Key Points
Question
What is the incidence of long-term opioid use among previously opioid-naive patients with hidradenitis suppurativa, and does it differ from that of patients without the condition?
Findings
In this cohort study of 22 277 patients with hidradenitis suppurativa, overall crude 1-year incidence of long-term opioid use was twice (0.33%) that among control patients (0.14%). The risk of long-term opioid use was 53% greater among patients with hidradenitis suppurativa after controlling for relevant confounders.
Meaning
These results suggest that patients with hidradenitis suppurativa may benefit from periodic assessment of pain and screening for opioid misuse.
This cohort study compares overall and subgroup incidence of long-term opioid use in a population of opioid-naive patients with hidradenitis suppurativa and controls from US electronic health record data.
Abstract
Importance
Risk of long-term opioid use among patients with hidradenitis suppurativa (HS), who experience pain that substantially impairs quality of life, is unknown to date.
Objective
To compare overall and subgroup incidence of long-term opioid use in a population of opioid-naive patients with HS and control patients.
Design, Setting, and Participants
This retrospective cohort study was based on a demographically heterogeneous population-based sample of more than 56 million unique patients from January 1, 2008, through December 10, 2018. Patients with HS (n = 22 277) and controls (n = 828 832) were identified using electronic health records data. Data were analyzed from December 13, 2018, through January 28, 2019.
Main Outcomes and Measures
The primary outcome was incident long-term opioid use.
Results
Among the 22 277 patients with HS, mean (SD) age was 40.8 (14.6) years, 16 912 (75.9%) were women, and 13 190 (59.2%) were white. Crude 1-year incidence of long-term opioid use among opioid-naive patients with HS was 0.33% (74 of 22 277), compared with 0.14% (1168 of 828 832) among controls (P < .001). In adjusted analysis, patients with HS had 1.53 (95% CI, 1.20-1.95; P < .001) times the odds of new long-term opioid use compared with controls. Among patients with HS, advancing age (odds ratio [OR], 1.02 per 1-year increase; 95% CI, 1.00-1.03; P = .05), ever smoking (OR, 3.64; 95% CI, 2.06-6.41; P < .001), history of depression (OR, 1.97; 95% CI, 1.21-3.19; P = .006), and baseline Charlson comorbidity index score (OR, 1.15 per 1-point increase; 95% CI, 1.03-1.29; P = .01) were associated with higher odds of long-term opioid use. Among patients with HS and long-term opioid use, 4 of 74 (5.4%) were diagnosed with opioid use disorder during the study period. The most frequent schedule II opioid prescriptions included oxycodone hydrochloride (55 of 74 patients [74.3%]), hydrocodone bitartrate (44 [59.5%]), hydromorphone hydrochloride (16 [21.6%]), morphine sulfate (13 [17.6%]), and fentanyl citrate (6 [8.1%]). Tramadol hydrochloride (32 [43.2%]) represented the most frequent non–schedule II prescription. Disciplines prescribing the most opioids to patients with HS included primary care (398 [72.8%]), anesthesiology/pain management (48 [8.8%]), gastroenterology (25 [4.6%]), surgery (23 [4.2%]), and emergency medicine (10 [1.8%]).
Conclusions and Relevance
In this study, patients with HS were at higher risk for long-term opioid use. These results suggest that periodic assessment of pain and screening for long-term opioid use may be warranted, particularly among patients who are older, who smoke tobacco, or who have depression and other medical comorbidities.
Introduction
Acute and chronic pain as well as disease-related impairments in quality of life may influence initiation and long-term use of opioids among patients with hidradenitis suppurativa (HS). In a global survey including more than 1900 patients with HS, HS-related pain during the past week was described as moderate or higher in 61.4% of cases. In 4.5% of cases, patients described the pain as worst possible. Only 9% of patients with HS described no recent pain.1 Pain has been observed to be more strongly associated with impaired quality of life in HS than disease severity.2 In an international Delphi process to define a core outcome set for HS clinical trials, patients and health care professionals identified pain as the most important symptom to measure, and pain was assigned as a core domain.3
Given the devastating physical, emotional, and psychological effects of pain in HS, patients may be at greater risk for long-term opioid use. The purpose of the present investigation was to compare the overall and subgroup incidence of long-term opioid use in a large population of patients with HS and control patients in the United States and to determine which clinical characteristics are most closely associated with long-term opioid use among patients with HS.
