Factors Associated With Point-of-Care Treatment Decisions for Hidradenitis Suppurativa | Dermatology | JAMA Dermatology | JAMA Network
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Figure.  Inclusion and Exclusion Criteria and Sex Composition of the Hidradenitis Suppurativa (HS) Cohort
Inclusion and Exclusion Criteria and Sex Composition of the Hidradenitis Suppurativa (HS) Cohort

ICD-9 indicates International Classification of Diseases, Ninth Revision.

Table 1.  Demographic Characteristics of the Hidradenitis Suppurativa Treatment Cohort
Demographic Characteristics of the Hidradenitis Suppurativa Treatment Cohort
Table 2.  Frequency of Treatment Categories for the Hidradenitis Suppurativa Cohort
Frequency of Treatment Categories for the Hidradenitis Suppurativa Cohort
Table 3.  Associations With Receipt of Treatment Among Patients With Hidradenitis Suppurativa
Associations With Receipt of Treatment Among Patients With Hidradenitis Suppurativa
Table 4.  Associations With Escalation of Treatment Among Patients With Hidradenitis Suppurativa
Associations With Escalation of Treatment Among Patients With Hidradenitis Suppurativa
1.
Wolkenstein  P, Loundou  A, Barrau  K, Auquier  P, Revuz  J; Quality of Life Group of the French Society of Dermatology.  Quality of life impairment in hidradenitis suppurativa: a study of 61 cases.  J Am Acad Dermatol. 2007;56(4):621-623.PubMedGoogle ScholarCrossref
2.
Matusiak  L, Bieniek  A, Szepietowski  JC.  Psychophysical aspects of hidradenitis suppurativa.  Acta Derm Venereol. 2010;90(3):264-268.PubMedGoogle ScholarCrossref
3.
Esmann  S, Jemec  GB.  Psychosocial impact of hidradenitis suppurativa: a qualitative study.  Acta Derm Venereol. 2011;91(3):328-332.PubMedGoogle ScholarCrossref
4.
Sartorius  K, Emtestam  L, Jemec  GB, Lapins  J.  Objective scoring of hidradenitis suppurativa reflecting the role of tobacco smoking and obesity.  Br J Dermatol. 2009;161(4):831-839.PubMedGoogle ScholarCrossref
5.
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.PubMedGoogle ScholarCrossref
6.
Canoui-Poitrine  F, Revuz  JE, Wolkenstein  P,  et al.  Clinical characteristics of a series of 302 French patients with hidradenitis suppurativa, with an analysis of factors associated with disease severity.  J Am Acad Dermatol. 2009;61(1):51-57.PubMedGoogle ScholarCrossref
7.
Matusiak  L, Bieniek  A, Szepietowski  JC.  Hidradenitis suppurativa and associated factors: still unsolved problems.  J Am Acad Dermatol. 2009;61(2):362-365.PubMedGoogle ScholarCrossref
8.
Vazquez  BG, Alikhan  A, Weaver  AL, Wetter  DA, Davis  MD.  Incidence of hidradenitis suppurativa and associated factors: a population-based study of Olmsted County, Minnesota.  J Invest Dermatol. 2013;133(1):97-103.PubMedGoogle ScholarCrossref
9.
Kirby  JS, Miller  JJ, Adams  DR, Leslie  D.  Health care utilization patterns and costs for patients with hidradenitis suppurativa.  JAMA Dermatol. 2014;150(9):937-944.PubMedGoogle ScholarCrossref
Original Investigation
May 2016

Factors Associated With Point-of-Care Treatment Decisions for Hidradenitis Suppurativa

Author Affiliations
  • 1Department of Dermatology, Hofstra North Shore–LIJ School of Medicine, North Shore-LIJ Health System, Hempstead, New York
  • 2Boston University School of Medicine, Boston, Massachusetts
JAMA Dermatol. 2016;152(5):553-557. doi:10.1001/jamadermatol.2015.4593
Abstract

Importance  Studies evaluating factors associated with disease severity in hidradenitis suppurativa (HS) are limited, and the existing data are controversial. It is also unclear whether severity assessed by HS scoring methods correlate with partnered decision-making on treatment strategies, and thus the clinical relevance of these severity assessments is unknown.

Objective  To assess factors associated with disease severity as measured by point-of-care decisions on receipt or escalation of treatment for HS.

Design, Setting, and Participants  The retrospective cohort comprised 437 patients with HS ages 18 to 64 years at enrollment with at least 5 monitoring periods of 3 months’ duration. The study was performed at an academic medical center.

