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Table 1.  
Demographic and Clinical Characteristics
Demographic and Clinical Characteristics
Table 2.  
Incidence of Long-term Opioid Use Among Patients With HS and Controls
Incidence of Long-term Opioid Use Among Patients With HS and Controls
Table 3.  
Factors Associated With Long-term Opioid Use Among Patients With HS
Factors Associated With Long-term Opioid Use Among Patients With HS
Table 4.  
Long-term Opioid Use According to Type of Opioid Among Patients With HS
Long-term Opioid Use According to Type of Opioid Among Patients With HS
1.
Garg  A, Neuren  E, Cha  D,  et al.  Evaluating unmet needs in hidradenitis suppurativa: results from the Global VOICE project  [published online July 3, 2019].  J Am Acad Dermatol. doi:10.1016/j.jaad.2019.06.1301PubMedGoogle Scholar
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Matusiak  Ł, Szczęch  J, Kaaz  K, Lelonek  E, Szepietowski  JC.  Clinical characteristics of pruritus and pain in patients with hidradenitis suppurativa.  Acta Derm Venereol. 2018;98(2):191-194. doi:10.2340/00015555-2815PubMedGoogle ScholarCrossref
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Thorlacius  L, Ingram  JR, Villumsen  B,  et al; Hidradenitis Suppurativa Core Outcomes Set International Collaboration (HISTORIC).  A core domain set for hidradenitis suppurativa trial outcomes: an international Delphi process.  Br J Dermatol. 2018;179(3):642-650. doi:10.1111/bjd.16672PubMedGoogle ScholarCrossref
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Strunk  A, Midura  M, Papagermanos  V, Alloo  A, Garg  A.  Validation of a case-finding algorithm for hidradenitis suppurativa using administrative coding from a clinical database.  Dermatology. 2017;233(1):53-57. doi:10.1159/000468148PubMedGoogle ScholarCrossref
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Moshfegh  J, George  SZ, Sun  E.  Risk and risk factors for chronic opioid use among opioid-naïve patients with newly diagnosed musculoskeletal pain in the neck, shoulder, knee, or low back.  Ann Intern Med. 2018;170(7):504-505. doi:10.7326/M18-2261PubMedGoogle ScholarCrossref
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Centers for Disease Control and Prevention. Opioid overdose: analyzing prescription data and morphine milligram equivalents (MME). Atlanta, GA: Centers for Disease Control and Prevention; 2018. https://www.cdc.gov/drugoverdose/resources/data.html. Updated April 10, 2019. Accessed July 14, 2019.
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US Department of Justice, Drug Enforcement Administration, Office of Diversion Control. Practioner’s manual: an informational outline of the Controlled Substances Act. https://www.deadiversion.usdoj.gov/pubs/manuals/pract/pract_manual012508.pdf. 2006 edition. Accessed July 14, 2019.
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Kim  HM, Smith  EG, Stano  CM,  et al.  Validation of key behaviourally based mental health diagnoses in administrative data: suicide attempt, alcohol abuse, illicit drug abuse and tobacco use.  BMC Health Serv Res. 2012;12:18. doi:10.1186/1472-6963-12-18PubMedGoogle ScholarCrossref
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Garg  A, Papagermanos  V, Midura  M, Strunk  A, Merson  J.  Opioid, alcohol, and cannabis misuse among patients with hidradenitis suppurativa: a population-based analysis in the United States.  J Am Acad Dermatol. 2018;79(3):495-500.e1. doi:10.1016/j.jaad.2018.02.053PubMedGoogle ScholarCrossref
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Garg  A, Besen  J, Legler  A, Lam  CS.  Factors associated with point-of-care treatment decisions for hidradenitis suppurativa.  JAMA Dermatol. 2016;152(5):553-557. doi:10.1001/jamadermatol.2015.4593PubMedGoogle ScholarCrossref
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Sartorius  K, Emtestam  L, Jemec  GBE, Lapins  J.  Objective scoring of hidradenitis suppurativa reflecting the role of tobacco smoking and obesity.  Br J Dermatol. 2009;161(4):831-839. doi:10.1111/j.1365-2133.2009.09198.xPubMedGoogle ScholarCrossref
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Schrader  AM, Deckers  IE, van der Zee  HH, Boer  J, Prens  EP.  Hidradenitis suppurativa: a retrospective study of 846 Dutch patients to identify factors associated with disease severity.  J Am Acad Dermatol. 2014;71(3):460-467. doi:10.1016/j.jaad.2014.04.001PubMedGoogle ScholarCrossref
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Bair  MJ, Robinson  RL, Katon  W, Kroenke  K.  Depression and pain comorbidity: a literature review.  Arch Intern Med. 2003;163(20):2433-2445. doi:10.1001/archinte.163.20.2433PubMedGoogle ScholarCrossref
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Sullivan  MD, Edlund  MJ, Zhang  L, Unützer  J, Wells  KB.  Association between mental health disorders, problem drug use, and regular prescription opioid use.  Arch Intern Med. 2006;166(19):2087-2093. doi:10.1001/archinte.166.19.2087PubMedGoogle ScholarCrossref
