 | 7.3 | 8.0 | 8.8 | 9.5 | 10.2 | 10.5 |
| ≥66 | 8.0 | 3.3 | 4.2 | 4.8 | 5.6 | 6.2 | 7.4 | 7.7 | 8.6 | 9.1 | 9.9 | 10.6 | 11.3 | 11.5 |
| County status | ||||||||||||||
| Rural | 5.8 | 2.3 | 2.8 | 3.2 | 3.8 | 4.2 | 5.5 | 5.3 | 6.4 | 6.9 | 7.7 | 8.3 | 9.0 | 9.1 |
| Urban | 4.6 | 1.9 | 2.3 | 2.7 | 3.1 | 3.5 | 4.1 | 4.4 | 5.0 | 5.5 | 6.1 | 6.6 | 7.1 | 7.5 |
| County non-Hispanic White population | ||||||||||||||
| Quartile 1 (least) | 4.6 | 1.9 | 2.3 | 2.6 | 3.0 | 3.4 | 4.0 | 4.2 | 4.9 | 5.4 | 6.0 | 6.5 | 7.1 | 7.4 |
| Quartile 2 | 4.7 | 1.9 | 2.4 | 2.7 | 3.2 | 3.6 | 4.4 | 4.5 | 5.2 | 5.7 | 6.3 | 6.8 | 7.3 | 7.6 |
| Quartile 3 | 5.0 | 2.1 | 2.6 | 2.9 | 3.4 | 3.8 | 4.8 | 4.9 | 5.6 | 6.1 | 6.8 | 7.4 | 8.0 | 8.1 |
| Quartile 4 (most) | 6.2 | 2.4 | 3.1 | 3.4 | 4.0 | 4.5 | 6.0 | 5.8 | 6.9 | 7.8 | 8.5 | 9.1 | 9.8 | 9.6 |
| County poverty level | ||||||||||||||
| Quartile 1 (lowest) | 4.2 | 1.8 | 2.2 | 2.5 | 2.9 | 3.1 | 3.7 | 3.9 | 4.5 | 5.0 | 5.5 | 6.1 | 6.6 | 6.9 |
| Quartile 2 | 4.7 | 1.9 | 2.4 | 2.8 | 3.2 | 3.5 | 4.2 | 4.4 | 5.1 | 5.6 | 6.1 | 6.7 | 7.2 | 7.4 |
| Quartile 3 | 4.9 | 2.0 | 2.5 | 2.8 | 3.3 | 3.7 | 4.4 | 4.6 | 5.3 | 5.8 | 6.5 | 7.0 | 7.7 | 8.1 |
| Quartile 4 (highest) | 5.5 | 2.2 | 2.8 | 3.2 | 3.6 | 3.9 | 4.9 | 5.0 | 6.1 | 6.6 | 7.4 | 8.3 | 8.8 | 8.9 |
Abbreviation: OACG, overlapping opioid analgesic and gabapentin episodes.
Discussion
Despite gabapentin’s questionable effectiveness in pain management, OACG prescribing has increased, with a potential associated increased risk of all-cause and drug-related hospitalizations. Pain specialists were the most frequent OACG prescribers. Differences between specialties may be exacerbated by cases in which gabapentin may have modest impact (eg, chronic and/or neuropathic pain), by the complexity of cases overall, or because opioid prescribing restrictions more severely affect pain management strategies for complex cases. Prescribing patterns for OACG were similar to those for female patients, patients 66 years or older, and counties with high poverty levels, rural populations, and predominantly non-Hispanic White populations, suggesting that increased OACG prescribing may therefore be an unintentional consequence of opioid prescribing restrictions. Better understanding factors associated with these trends, and to what extent they may be mitigated or exacerbated by prescribing policies and/or physician education, will facilitate efforts to address this increasingly common and potentially dangerous clinical practice. Limitations of this study include observing dispensed not written prescriptions, data limited to retail pharmacies, and lacking information on patient clinical status.
eMethods 1. Data Sources, Variables, and Analysis
eMethods 2. Methodological Limitations
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Associated Data
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Supplementary Materials
eMethods 1. Data Sources, Variables, and Analysis
eMethods 2. Methodological Limitations