Main Outcomes and Measures  Receipt of treatment and treatment escalation.

Results  The average monitoring time of patients with HS was 4.2 person-years. The frequency of patients with HS with no treatment decreased over the monitoring period, while the frequency for receipt of treatment increased. Care by a dermatologist (odds ratio [OR], 6.7; 95% CI, 5.2-8.6) provided the strongest predictor of having received treatment for HS, and it was also associated with increased odds of escalating treatment (OR, 3.0; 95% CI, 2.4-3.7). Tobacco smoking was associated with treatment escalation (OR, 1.4; 95% CI, 1.1-1.7) over time, whereas obesity was not associated with treatment or escalation. The likelihood of receiving (OR, 1.4; 95% CI, 1.2-1.8) or escalating treatment (OR, 1.2; 95% CI, 1.0-1.4) was increased between ages 18 and 39 years. Male sex was not associated with treatment escalation.

Conclusions and Relevance  Clinician type, tobacco smoking, and age may be important clinical factors that patients and clinicians may consider in developing partnered short- and long-term treatment strategies. Obesity and sex do not seem to influence treatment decisions for HS.

Introduction

Hidradenitis suppurativa (HS) is a potentially debilitating chronic inflammatory disease that has an impact on several quality-of-life domains.1-3 Its inherent unpredictability, both with respect to course of disease and response to treatment, poses considerable challenges for patients and physicians alike. Studies evaluating predictors of disease severity in HS are limited, and the existing data are controversial. Observed differences may reflect the heterogenous nature of the disease. Moreover, use of different scoring methodologies, not all of which have been validated, may contribute to the variance in presence or strength of associations, and this approach has also made comparative analyses more difficult. It is also not known whether HS scoring methods correlate with patients’ own assessment of their disease, and the influence of these severity instruments on partnered decision-making on treatments is unknown. The purpose of this study was to assess factors associated with disease severity as measured by point-of-care decisions on receipt or escalation of treatment for HS.

Methods

This was a retrospective cohort study approved by the institutional review board of the Boston University School of Medicine. The HS cohort was established at Boston University Medical Center and 6 affiliated community health centers whose catchment area is composed of 8 of Boston’s 18 neighborhoods.

There were 624 patients identified with 2 or more International Classification of Diseases, Ninth Revision (ICD-9), codes of 705.83 corresponding to HS between 2003 and 2013. Patients who were 18 to 64 years old at enrollment with at least 5 monitoring periods of 3 months’ duration each were included in the analyses. We found 427 patients meeting inclusion criteria (Figure). This cohort was validated by random medical record review of 55 cases which yielded a positive predictive value of 83.6% (95% CI, 70.7%-91.8%) using the case definition adopted by the Second International Conference on Hidradenitis Suppurativa; March 5, 2009; San Francisco, California.

Self-reported demographic information, tobacco smoking status, body mass index (BMI, calculated as weight in kilograms divided by height in meters squared), and highest category of treatment for HS were evaluated for each patient in 3-month time periods. The initial 3-month period was used to establish baseline smoking, obesity, and treatment status. Smoking status and BMI values were interpolated between periods in which no status was assessed. Smoking status was dichotomized as ever and never smokers. Obesity was defined as a calculated BMI of 30 or greater. In addition, we validated tobacco smoking and obesity in the cohort with separate regression analyses using diagnosis of respiratory disease (odds ratio [OR], 2.1; 95% CI, 1.1-4.2) and hypertension (OR, 2.2; 95% CI, 1.5-3.1), respectively, as outcomes. Treatments for HS were categorized as follows: 0, no treatment; 1, topical anti-inflammatory or topical antibiotic regimens; 2, oral antibiotics; 3, oral retinoid; 4, immunomodulating agent; and 5, surgical management, excluding incision and drainage.

We used χ2 tests to compare dichotomous variables that were reported as frequency possessing the trait. We constructed univariate and multivariate conditional logistic regression models using complete case series analysis to estimate odds of associated outcomes. Odds ratios, 95% CIs, and P values are reported. We used an a priori statistical significance level of 0.05. SAS statistical software was used to analyze the data (version 9.3; SAS Institute Inc).

Results

Patients with HS were monitored for a total of 6439 time periods, which equated to 1610 person-years for the analysis. The average monitoring time was 16.7 periods, or 4.2 person-years. Demographic and clinical characteristics for the HS cohort are outlined in Table 1. The mean age of the HS treatment cohort was 39.4 years. The HS treatment cohort was composed mostly of women (74%) and was predominantly nonwhite (85%) patients. At the time of enrollment, less than half (45%) of these patients had engaged a dermatologist in their care. The frequency of ever being a tobacco smoker or ever being obese was 65% and 73%, respectively. Over the 4.2 person-years monitoring period, the frequency of patients with HS receiving no treatment reduced significantly, whereas the frequency of all treatment types increased significantly (Table 2).