Methods
Patient Population
This retrospective cohort study used a multiple health system data analytics and research platform (Explorys) developed by IBM Corporation, Watson Health.4 Clinical information from electronic medical records, laboratories, practice management systems, and claims systems was matched using the single set of Unified Medical Language System ontologies to create longitudinal records for unique patients. Data are standardized and curated according to common controlled vocabularies and classifications systems, including International Classification of Diseases (ICD), Systemized Nomenclature of Medicine—Clinical Terms (SNOMEDCT),5 Logical Observation Identifiers Names and Codes (LOINC),6 and RxNorm.7 At present, the database encompasses 27 participating integrated health care organizations. More than 56 million unique lives, representing approximately 17% of the population across all 4 census regions of the United States, are captured. Patients with all types of insurance as well as those who are self-pay are represented. This study was approved by the human subjects committee at the Feinstein Institute of Medical Research at Northwell Health, which waived the need for informed consent for use of deidentified data. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.
This study was limited to patients 18 years or older with active status in the database for at least 3 consecutive calendar years from January 1, 2008, through December 10, 2018. A random date during the second calendar year was assigned as the index date for each patient.8 To identify an opioid-naive population, we excluded patients who received an opioid prescription for pain, addiction, or overdose in the year before the index date. We also excluded those with diagnosis of opioid use disorder (OUD) on or before the index date as well as those with a cancer diagnosis other than nonmelanoma skin cancer at any point before or during the study period. Finally, we excluded patients with missing data on age, sex, or race/ethnicity or with missing information for the primary exposure, outcome, or covariates.
Patients with HS were identified using at least 1 code from the International Classification of Diseases, Ninth Revision (ICD-9; 705.83) or diagnosis code from the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10; L73.2). In a validation study, Strunk et al9 observed a positive predictive value of 79.3% and an accuracy of 90% for diagnosis of HS using this algorithm. The primary outcome of the analysis was incidence of long-term opioid use, defined as at least 10 prescriptions within the 1-year follow-up period after the index date, where at least 2 of the prescriptions had start dates longer than 90 days apart.10 We excluded opioids in cough and cold preparations, including products containing antitussives, decongestants, antihistamines, and expectorants. Injectable and intravenous opioids were also excluded, as were medications used solely for the treatment of OUD and opioid overdose. This definition is based on similar methods that have been used in prior studies evaluating long-term opioid use.8,11 Opioids were identified using National Drug Codes12 and SNOMEDCT terms corresponding to opioid and opiate. Comorbidities, including depression, alcohol abuse, substance abuse, and the individual disease components of the Charlson comorbidity index, were based on diagnoses that occurred on or before a patient’s index date.
Statistical Analysis
Data were analyzed from December 13, 2018, through January 28, 2019. Baseline covariates were summarized using means, SDs, frequencies, and percentages. We calculated crude incidence of long-term opioid use in a 1-year period for HS and control cohorts and for patient subgroups. Risk of long-term opioid use was compared between patients with and without HS using an adjusted odds ratio (OR) derived from multivariable logistic regression, controlling for age, sex, race, calendar year, smoking status (ever or never), depression, alcohol abuse, substance abuse, and Charlson comorbidity index score. Interactions between each demographic or clinical covariate and HS were tested individually by including an interaction term between HS status and the covariate of interest in separate logistic regression models. In a secondary analysis, we performed a separate multivariable logistic regression only within the HS cohort to identify factors associated with long-term opioid use among these patients.
Patterns of opioid use were summarized for patients with HS who initiated long-term opioid use during the study period. Opioid prescriptions were classified according to drug component and Drug Enforcement Agency schedule. The Drug Enforcement Agency classifies opioids into 5 schedules based on the benefits of medical use vs the drug’s abuse potential. Only schedule II to V drugs have medical uses, with schedule II drugs having the highest abuse potential.13 We calculated the percentage of patients with HS and long-term opioid use who had at least 1 prescription for each type of drug. We determined the percentage of total opioid prescriptions attributed to health care professional specialties. Finally, we estimated the incidence of OUD diagnosis, which was defined as at least 2 ICD-9 or ICD-10 diagnosis codes for opioid abuse or dependence or OUD occurring during or after the 1-year follow-up period.14 Statistical significance was evaluated at the level of 2-sided α = .05. All analyses were performed using R, version 3.3.1 (R Foundation for Statistical Computing).
