- Email: [email protected]
Hidradenitis Suppurativa Is Associated with Polycystic Ovary Syndrome: A Population-Based Analysis in the United States
Accepted Manuscript Hidradenitis suppurativa is associated with polycystic ovary syndrome: a populationbased analysis in the United States Amit Garg, MD, Erica Neuren, BA, Andrew Strunk, MA PII:
S0022-202X(18)30027-7
DOI:
10.1016/j.jid.2018.01.009
Reference:
JID 1257
To appear in:
The Journal of Investigative Dermatology
Received Date: 19 September 2017 Revised Date:
5 December 2017
Accepted Date: 4 January 2018
Please cite this article as: Garg A, Neuren E, Strunk A, Hidradenitis suppurativa is associated with polycystic ovary syndrome: a population-based analysis in the United States, The Journal of Investigative Dermatology (2018), doi: 10.1016/j.jid.2018.01.009. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Hidradenitis suppurativa is associated with polycystic ovary syndrome: a population-based analysis
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in the United States
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Short title:
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HS is associated with PCOS
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Amit Garg, MD, Erica Neuren, BA, Andrew Strunk, MA
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Department of Dermatology, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell
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New Hyde Park, New York, USA
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Correspondence: Amit Garg, MD, Department of Dermatology, 1991 Marcus Avenue, Suite 300, New
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Hyde Park, NY, 11042. Phone: 516-321-8543. Fax: 516-321-8516. Email: [email protected]
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ORCID ID for Amit Garg: 0000-0003-0886-6856
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Abbreviations: BMI, body mass index; HS, hidradenitis suppurativa; PCOS, polycystic ovary syndrome;
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US, United States
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ABSTRACT Polycystic ovary syndrome (PCOS) has been linked to hidradenitis suppurativa (HS). However, evidence establishing a relationship between the two conditions is limited. We sought to determine
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prevalence of PCOS among HS patients and the strength of the association. We performed a cross-
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sectional analysis involving 22,990 HS patients using clinical data from a multi-health system analytics
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platform (Explorys Inc., 2017) comprising over 50 million unique patients across all census regions of the
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United States. Prevalence of PCOS among patients with HS was 9.0%, compared to 2.9% in patients
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without HS (p<.0001). Likelihood of HS patients having PCOS was 2.14 [95% CI 2.04-2.24] times that of
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non-HS patients, and PCOS was associated with HS across all subgroups. Strength of the HS association
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with PCOS was similar to that of diabetes mellitus [OR 2.88, 95% CI 2.83-2.93] and obesity [OR 3.93,
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95% CI 3.87-3.99] with PCOS. Influence of disease severity on strength of association with PCOS could
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not be assessed, nor could an HS phenotype for patients also having PCOS. This analysis could not
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establish directionality of relationship, nor causal link. In conclusion, PCOS is associated with HS, and
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HS patients with symptoms or signs of androgen excess should be screened for PCOS.
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INTRODUCTION Hidradenitis suppurativa (HS) is an inflammatory disease involving the pilosebaceous unit which results in painful nodules and draining abscesses, and which results in formation of fistulas, sinus tracts
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and scarring, commonly affecting the axillae, breasts, groin, and perineum (Jemec, 2012). HS
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predominantly affects young adult women, and the incidence within this demographic appears to be rising
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in the United States (US) (Garg et al., 2017a; 2017b).
Polycystic ovary syndrome (PCOS), characterized by hyperandrogenism, irregular menses, and
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polycystic ovaries (Castro et al., 2015), is one of the most common endocrine and metabolic disorders in
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young women (Diamanti-Kandarakis et al., 1999; March et al., 2010). Comorbidity burden associated
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with PCOS is substantial and includes premature adrenarche (Rosenfield, 2007), oligo-ovulatory
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infertility (Kousta et al., 1999), as well as those which may overlap with HS such as obesity (Alvarez-
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Blasco et al., 2006; Ehrmann et al., 2006), diabetes mellitus (Peppard et al., 2001), and the metabolic
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syndrome (Ehrmann et al., 2006; Coviello et al., 2006; Miller et al., 2016). Given the overlap in demographics and co-morbidities, and since response to anti-androgen
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therapy has been observed in both conditions (Mortimer et al., 1986a; Kraft and Searles, 2007; Verdolini
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et al., 2013; Lee and Fischer, 2015; Nestler, 2008; Goodman et al., 2015), we sought to compare the
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prevalence of PCOS among patients with and without HS while controlling for potential confounders.