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Fuentes  AV, Pineda  MD, Venkata  KCN.  Comprehension of top 200 prescribed drugs in the US as a resource for pharmacy teaching, training and practice.  Pharmacy (Basel). 2018;6(2):E43. doi:10.3390/pharmacy6020043PubMedGoogle ScholarCrossref
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Sullivan  MD, Edlund  MJ, Fan  M, DeVries  A, Braden  J, Martin  BC.  Trends in use of opioids for non-cancer pain conditions 2000-2005 in commercial and Medicaid insurance plans: the TROUP study.  Pain. 2008;138(2):440-449. doi:10.1016/j.pain.2008.04.027PubMedGoogle ScholarCrossref
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Frenk  SM, Porter  K, Paulozzi  LJ. Prescription opioid analgesic use among adults: United States, 1999-2012. NCHS Data Brief. No.189. https://www.cdc.gov/nchs/data/databriefs/db189.pdf. Published February 2015. Accessed July 14, 2019.
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United States Environmental Protection Agency. Fact sheet for OSCs: fentanyl and fentanyl analogs, version 1.0. https://www.epa.gov/sites/production/files/2018-07/documents/fentanyl_fact_sheet_ver_7-26-18.pdf. Published May 22, 2018. Accessed July 14, 2019.
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Hedegaard  H, Bastian  BA, Trinidad  JP, Warner  M. Drugs most frequently involved in drug overdose deaths: United States, 2011-2016. National Vital Statistics Reports, Vol 67, No. 9. https://www.cdc.gov/nchs/data/nvsr/nvsr67/nvsr67_09-508.pdf. Published December 12, 2018. Accessed July 14, 2019.
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World Health Organization. Tramadol: update review report: agenda item 6.1. Expert Committee on Drug Dependence; Thirty-Sixth Meeting; Geneva, Switzerland. https://www.who.int/medicines/areas/quality_safety/6_1_Update.pdf. June 16-20, 2014. Accessed July 14, 2019.
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Ingram  JR, Abbott  R, Ghazavi  M,  et al.  The hidradenitis suppurativa priority setting partnership.  Br J Dermatol. 2014;171(6):1422-1427. doi:10.1111/bjd.13163PubMedGoogle ScholarCrossref
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Busse  JW, Wang  L, Kamaleldin  M,  et al.  Opioids for chronic noncancer pain: a systematic review and meta-analysis.  JAMA. 2018;320(23):2448-2460. doi:10.1001/jama.2018.18472PubMedGoogle ScholarCrossref
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Dowell  D, Haegerich  TM, Chou  R.  CDC guideline for prescribing opioids for chronic pain—United States, 2016.  MMWR Recomm Rep. 2016;65(1):1-49. doi:10.15585/mmwr.rr6501e1PubMedGoogle ScholarCrossref
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Zouboulis  CC, Desai  N, Emtestam  L,  et al.  European S1 guideline for the treatment of hidradenitis suppurativa/acne inversa.  J Eur Acad Dermatol Venereol. 2015;29(4):619-644. doi:10.1111/jdv.12966PubMedGoogle ScholarCrossref
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Horváth  B, Janse  IC, Sibbald  GR.  Pain management in patients with hidradenitis suppurativa.  J Am Acad Dermatol. 2015;73(5)(suppl 1):S47-S51. doi:10.1016/j.jaad.2015.07.046PubMedGoogle ScholarCrossref
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Grattan  A, Sullivan  MD, Saunders  KW, Campbell  CI, Von Korff  MR.  Depression and prescription opioid misuse among chronic opioid therapy recipients with no history of substance abuse.  Ann Fam Med. 2012;10(4):304-311. doi:10.1370/afm.1371PubMedGoogle ScholarCrossref
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Ives  TJ, Chelminski  PR, Hammett-Stabler  CA,  et al.  Predictors of opioid misuse in patients with chronic pain: a prospective cohort study.  BMC Health Serv Res. 2006;6:46. doi:10.1186/1472-6963-6-46PubMedGoogle ScholarCrossref
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Boscarino  JA, Rukstalis  M, Hoffman  SN,  et al.  Risk factors for drug dependence among out-patients on opioid therapy in a large US health-care system.  Addiction. 2010;105(10):1776-1782. doi:10.1111/j.1360-0443.2010.03052.xPubMedGoogle ScholarCrossref
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Webster  LR, Webster  RM.  Predicting aberrant behaviors in opioid-treated patients: preliminary validation of the Opioid Risk Tool.  Pain Med. 2005;6(6):432-442. doi:10.1111/j.1526-4637.2005.00072.xPubMedGoogle ScholarCrossref
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Belgrade  MJ, Schamber  CD, Lindgren  BR.  The DIRE score: predicting outcomes of opioid prescribing for chronic pain.  J Pain. 2006;7(9):671-681. doi:10.1016/j.jpain.2006.03.001PubMedGoogle ScholarCrossref
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Butler  SF, Budman  SH, Fernandez  KC,  et al.  Development and validation of the Current Opioid Misuse Measure.  Pain. 2007;130(1-2):144-156. doi:10.1016/j.pain.2007.01.014PubMedGoogle ScholarCrossref
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    Original Investigation
    September 11, 2019

