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Comparative Overall Comorbidity Burden Among Patients With Hidradenitis Suppurativa

Educational Objective
To understand the comorbidity burden of hidradenitis suppurativa and compare it with psoriasis.
1 Credit CME
Key Points

Question  What is the overall burden of comorbid disease in patients with hidradenitis suppurativa?

Findings  In this cross-sectional study of 3818 patients in each of 3 matched cohorts, patients with hidradenitis suppurativa had a mean Charlson Comorbidity Index score of 1.95, which was significantly higher than mean CCI scores of age-, sex-, and race-matched cohorts of patients with psoriasis (Charlson Comorbidity Index score, 1.47) and a control group (Charlson Comorbidity Index score, 0.95).

Meaning  The overall comorbidity burden in patients with hidradenitis suppurativa has implications for mortality risk and resource use, and it may warrant multidisciplinary implementation of routine screening measures.

Abstract

Importance  The overall comorbidity burden among patients with hidradenitis suppurativa (HS) has not been systematically evaluated.

Objectives  To investigate the standardized overall comorbidity burden among patients with HS and to compare it with the comorbidity burden in patients with psoriasis and a control group.

Design, Setting, and Participants  A cross-sectional analysis was conducted of 5306 patients with HS, 14 037 patients with psoriasis, and 1 733 810 controls identified using electronic health records data from October 1, 2013, through October 1, 2018.

Main Outcome and Measure  The primary outcome was the mean Charlson Comorbidity Index (CCI) score.

Results  Each matched cohort had 3818 patients (2789 women and 1029 men; mean [SD] age, 45.7 [15.0]). Before matching, the overall mean (SD) CCI score was highest among the psoriasis cohort (2.33 [3.13]), followed by the HS cohort (1.80 [2.79]) and control cohort (1.26 [2.35]). In matched analyses, the overall mean (SD) CCI score was highest among the HS cohort (1.95 [2.96]), followed by the psoriasis cohort (1.47 [2.43]; P < .001) and control cohort (0.95 [1.99]; P < .001) patients. A total of 516 patients with HS (13.5%) had an overall mean CCI score of 5 or greater. Mean CCI score was highest for patients with HS across all sex, race, and age groups. The most common comorbidities among patients with HS were chronic pulmonary disease (1540 [40.3%]), diabetes with chronic complications (365 [9.6%]), diabetes without chronic complications (927 [24.3%]), and mild liver disease (455 [11.9%]). Patients with HS with a CCI score of 5 or greater had 4.97 (95% CI, 1.49-16.63) times the adjusted risk of 5-year mortality compared with patients with HS with a CCI score of zero.

Conclusions and Relevance  Patients with HS have a higher overall comorbidity burden compared with patients with psoriasis and a control group. A significant proportion of patients with HS have CCI scores of 5 or greater, which are associated with increased mortality. This degree of comorbidity burden may warrant multidisciplinary implementation of routine screening measures.

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CME Disclosure Statement: Unless noted, all individuals in control of content reported no relevant financial relationships. If applicable, all relevant financial relationships have been mitigated.

Article Information

Accepted for Publication: December 22, 2018.

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: April 17, 2019. doi:10.1001/jamadermatol.2019.0164

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: Strunk, Garg.

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

Drafting of the manuscript: Reddy, Garg.

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

Statistical analysis: Strunk, Garg.

Obtained funding: Garg.

Administrative, technical, or material support: Reddy.

Supervision: Garg.

Conflict of Interest Disclosures: Dr Garg reported serving as a consultant to AbbVie, Pfizer, Janssen, and Asana Biosciences; receiving honoraria from AbbVie, Pfizer, Janssen, and Asana Biosciences; and receiving research grants from AbbVie, UCB, and the National Psoriasis Foundation. No other disclosures were reported.

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

Role of the Funder/Sponsor: The funding source 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.