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RESULTS
We identified 22,990 female patients with HS. The prevalence of PCOS among female patients
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with HS was 9.0% (2,070/22,9900), compared to 2.9% (96,940/3,369,150 in the general population of
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patients without HS (p<.0001). (Table 1) Prevalence of PCOS was greatest among diabetic HS patients
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(17.2%), obese HS patients (11.0%), and among HS patients aged 30-39 (11.0%). (Figure 1)
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In unadjusted analysis, HS patients had 3.34 [95% CI 3.19-3.50] times the odds of having PCOS
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compared to non-HS patients. After controlling for age, race, smoking status, obesity, and type II diabetes
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mellitus, the odds of having PCOS remained 2.14 [95% CI 2.04-2.24) times as high in HS patients
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relative to non-HS patients. The strength of the HS association with PCOS was similar to that of diabetes
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mellitus [OR 2.88, 95% CI 2.83-2.93] and obesity [OR 3.93 95% CI 3.87-3.99] with PCOS. PCOS was
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associated with HS across all patient subgroups. (Figure 1) The strength of this relationship differed
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significantly according to age groups (interaction p <.0001), race (p = .0011), diabetes status (p = .02),
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and smoking status (p = .0003). The greatest relative difference in the odds of PCOS between those with
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and without HS was observed in patients aged 18-29 (OR 2.50, 95% CI 2.30-2.71), non-smokers (OR
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2.37, 95% CI 2.21-2.55), Caucasian patients (OR 2.26, 95% CI 2.14-2.40), and those without diabetes
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(OR 2.22, 95% CI 2.10-2.34).
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DISCUSSION
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The prevalence of PCOS among HS patients within a national population-based sample in the US
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has not previously been reported. In this study, we have observed a PCOS prevalence of 9.0% among HS
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patients. The prevalence of PCOS was greatest among HS patients who had diabetes mellitus, who were
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obese, and among young adults. HS patients had more than 3 times the crude prevalence of PCOS
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compared to non-HS patients. The association was somewhat attenuated after adjusting for common risk
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factors, such as obesity, diabetes, and smoking status. However, in adjusted analysis overall likelihood of
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having PCOS among patients with HS remained twice that compared to patients without HS. The
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association was present across all subgroups of HS patients. HS was associated with PCOS in both obese
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and non-obese patient subgroups. This suggests that the relationship between HS and PCOS exists
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independently of the influence of obesity.
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The relationship between PCOS and HS was previously evaluated in a single institution case
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series of 64 women with HS, in which the prevalence of PCOS was observed to be 12.5% (8/64).
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However, prevalence estimates were not compared to a matched population, and as such, there was no
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analysis on strength of association (Kraft and Searles, 2007). Among 1730 patients with HS in a second
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single institution analysis, the prevalence of PCOS was 4%, compared to only 0.17% in the matched
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control cohort. In multivariable analysis, patients with HS had more than 13 times the odds of having
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PCOS compared to those without HS (Shlyankevich et al., 2014).
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Signs of androgen excess, even in the absence of a diagnosis of PCOS, have been observed among women with HS. In two series, there were high frequencies of acne, hirsutism, irregular
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menstruation, and infertility noted (Mortimer et al., 1986b; Barth et al., 1996). In addition to the
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observation of clinical signs suggestive of androgen excess, the relationship between HS and
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hyperandrogenism was further supported by the observation of a high free androgen index in the context
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of low sex hormone binding globulin (SHBG) (Mortimer et al., 1986b). The analysis did not account for
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high body weights among HS patients, which could have been responsible for the low SHBG levels
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observed.