Results
We identified 22 277 patients with HS and 828 832 controls meeting eligibility criteria, the demographic and clinical characteristics for whom are described in Table 1. Patients with HS had a mean (SD) age of 40.8 (14.6) years, consisted of 16 912 women (75.9%) and 5365 men (24.1%), and were mostly white (13 190 [59.2%]). Black patients constituted 7349 (33.0%) of the HS cohort.
Table 1. Demographic and Clinical Characteristics.
| Variable | Patient Group | |
|---|---|---|
| HS (n = 22 277) | Control (n = 828 832) | |
| Age, mean (SD), y | 40.8 (14.6) | 51.1 (18.1) |
| Sex, No. (%) | ||
| Male | 5365 (24.1) | 316 465 (38.2) |
| Female | 16 912 (75.9) | 512 367 (61.8) |
| Race/ethnicity | ||
| White | 13 190 (59.2) | 665 960 (80.3) |
| Black | 7349 (33.0) | 91 241 (11.0) |
| Other | 1738 (7.8) | 71 631 (8.6) |
| Ever smoked, No. (%) | 9678 (43.4) | 197 181 (23.8) |
| HS duration, mean (SD), y | 2.3 (2.8) | NA |
| Depression, No. (%) | 6275 (28.2) | 96 483 (11.6) |
| CCI score, mean (SD)a | 0.91 (1.46) | 0.56 (1.71) |
| Alcohol abuse, No. (%) | 528 (2.4) | 9195 (1.1) |
| Substance abuse, No. (%) | 650 (2.9) | 6439 (0.8) |
Abbreviations: CCI, Charlson comorbidity index; HS, hidradenitis suppurativa; NA, not applicable.
Scores range from 0 to 25, with higher scores indicating greater number of comorbidities.
Overall and subgroup-specific crude 1-year incidences of long-term opioid use are presented in Table 2. Overall crude 1-year incidence of long-term opioid use among opioid-naive patients with HS was 0.33% (74 of 22 277) compared with 0.14% (1168 of 828 832) among controls. In unadjusted analysis, patients with HS had 2.36 (95% CI, 1.87-2.99; P < .001) times higher odds of incident long-term opioid use compared with controls. In the fully adjusted model, patients with HS had 1.53 (95% CI, 1.20-1.95; P < .001) times the odds of incident long-term opioid use compared with controls. The odds of long-term opioid use were also significantly higher for patients with HS than controls in several specific demographic and clinical subgroups. However, the relative strength of these associations did not differ significantly within the subgroups of age, sex, race/ethnicity, tobacco use, depression, alcohol use, nonopioid substance abuse, and Charlson comorbidity index score (Table 2).
Table 2. Incidence of Long-term Opioid Use Among Patients With HS and Controls.