The likelihood of receipt and escalation of treatment among patients with HS is described in Table 3 and Table 4, respectively. In adjusted analysis, engaging a dermatologist (OR, 6.7; 95% CI, 5.2-8.6) provided the strongest predictor of having received treatment for HS, and it was also associated with increased odds of having escalated treatment (OR, 3.0; 95% CI, 2.4-3.7). While tobacco smoking had no association with receipt of treatment, it was associated with treatment escalation (OR, 1.4; 95% CI, 1.1-1.7). Obesity had no association with receipt or escalation of treatment.

Male sex was not associated with receipt or escalation of treatment. The likelihood of receiving (OR, 1.4; 95% CI, 1.2-1.8) or escalating treatment (OR, 1.2; 95% CI, 1.0-1.4) was increased between ages 18 to 39 years, compared with ages 40 to 64 years. Patients who self-identified as nonwhite (OR, 0.66; 95% CI, 0.46-0.94) were less likely to receive treatment, although race was not associated with treatment escalation. Having subsidized insurance was associated with an increased odds of receiving treatment (OR, 1.7; 95% CI, 1.5-2.1) as well as treatment escalation (OR, 1.2; 95% CI, 1.0-1.4). Number of physician visits was also associated with receipt and escalation of treatment. Greater number of visits increased the odds of receipt and escalation of treatment. Number of follow-up periods in the analysis had no association with receipt or escalation of treatment.

Discussion

During the study period, the frequency of patients with HS receiving no treatment decreased, while the frequency of their receiving any form of treatment increased. This may suggest that the natural course of disease involves increasing severity over time, prompting patients to seek treatment. Another explanation may be that patients frustrated with the course of even stable disease are troubled enough to pursue some form of treatment. Less than half of the patients in our cohort had engaged a dermatologist; however, this relationship was associated with the greatest likelihood of receiving treatment for HS. Moreover, care by a dermatologist also provided an increased likelihood that treatment for HS was escalated over time. Given that most patients with HS require some form of treatment, or in many instances advancement of treatment, quality of care and outcomes in these patients may be improved with early recognition of HS and referral to dermatology.

While tobacco smoking had no greater influence on receipt of treatment among patients with HS, it was associated with treatment escalation. Tobacco smoking may either limit the effectiveness of treatment or lead to worsening of disease over time, both of which may require an escalation in treatment. The influence of tobacco smoking on treatment has not been explored previously. To date, the association between HS severity and tobacco smoking has been shown only through assessment via disparate scoring instruments, and the outcomes are controversial. In a Scandinavian cohort of 251 patients, tobacco smokers had a significantly higher median modified HS score compared with nonsmokers.4 In a Dutch study, smoking pack-years was only modestly associated with HS severity as measured by the Hurley Stage.5 French, Polish, and Olmstead County cohorts reported no significant association observed between tobacco smoking and HS severity, as assessed by Sartorius score or Hurley stage, in adjusted or multivariate analyses.6-8

We observed no greater influence of obesity on either receipt or escalation of treatment among patients with HS. To our knowledge, the influence of obesity on point-of-care management has not been explored previously. Other observational studies have characterized the controversial relationship between obesity and HS severity as assessed by disparate scoring instruments. Increased BMI was independently associated with an increased median modified HS score in the Scandinavian cohort,4 and an increased Sartorius score in the French cohort.6 The Dutch study also showed a modest association between BMI and HS severity as measured by the Hurley stage.5 However, no association was observed between BMI and Hurley stage among incident cases of HS in the Olmstead County cohort,8 or among a smaller group of patients in a Polish cohort.7

With limited evidence to guide treatment, and given that efficacy of treatment approaches have generally been suboptimal, dermatologists may adopt counseling on smoking cessation and weight loss as part of the therapeutic strategy. Overall, it important to recognize that disease or disease severity associations for HS with tobacco smoking and obesity are modest, remain controversial, and that no causal links have been established to date.