References
1.
Jemec  GB.  Clinical practice. Hidradenitis suppurativa.  N Engl J Med. 2012;366(2):158-164. doi:10.1056/NEJMcp1014163PubMedGoogle ScholarCrossref
2.
von der Werth  JM, Jemec  GB.  Morbidity in patients with hidradenitis suppurativa.  Br J Dermatol. 2001;144(4):809-813. doi:10.1046/j.1365-2133.2001.04137.xPubMedGoogle ScholarCrossref
3.
Garg  A, Birabaharan  M, Strunk  A.  Prevalence of type 2 diabetes mellitus among patients with hidradenitis suppurativa in the United States.  J Am Acad Dermatol. 2018;79(1):71-76. doi:10.1016/j.jaad.2018.01.014PubMedGoogle ScholarCrossref
4.
Garg  A, Hundal  J, Strunk  A.  Overall and subgroup prevalence of Crohn disease among patients with hidradenitis suppurativa: a population-based analysis in the United States.  JAMA Dermatol. 2018;154(7):814-818. doi:10.1001/jamadermatol.2018.0878PubMedGoogle ScholarCrossref
5.
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
6.
Garg  A, Neuren  E, Strunk  A.  Hidradenitis suppurativa is associated with polycystic ovarian syndrome: a population-based analysis in the United States.  J Invest Dermatol. 2018;138(6):1288-1292. doi:10.1016/j.jid.2018.01.009PubMedGoogle ScholarCrossref
7.
Wertenteil  S, Strunk  A, Garg  A.  Incidence of obstructive sleep apnoea among patients with hidradenitis suppurativa: a retrospective population-based cohort analysis.  Br J Dermatol. 2018;179(6):1398-1399. doi:10.1111/bjd.16931PubMedGoogle ScholarCrossref
8.
Egeberg  A, Gislason  GH, Hansen  PR.  Risk of major adverse cardiovascular events and all-cause mortality in patients with hidradenitis suppurativa.  JAMA Dermatol. 2016;152(4):429-434. doi:10.1001/jamadermatol.2015.6264PubMedGoogle ScholarCrossref
9.
Boehncke  WH.  Systemic inflammation and cardiovascular comorbidity in psoriasis patients: causes and consequences.  Front Immunol. 2018;9(9):579-591. doi:10.3389/fimmu.2018.00579PubMedGoogle ScholarCrossref
10.
IBM Watson Health. The data curation process: Watson Health informatics—overview of mapping, standardization, and indexing. https://www.ibm.com/downloads/cas/JBNOXQK4. Accessed October 10, 2018.
11.
US National Library of Medicine. SNOMED CT. http://www.nlm.nih.gov/research/umls/Snomed/snomed_main.html. Accessed October 10, 2018.
12.
Nelson  SJ, Zeng  K, Kilbourne  J, Powell  T, Moore  R.  Normalized names for clinical drugs: RxNorm at 6 years.  J Am Med Inform Assoc. 2011;18(4):441-448. doi:10.1136/amiajnl-2011-000116PubMedGoogle ScholarCrossref
13.
McDonald  CJ, Huff  SM, Suico  JG,  et al.  LOINC, a universal standard for identifying laboratory observations: a 5-year update.  Clin Chem. 2003;49(4):624-633. doi:10.1373/49.4.624PubMedGoogle ScholarCrossref
14.
Shen  JJ, Wan  TT, Perlin  JB.  An exploration of the complex relationship of socioecologic factors in the treatment and outcomes of acute myocardial infarction in disadvantaged populations.  Health Serv Res. 2001;36(4):711-732.PubMedGoogle Scholar
15.
Foraker  RE, Rose  KM, Whitsel  EA, Suchindran  CM, Wood  JL, Rosamond  WD.  Neighborhood socioeconomic status, Medicaid coverage and medical management of myocardial infarction: atherosclerosis risk in communities (ARIC) community surveillance.  BMC Public Health. 2010;10:632. doi:10.1186/1471-2458-10-632PubMedGoogle ScholarCrossref
16.
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
17.
Asgari  MM, Wu  JJ, Gelfand  JM,  et al.  Validity of diagnostic codes and prevalence of psoriasis and psoriatic arthritis in a managed care population, 1996-2009.  Pharmacoepidemiol Drug Saf. 2013;22(8):842-849. doi:10.1002/pds.3447PubMedGoogle ScholarCrossref
18.
Löfvendahl  S, Theander  E, Svensson  Å, Carlsson  KS, Englund  M, Petersson  IF.  Validity of diagnostic codes and prevalence of physician-diagnosed psoriasis and psoriatic arthritis in southern Sweden—a population-based register study.  PLoS One. 2014;9(5):e98024. doi:10.1371/journal.pone.0098024PubMedGoogle ScholarCrossref
19.
Charlson  ME, Pompei  P, Ales  KL, MacKenzie  CR.  A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.  J Chronic Dis. 1987;40(5):373-383. doi:10.1016/0021-9681(87)90171-8PubMedGoogle ScholarCrossref