| Subgroup | 1-Year Incidence of Long-term Opioid Use, No. of Cases/Total (%) | HS vs Control Group, OR (95% CI)a | ||
|---|---|---|---|---|
| Patients With HS (n = 22 277) | Control (n = 828 832) | Unadjusted | Adjustedb | |
| Overall | 74/22 277 (0.33) | 1168/828 832 (0.14) | 2.36 (1.87-2.99) | 1.53 (1.20-1.95) |
| Age, y | ||||
| 18-29 | 10/5950 (0.17) | 79/127 802 (0.06) | 2.72 (1.41-5.26) | 1.87 (0.96-3.61) |
| 30-39 | 14/5310 (0.26) | 140/112 142 (0.12) | 2.11 (1.22-3.67) | 1.24 (0.71-2.16) |
| 40-49 | 17/4668 (0.36) | 202/136 911 (0.15) | 2.47 (1.51-4.06) | 1.35 (0.82-2.22) |
| 50-59 | 19/3774 (0.50) | 283/165 693 (0.17) | 2.96 (1.86-4.71) | 1.51 (0.94-2.42) |
| 60-69 | 12/1853 (0.65) | 243/142 791 (0.17) | 3.82 (2.14-6.84) | 1.98 (1.10-3.56) |
| 70-79 | 1/566 (0.18) | 126/86 541 (0.15) | 1.21 (0.17-8.70) | 0.65 (0.09-4.68) |
| 80-89 | 1/156 (0.64) | 95/56 952 (0.17) | 3.86 (0.53-27.87) | 2.39 (0.33-17.46) |
| Sex | ||||
| Male | 23/5365 (0.43) | 451/316 465 (0.14) | 3.02 (1.98-4.59) | 2.04 (1.33-3.11) |
| Female | 51/16 912 (0.30) | 717/512 367 (0.14) | 2.16 (1.62-2.87) | 1.37 (1.02-1.83) |
| Race | ||||
| White | 52/13 190 (0.39) | 928/665 960 (0.14) | 2.84 (2.14-3.75) | 1.81 (1.36-2.41) |
| Black | 20/7349 (0.27) | 153/91 241 (0.17) | 1.62 (1.02-2.59) | 1.19 (0.74-1.90) |
| Other | 2/1738 (0.12) | 87/71 631 (0.12) | 0.95 (0.23-3.85) | 0.62 (0.15-2.54) |
| Tobacco smoking status | ||||
| Smoker | 58/9678 (0.60) | 673/197 181 (0.34) | 1.76 (1.35-2.30) | 1.53 (1.16-2.02) |
| Nonsmoker | 16/12 599 (0.13) | 495/631 651 (0.08) | 1.62 (0.99-2.67) | 1.51 (0.91-2.49) |
| Depression | ||||
| Yes | 36/6275 (0.57) | 287/96 483 (0.30) | 1.93 (1.37-2.74) | 1.56 (1.10-2.22) |
| No | 38/16 002 (0.24) | 881/732 349 (0.12) | 1.98 (1.43-2.74) | 1.50 (1.08-2.09) |
| Alcohol abuse | ||||
| Yes | 4/528 (0.76) | 40/9195 (0.44) | 1.75 (0.62-4.90) | 1.38 (0.49-3.90) |
| No | 70/21 749 (0.32) | 1128/819 637 (0.14) | 2.34 (1.84-2.98) | 1.54 (1.20-1.98) |
| Nonopioid substance abusec | ||||
| Yes | 4/650 (0.62) | 35/6439 (0.54) | 1.13 (0.40-3.20) | 0.94 (0.33-2.65) |
| No | 70/21 627 (0.32) | 1133/822 393 (0.14) | 2.35 (1.85-3.00) | 1.58 (1.23-2.03) |
| Charlson comorbidity index scored | ||||
| 0 | 20/11 736 (0.17) | 586/578 406 (0.10) | 1.68 (1.08-2.63) | 1.21 (0.77-1.89) |
| 1-2 | 39/8303 (0.47) | 372/198 603 (0.19) | 2.51 (1.81-3.50) | 1.90 (1.35-2.66) |
| 3-4 | 8/1414 (0.57) | 121/35 316 (0.34) | 1.66 (0.81-3.39) | 1.31 (0.64-2.70) |
| ≥5 | 7/824 (0.85) | 89/16 507 (0.54) | 1.58 (0.73-3.42) | 1.26 (0.58-2.75) |
Abbreviations: CCI, Charlson comorbidity index; HS, hidradenitis suppurativa; OR, odds ratio.
All ORs compare the odds of long-term opioid use between patients with HS and controls (reference). Odds ratios within subgroups were calculated based on separate models including interaction term(s) for HS status and the covariate of interest. All interaction terms between HS status and the other covariates were nonsignificant (P > .05).
Based on a logistic regression model controlling for age, sex, race, calendar year, smoking status, depression, alcohol abuse, nonopioid substance abuse, and Charlson comorbidity index.
Includes substance other than opioid, including sedative, hypnotic, anxiolytic, cocaine, cannabis, amphetamine, or hallucinogen.
Scores range from 0 to 25, with higher scores indicating greater number of comorbidities.