Secondary findings in this study may also relevant in developing short- and long-term treatment strategies. Patients with HS ages 18 to 30 years were more likely to receive and escalate treatment compared with those were 40 to 64 years old. Younger patients may be more likely to seek out treatment and be more aggressive in escalating treatment given the significant impact on quality of life associated with HS. However, this observation also may reflect onset and course of disease in HS, for which activity and severity seem most significant prior to the fourth decade. The HS literature suggests men have greater disease severity, as assessed by HS scoring instruments.5,6 However, our data indicate that an increase in scores among men may result in no greater likelihood of receipt or escalation of treatment. The increased likelihood of receiving and escalating treatment among of patients with HS with subsidized insurance may be reflective of the statewide mandate for health insurance which was commensurate with the establishment of the HS cohort. It is unclear why nonwhites were less likely to receive treatment, although this observation may be more reflective of societal or care disparities rather than differences in disease severity among demographic groups. Receipt and escalation of treatment was also associated with a greater number of physician visits which likely reflects complexity of care related to treatment and perhaps to comorbidities among patients with HS. High frequency of emergency department and inpatient use by these patients is also documented.9

Our data have limitations that warrant caution when interpreting the results. Our cohort is derived from multiple community-based and academic hospitals within a single institution. The institution’s race and ethnicity data used in the analysis are self-reported but are not yet structured according to the 2010 US Census Bureau classification for people of Hispanic ethnicity. Although the cohort is highly diversified, it is unclear if patients with HS are representative of those in other parts of the United States or in other countries. As with other studies using a retrospective observational methodology, we could not account for all confounders, nor can the interpretation of the regression analyses be singular.

Conclusions

We have observed course of disease in HS to be progressive. We have identified clinical factors that patients and clinicians may consider in developing partnered short- and long-term treatment strategies. We have also identified factors, namely obesity and male sex, which do not seem to additionally influence treatment of HS.

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Article Information

Corresponding Author: Amit Garg, MD, Department of Dermatology, Hofstra NSLIJ School of Medicine, North Shore-LIJ Health System, 1554 Northern Blvd, Second Floor, Manhasset, NY 11030 (amgarg@nshs.edu).

Accepted for Publication: September 30, 2015.

Published Online: February 3, 2016. doi:10.1001/jamadermatol.2015.4593.

Author Contributions: Drs Garg and Lam 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.

Study concept and design: Garg, Besen, Legler.

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

Drafting of the manuscript: Garg, Besen, Legler.

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

Statistical analysis: Garg, Legler.

Administrative, technical, or material support: Besen.

Study supervision: Garg, Lam.

Conflict of Interest Disclosures: None reported.

References
1.
Wolkenstein  P, Loundou  A, Barrau  K, Auquier  P, Revuz  J; Quality of Life Group of the French Society of Dermatology.  Quality of life impairment in hidradenitis suppurativa: a study of 61 cases.  J Am Acad Dermatol. 2007;56(4):621-623.PubMedGoogle ScholarCrossref
2.
Matusiak  L, Bieniek  A, Szepietowski  JC.  Psychophysical aspects of hidradenitis suppurativa.  Acta Derm Venereol. 2010;90(3):264-268.PubMedGoogle ScholarCrossref
3.
Esmann  S, Jemec  GB.  Psychosocial impact of hidradenitis suppurativa: a qualitative study.  Acta Derm Venereol. 2011;91(3):328-332.PubMedGoogle ScholarCrossref
4.
Sartorius  K, Emtestam  L, Jemec  GB, Lapins  J.  Objective scoring of hidradenitis suppurativa reflecting the role of tobacco smoking and obesity.  Br J Dermatol. 2009;161(4):831-839.PubMedGoogle ScholarCrossref
5.
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.PubMedGoogle ScholarCrossref
6.
Canoui-Poitrine  F, Revuz  JE, Wolkenstein  P,  et al.  Clinical characteristics of a series of 302 French patients with hidradenitis suppurativa, with an analysis of factors associated with disease severity.  J Am Acad Dermatol. 2009;61(1):51-57.PubMedGoogle ScholarCrossref
7.
Matusiak  L, Bieniek  A, Szepietowski  JC.  Hidradenitis suppurativa and associated factors: still unsolved problems.  J Am Acad Dermatol. 2009;61(2):362-365.PubMedGoogle ScholarCrossref
8.
Vazquez  BG, Alikhan  A, Weaver  AL, Wetter  DA, Davis  MD.  Incidence of hidradenitis suppurativa and associated factors: a population-based study of Olmsted County, Minnesota.  J Invest Dermatol. 2013;133(1):97-103.PubMedGoogle ScholarCrossref
9.
Kirby  JS, Miller  JJ, Adams  DR, Leslie  D.  Health care utilization patterns and costs for patients with hidradenitis suppurativa.  JAMA Dermatol. 2014;150(9):937-944.PubMedGoogle ScholarCrossref
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