    Incidence of Long-term Opioid Use Among Opioid-Naive Patients With Hidradenitis Suppurativa in the United States

    Author Affiliations
    • 1Department of Dermatology, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, New Hyde Park, New York
    • 2Department of Dermatology, Emory University School of Medicine, Atlanta, Georgia
    JAMA Dermatol. Published online September 11, 2019. doi:10.1001/jamadermatol.2019.2610
    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.

    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.

    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).

    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 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.

    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 disease16-18 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.29-32 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 setting36-38 (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.

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    Article Information

    Accepted for Publication: July 15, 2019.

    Corresponding Author: Amit Garg, MD, Department of Dermatology, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, 1991 Marcus Ave, Ste 300, New Hyde Park, NY 11042 (amgarg@northwell.edu).

    Published Online: September 11, 2019. doi:10.1001/jamadermatol.2019.2610

    Author Contributions: Mr Strunk and Dr Garg had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: All authors.

    Acquisition, analysis, or interpretation of data: All authors.

    Drafting of the manuscript: Reddy, Orenstein, Garg.

    Critical revision of the manuscript for important intellectual content: Orenstein, Strunk, Garg.

    Statistical analysis: Strunk.

    Obtained funding: Garg.

    Administrative, technical, or material support: Reddy.

    Supervision: Garg.

    Conflict of Interest Disclosures: Dr Orenstein reported receiving personal fees from Frontline Medical Communications and MedEd Consulting outside the submitted work. Dr Garg reported receiving grants and personal fees from from AbbVie and UCB during the conduct of the study, personal fees from Asana BioSciences, Pfizer Inc, Amgen, and Janssen Pharmaceutica, and grants from the National Psoriasis Foundation outside the submitted work. No other disclosures were reported.

    Funding/Support: This study was supported in part by an education grant from AbbVie (Dr Garg).

    Role of the Funder/Sponsor: The sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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