Factors associated with incident long-term opioid use among patients with HS are shown in Table 3. Among patients with HS, each additional year of age was associated with a 2% increase in the risk of long-term opioid use (OR, 1.02; 95% CI, 1.00-1.03; P = .05). Patients with HS who were ever tobacco smokers had 3.64 (95% CI, 2.06-6.41; P < .001) times the odds of long-term opioid use compared with patients with HS who never smoked. Patients with HS and depression had nearly twice (OR, 1.97; 95% CI, 1.21-3.19; P = .006) the odds of long-term opioid use compared with patients with HS without depression. Each additional 1-U increase in Charlson comorbidity index score was associated with a 15% (OR, 1.15; 95% CI, 1.03-1.29; P = .01) increase in risk of long-term opioid use among patients with HS. Sex, race/ethnicity, disease duration, established dermatologic care, alcohol abuse, and nonopioid substance abuse were not associated with increased risk of long-term opioid use among patients with HS.
Table 3. Factors Associated With Long-term Opioid Use Among Patients With HS.
| Variable | OR (95% CI) | P Valueb | |
|---|---|---|---|
| Unadjusted | Adjusteda | ||
| Age per 1-y increase | 1.03 (1.01-1.04) | 1.02 (1.00-1.03) | .05 |
| Sex | |||
| Male | 1.42 (0.87-2.33) | 1.21 (0.72-2.04) | .47 |
| Female | 1 [Reference] | 1 [Reference] | NA |
| Race | |||
| White | 1 [Reference] | 1 [Reference] | NA |
| Black | 0.69 (0.41-1.16) | 0.72 (0.42-1.24) | .24 |
| Other | 0.29 (0.07-1.20) | 0.35 (0.08-1.45) | .15 |
| Smoking status | |||
| Ever | 4.74 (2.72-8.25) | 3.64 (2.06-6.41) | <.001 |
| Never | 1 [Reference] | 1 [Reference] | NA |
| HS duration per 1-y increase | 0.99 (0.91-1.08) | 0.96 (0.88-1.05) | .34 |
| Depression | |||
| Yes | 2.42 (1.54-3.83) | 1.97 (1.21-3.19) | .006 |
| No | 1 [Reference] | 1 [Reference] | NA |
| Alcohol abuse diagnosis | |||
| Yes | 2.36 (0.86-6.50) | 1.11 (0.38-3.20) | .85 |
| No | 1 [Reference] | 1 [Reference] | NA |
| Nonopioid substance abuse diagnosisc | |||
| Yes | 1.91 (0.69-5.24) | 1.04 (0.36-3.02) | .94 |
| No | 1 [Reference] | 1 [Reference] | NA |
| Dermatology encounters (≥2) | |||
| Yes | 0.99 (0.46-2.17) | 1.10 (0.50-2.40) | .82 |
| No | 1 [Reference] | 1 [Reference] | NA |
| CCI score per 1-U increase | 1.26 (1.15-1.38) | 1.15 (1.03-1.29) | .01 |
Abbreviations: CCI, Charlson comorbidity index; HS, hidradenitis suppurativa; NA, not applicable; OR, odds ratio.
Based on a logistic regression model within the cohort of patients with HS, controlling for all of the above covariates as well as calendar year.
Calculated for adjusted OR.
Includes substance other than opioid, including sedative, hypnotic, anxiolytic, cocaine, cannabis, amphetamine, or hallucinogen.
Table 4 describes the percentage of patients with HS with long-term opioid use who had at least 1 prescription within each opioid type. Among 74 patients with long-term opioid use, 55 (74.3%) received a prescription containing oxycodone hydrochloride; 44 (59.5%), hydrocodone bitartrate; 16 (21.6%), hydromorphone hydrochloride; 13 (17.6%), morphine sulfate; 6 (8.1%), fentanyl citrate; and 5 (6.8%), meperidine hydrochloride. Long- or short-acting tramadol hydrochloride (32 [43.2%]) represented the most frequent non–schedule II prescription. Among the 547 opioid prescriptions that could be ascribed to a specific health care professional, the medical specialties that prescribed the most opioids for patients with HS included primary care (398 [72.8%]), anesthesiology/pain management (48 [8.8%]), gastroenterology (25 [4.6%]), surgery (23 [4.2%]), and emergency medicine (10 [1.8%]). The remaining opioid prescriptions with known specialist type (43 [7.9%]) were submitted by 21 other disciplines. The specialist type could not be determined for 448 of 995 prescriptions (45.0%). Among the 74 patients with HS and long-term opioid use, 4 (5.4%) had a new diagnosis of OUD.