20.
Quan  H, Li  B, Saunders  LD,  et al; IMECCHI Investigators.  Assessing validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions in a unique dually coded database.  Health Serv Res. 2008;43(4):1424-1441. doi:10.1111/j.1475-6773.2007.00822.xPubMedGoogle ScholarCrossref
21.
Thygesen  SK, Christiansen  CF, Christensen  S, Lash  TL, Sørensen  HT.  The predictive value of ICD-10 diagnostic coding used to assess Charlson Comorbidity Index conditions in the population-based Danish National Registry of Patients.  BMC Med Res Methodol. 2011;11:83. doi:10.1186/1471-2288-11-83PubMedGoogle ScholarCrossref
22.
Sharabiani  MT, Aylin  P, Bottle  A.  Systematic review of comorbidity indices for administrative data.  Med Care. 2012;50(12):1109-1118. doi:10.1097/MLR.0b013e31825f64d0PubMedGoogle ScholarCrossref
23.
Charlson  M, Szatrowski  TP, Peterson  J, Gold  J.  Validation of a combined comorbidity index.  J Clin Epidemiol. 1994;47(11):1245-1251. doi:10.1016/0895-4356(94)90129-5PubMedGoogle ScholarCrossref
24.
Khan  NF, Perera  R, Harper  S, Rose  PW.  Adaptation and validation of the Charlson Index for Read/OXMIS coded databases.  BMC Fam Pract. 2010;11:1. doi:10.1186/1471-2296-11-1PubMedGoogle ScholarCrossref
25.
Selim  AJ, Berlowitz  DR, Fincke  G,  et al.  Risk-adjusted mortality rates as a potential outcome indicator for outpatient quality assessments.  Med Care. 2002;40(3):237-245. doi:10.1097/00005650-200203000-00007PubMedGoogle ScholarCrossref
26.
Schneeweiss  S, Wang  PS, Avorn  J, Maclure  M, Levin  R, Glynn  RJ.  Consistency of performance ranking of comorbidity adjustment scores in Canadian and US utilization data.  J Gen Intern Med. 2004;19(5, pt 1):444-450. doi:10.1111/j.1525-1497.2004.30109.xPubMedGoogle ScholarCrossref
27.
Guzzo  TJ, Dluzniewski  P, Orosco  R, Platz  EA, Partin  AW, Han  M.  Prediction of mortality after radical prostatectomy by Charlson Comorbidity Index.  Urology. 2010;76(3):553-557. doi:10.1016/j.urology.2010.02.069PubMedGoogle ScholarCrossref
28.
Murray  SB, Bates  DW, Ngo  L, Ufberg  JW, Shapiro  NI.  Charlson Index is associated with one-year mortality in emergency department patients with suspected infection.  Acad Emerg Med. 2006;13(5):530-536. doi:10.1197/j.aem.2005.11.084PubMedGoogle ScholarCrossref
29.
Stavem  K, Hoel  H, Skjaker  SA, Haagensen  R.  Charlson Comorbidity Index derived from chart review or administrative data: agreement and prediction of mortality in intensive care patients.  Clin Epidemiol. 2017;9:311-320. doi:10.2147/CLEP.S133624PubMedGoogle ScholarCrossref
30.
Lalani  S, Pope  J, de Leon  F, Peschken  C; Members of CaNIOS/1000 Faces of Lupus.  Clinical features and prognosis of late-onset systemic lupus erythematosus: results from the 1000 Faces of Lupus Study.  J Rheumatol. 2010;37(1):38-44. doi:10.3899/jrheum.080957PubMedGoogle ScholarCrossref
31.
Linos  E, Fiorentino  D, Lingala  B, Krishnan  E, Chung  L.  Atherosclerotic cardiovascular disease and dermatomyositis: an analysis of the Nationwide Inpatient Sample survey.  Arthritis Res Ther. 2013;15(1):R7. doi:10.1186/ar4135PubMedGoogle ScholarCrossref
32.
Durcan  L, Wilson  F, Conway  R, Cunnane  G, O’Shea  FD.  Increased body mass index in ankylosing spondylitis is associated with greater burden of symptoms and poor perceptions of the benefits of exercise.  J Rheumatol. 2012;39(12):2310-2314. doi:10.3899/jrheum.120595PubMedGoogle ScholarCrossref
33.
Azuaga-Piñango  AB, Castellanos-Moreira  R, Rodriguez-Garcia  SC,  et al.  AB0332 Comorbidities prevalence and Charlson Index in a cohort of patients with rheumatoid arthritis.  Ann Rheum Dis. 2018;77(suppl 2):1341. doi:10.1136/annrheumdis-2018-eular.3216Google Scholar
34.
Charlson  ME, Charlson  RE, Peterson  JC, Marinopoulos  SS, Briggs  WM, Hollenberg  JP.  The Charlson Comorbidity Index is adapted to predict costs of chronic disease in primary care patients.  J Clin Epidemiol. 2008;61(12):1234-1240. doi:10.1016/j.jclinepi.2008.01.006PubMedGoogle ScholarCrossref
35.