Table 4. Long-term Opioid Use According to Type of Opioid Among Patients With HS.
| Type of Opioid Prescribed at Least Once | No. (%) of Patients With HS and Long-term Opioid Use (n = 74) |
|---|---|
| Schedule II | |
| Oxycodone hydrochloride | 55 (74.3) |
| Hydrocodone bitartrate | 44 (59.5) |
| Hydromorphone hydrochloride | 16 (21.6) |
| Morphine sulfate | 13 (17.6) |
| Fentanyl citrate | 6 (8.1) |
| Meperidine hydrochloride | 5 (6.8) |
| Methadone hydrochloride | 1 (1.4) |
| Codeine sulfate/codeine phosphate | 0 |
| Oxymorphone hydrochloride | 0 |
| Tapentadol hydrochloride | 0 |
| Levomethadyl acetate hydrochloride | 0 |
| Levorphanol tartrate | 0 |
| Nonschedule II | |
| Tramadol hydrochloride (Long and short acting) | 32 (43.2) |
| Codeine (≤90 mg per dosage unit) combination product | 7 (9.5) |
| Propoxyphene hydrochloride | 1 (1.4) |
| Buprenorphine hydrochloride | 0 |
| Butorphanol tartrate | 0 |
| Dihydrocodeine bitartrate combination product, 90 mg per dosage unit or less a | 0 |
| Pentazocine hydrochloride | 0 |
Abbreviation: HS, hidradenitis suppurativa.
Includes combinations of aspirin, caffeine, and dihydrocodeine bitartrate; acetaminophen, caffeine, and dihydrocodeine bitartrate; and dihydrocodeine bitartrate, acetyl-para-aminophenol, and caffeine.
Discussion
The prevalence of substance use disorder among patients with HS has been reported at 4%, double that of patients without HS.15 Among patients with HS and substance abuse, opioids accounted for one-third of the cases. In this analysis, we have identified a greater than 2-fold crude increase in the 1-year incidence of long-term opioid use among patients with HS compared with controls. Patients with HS had 53% greater risk of long-term opioid use than those without the disease after accounting for demographic and clinical covariates. Although modest in absolute value, the incidence of long-term opioid use among patients with HS was double that of the control population. We captured new cases of long-term opioid use, rather than prevalent cases, during a 1-year period, and we have also applied a strict definition of long-term opioid use. The incidence of long-term opioid use observed for patients with HS in our analysis is also comparable to the incidences observed among patients with newly diagnosed musculoskeletal pain (0.31%) and those undergoing various types of surgical procedures (0.12%-1.4%).8,11 These are populations for whom increased vigilance and monitoring for long-term opioid use have been recommended. This recommendation may indicate that the chronic nociceptive nature of pain in HS may be at least as likely to prompt patients to pursue and sustain opioid therapy as may the pain in inflammatory and mechanical arthritis or perioperatively. As such, our results suggest that similar monitoring may be warranted for patients with HS, particularly if other risk factors, such as smoking and depression, are present.
Although age, tobacco smoking, depression, and comorbidity burden were factors associated with incident long-term opioid use among patients with HS, sex, race, disease duration, established dermatologic care, alcohol abuse, and nonopioid substance abuse were not. Patients with HS who smoke cigarettes may have more severe disease16,17,18 and consequently more pain. Patients with depression are also observed to self-report higher levels of pain19 and are more likely to initiate opioid therapy.20 Nonetheless, the association between demographic and clinical factors with long-term opioid use among patients with HS is likely more complex and warrants further qualitative study. Of note, dermatologic care had no association with long-term opioid use. We speculate that patients with HS who had dermatology encounters may have more severe disease and could be at greater risk for long-term opioid use, but this association also needs further evaluation.