Charlson  M, Wells  MT, Ullman  R, King  F, Shmukler  C.  The Charlson Comorbidity Index can be used prospectively to identify patients who will incur high future costs.  PLoS One. 2014;9(12):e112479. doi:10.1371/journal.pone.0112479PubMedGoogle ScholarCrossref
36.
Shalom  G, Babaev  M, Freud  T,  et al.  Demographic and health care service utilization by 4417 patients with hidradenitis suppurativa.  J Am Acad Dermatol. 2017;77(6):1047-1052.e2. doi:10.1016/j.jaad.2017.10.001PubMedGoogle ScholarCrossref
37.
Garg  A, Kirby  JS, Lavian  J, Lin  G, Strunk  A.  Sex- and age-adjusted population analysis of prevalence estimates for hidradenitis suppurativa in the United States.  JAMA Dermatol. 2017;153(8):760-764. doi:10.1001/jamadermatol.2017.0201PubMedGoogle ScholarCrossref
38.
Cunningham  TJ, Croft  JB, Liu  Y, Lu  H, Eke  PI, Giles  WH.  Vital signs: racial disparities in age-specific mortality among blacks or African Americans—United States, 1999-2015.  MMWR Morb Mortal Wkly Rep. 2017;66(17):444-456. doi:10.15585/mmwr.mm6617e1PubMedGoogle ScholarCrossref
39.
Schlapbach  C, Hänni  T, Yawalkar  N, Hunger  RE.  Expression of the IL-23/Th17 pathway in lesions of hidradenitis suppurativa.  J Am Acad Dermatol. 2011;65(4):790-798. doi:10.1016/j.jaad.2010.07.010PubMedGoogle ScholarCrossref
40.
van der Zee  HH, de Ruiter  L, van den Broecke  DG, Dik  WA, Laman  JD, Prens  EP.  Elevated levels of tumour necrosis factor (TNF)-α, interleukin (IL)-1β and IL-10 in hidradenitis suppurativa skin: a rationale for targeting TNF-α and IL-1β.  Br J Dermatol. 2011;164(6):1292-1298. doi:10.1111/j.1365-2133.2011.10254.xPubMedGoogle ScholarCrossref
41.
Bechara  FG, Sand  M, Skrygan  M, Kreuter  A, Altmeyer  P, Gambichler  T.  Acne inversa: evaluating antimicrobial peptides and proteins.  Ann Dermatol. 2012;24(4):393-397. doi:10.5021/ad.2012.24.4.393PubMedGoogle ScholarCrossref
42.
Kelly  G, Hughes  R, McGarry  T,  et al.  Dysregulated cytokine expression in lesional and nonlesional skin in hidradenitis suppurativa.  Br J Dermatol. 2015;173(6):1431-1439. doi:10.1111/bjd.14075PubMedGoogle ScholarCrossref
43.
Wolk  K, Warszawska  K, Hoeflich  C,  et al.  Deficiency of IL-22 contributes to a chronic inflammatory disease: pathogenetic mechanisms in acne inversa.  J Immunol. 2011;186(2):1228-1239. doi:10.4049/jimmunol.0903907PubMedGoogle ScholarCrossref
44.
Hotz  C, Boniotto  M, Guguin  A,  et al.  Intrinsic defect in keratinocyte function leads to inflammation in hidradenitis suppurativa.  J Invest Dermatol. 2016;136(9):1768-1780. doi:10.1016/j.jid.2016.04.036PubMedGoogle ScholarCrossref
45.
Matusiak  L, Bieniek  A, Szepietowski  JC.  Increased serum tumour necrosis factor-α in hidradenitis suppurativa patients: is there a basis for treatment with anti-tumour necrosis factor-α agents?  Acta Derm Venereol. 2009;89(6):601-603. doi:10.2340/00015555-0749PubMedGoogle ScholarCrossref
46.
Matusiak  Ł, Szczęch  J, Bieniek  A, Nowicka-Suszko  D, Szepietowski  JC.  Increased interleukin (IL)-17 serum levels in patients with hidradenitis suppurativa: implications for treatment with anti–IL-17 agents.  J Am Acad Dermatol. 2017;76(4):670-675. doi:10.1016/j.jaad.2016.10.042PubMedGoogle ScholarCrossref
47.
Xu  H, Xiao  X, He  Y,  et al.  Increased serum interleukin-6 levels in patients with hidradenitis suppurativa.  Postepy Dermatol Alergol. 2017;34(1):82-84. doi:10.5114/ada.2017.65626PubMedGoogle ScholarCrossref
48.
Jiménez-Gallo  D, de la Varga-Martínez  R, Ossorio-García  L, Albarrán-Planelles  C, Rodríguez  C, Linares-Barrios  M.  The clinical significance of increased serum proinflammatory cytokines, C-reactive protein, and erythrocyte sedimentation rate in patients with hidradenitis suppurativa.  Mediators Inflamm. 2017;2017:2450401. doi:10.1155/2017/2450401PubMedGoogle ScholarCrossref
49.
Onderdijk  AJ, van der Zee  HH, Esmann  S,  et al.  Depression in patients with hidradenitis suppurativa.  J Eur Acad Dermatol Venereol. 2013;27(4):473-478. doi:10.1111/j.1468-3083.2012.04468.xPubMedGoogle ScholarCrossref
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