Oxycodone, hydrocodone, hydromorphone, morphine, fentanyl, meperidine, and tramadol represented the most frequent prescriptions for patients with HS and long-term use of opioids. These opioid medications are also the ones most commonly prescribed in the general population.21,22 Schedule II medications have high addiction potential.23 Approximately 8% of patients with HS and long-term use of opioids had used fentanyl, which has multiple times the potency of morphine and which was responsible for the greatest number of drug overdose deaths in 2016.24,25 Tramadol may have habit-forming potential and thus is Drug Enforcement Agency scheduled. However, in its oral form, tramadol is considered to have low to moderate potential for physical dependence, particularly among patients with no history of substance abuse.26
Pain control likely represents the most common reason for opioid initiation and long-term use. Patients have identified pain control as a fundamental unmet need in HS.1 Pain is also a major contributor to impairment in quality of life among patients with HS,2,3,27 which we speculate may further propagate opioid use. Opioids are frequently prescribed to treat chronic noncancer pain in the United States. However, a systematic review and meta-analysis of 96 randomized clinical trials involving more than 26 000 patients indicated that patients receiving opioids for chronic noncancer pain had modest improvements in pain and physical functioning, and these improvements were attenuated further over time.28 As such, the potential benefit of long-term opioid use in chronic noncancer pain appears not to outweigh the risk. In the absence of disease-specific pain management protocols, recommendations for pain control in HS follow the World Health Organization pain ladder and closely mirror clinical practice guidelines from the Centers for Disease Control and Prevention.29,30,31,32 Although no formal studies have evaluated the relative effectiveness and safety of opioids compared with nonsteroidal anti-inflammatory drugs in HS, opioids are not recommended as first-line treatments for nociceptive pain in HS.32
Prior studies have shown that opioid misuse is common among patients receiving long-term opioid therapy,33,34 and estimates for current opioid dependence are as high as 26% in this group.35 In our analysis, only 5.4% of patients with HS who developed long-term opioid use also received a diagnosis of OUD, suggesting that a significant proportion of these cases went undiagnosed. Although opioid medications for patients with HS and long-term opioid use were most frequently prescribed by primary care professionals, all physicians, including dermatologists, have an opportunity to identify patients with HS at risk. Although dermatologists may not be experts in recognizing signs of opioid misuse or addiction, validated, easy-to-implement, patient- or physician-directed instruments are available to effectively facilitate risk assessment as well as screening in the ambulatory setting36,37,38 (eTables 1-3 in the Supplement).
Limitations
This retrospective analysis has important limitations that warrant consideration. We could not directly attribute opioid prescription to disease-related pain among patients with HS. We could not assess the influence of disease severity on the strength of the association with long-term opioid use in this claims-based analysis. Results regarding source of opioid prescriptions should be interpreted with caution because health care professional type could not be determined for a significant percentage of the opioid prescriptions. Opioid dosage, supply, and refill information could not be incorporated into the analysis owing to missing data. We were unable to evaluate use of nonopioid pain medications or other therapies to address pain, which prevented comparison between these modalities and opioids for pain management. Data on potentially relevant covariates that are not collected during routine health care, such as socioeconomic status, were not available. Finally, we could not capture patients who did not seek care in health systems included in the database or who may have migrated out of the networks. Despite these limitations, this population-based analysis describes important data on the risk of long-term opioid use among patients with HS. Because the population sample is drawn from various health care settings across US census regions, this study overcomes some of the selection biases associated with tertiary single-center or multicenter investigations. Given the size and demographic heterogeneity of the HS cohort, we believe these results may be generalized to the US population seeking health care.
Conclusions
This study found that patients with HS were at higher risk of long-term opioid use compared with those without HS. Results suggest that patients with HS, particularly those who are older, who smoke, or who have depression and other medical comorbidities, may benefit from periodic screening for opioid use. We underscore herein that the findings in this study should not further stigmatize patients who have HS. Rather, our hope is that the medical community, including dermatologists, will further embrace and engage in an integrated care plan that comprehensively supports the needs of patients with HS, including pain management. We believe future directions in research should include evaluating the association between disease severity and risk of opioid use, the role of disease-modifying therapies in reducing opioid use, and the development of effective and appropriate multimodal pain management strategies for HS.
eTable 1. Diagnosis, Intractability, Risk Efficacy (DIRE) Score
eTable 2. Opioid Risk Tool
eTable 3. The Current Opioid Use Measure
eReferences.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eTable 1. Diagnosis, Intractability, Risk Efficacy (DIRE) Score
eTable 2. Opioid Risk Tool
eTable 3. The Current Opioid Use Measure
eReferences.