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When compared to age-matched controls however, women with HS do not appear have an
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increase in clinical signs of androgenization (Jemec, 1988). Moreover, other studies have refuted the
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initial observation that androgens may be elevated among patients with HS. In a case controlled series of
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66 women with HS, plasma androgen levels were not significantly different between HS subjects and
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controls matched for age, weight, and hisutism. Testosterone and dehydroepiandrosterone sulphate were
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normal in all patients with HS (Barth et al., 1996). These findings were largely consistent with another
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earlier study evaluating plasma androgens in women with HS (Harrison et al., 1988).
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Because HS patients appear to exhibit normal androgen levels, an enhanced peripheral conversion of androgens has been suggested. However, activity of peripheral androgen-converting enzymes in
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apocrine glands of the axillae in HS patients showed no differences when compared to controls (Barth and
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Kealey, 1991). Moreover, androgen and estrogen receptor expression within apocrine glands of lesion
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skin fail to show alterations compared to control samples (Buimer et al., 2015). Skin and adnexae may
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produce peptide and steroid hormones de novo (Slominski et al., 2013; Labrie et al., 2000; Paus et al.,
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2008; Zouboulis, 2000; Zouboulis et al., 2007), which may alter hormone-related homeostasis in HS
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patients and promote early hyperkeratinization and follicular plugging (Kamp et al., 2011).
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Modulation of end organ hormone-related homeostasis may account for the observed efficacy of
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therapies including metformin, spironolactone, and finasteride which may influence the androgen
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environment. In a retrospective series of 64 women with HS, metformin was shown to improve symptoms
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in 55%, compared to 26% of HS patients who received treatment with oral antibiotics (Kraft and Searles,
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2007). In another case series of 22 women and three men with HS who received treatment with metformin
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for 24 weeks, 18 showed substantial improvement in disease severity as measured by Sartorius score and
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quality of life as measured by the Dermatology Life Quality Index score (Verdolini et al., 2013). Among
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20 patients with HS, 17 (85%) responded within three months to anti-androgenic treatment with
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spironolactone 100mg daily. Complete suppression was achieved in 11/20 (55%). There was no
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relationship between the initial severity and response to treatment (Lee and Fischer, 2015). Finally, in a
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small case series involving seven HS patients, six (86%) showed significant clinical improvement on
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finasteride 5 mg daily. Two of those six patients experienced complete remission (Joseph et al., 2005).
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There are limits which warrant consideration when interpreting the results of this study. We could not capture patients who did not seek care in health systems included in the database. Although ICD
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codes for both HS and PCOS have relatively high positive predictive values, the use of administrative
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claims data is an imperfect standard for case identification. While this may result in misclassification bias,
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there is no evidence that the accuracy of a claim for PCOS would differ according to HS status (i.e.
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differential misclassification). Influence of disease severity on strength of association with PCOS could
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not be assessed, nor could an HS phenotype for patients also having PCOS. This analysis could not
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establish directionality of the relationship, nor a causal link. Despite these limitations, the present study
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describes important data describing the association between HS and PCOS. The prevalence and strength
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of association reported in this study is based on the largest and most ethnically diversified cohort of
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patients with HS worldwide, and this has also facilitated subgroup analyses which allow identification of
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groups at highest risk. Because the population sample is drawn from various health care settings across all
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US census regions, this study overcomes selection biases associated with tertiary single or multi-center
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investigations. We believe these results may be generalized to the US population.
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In conclusion, our results indicate that HS has a strong association with PCOS, and is similar to associations of obesity and diabetes mellitus with PCOS. HS patients with symptoms or signs of
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hyperandrogenism should be screened for PCOS. The role of androgens in HS and the potential benefit of
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anti-androgen therapy warrant further exploration.
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MATERIALS AND METHODS
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Data Sources and Study Population
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This was a cross sectional analysis using a multi-health system data analytics and research
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platform (Explorys) developed by International Business Machines (IBM) Corporation, Watson Health™
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(Explorys Inc., 2017). Clinical information from electronic medical records, laboratories, practice
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management systems, and claims systems is matched using the single set of Unified Medical Language
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System ontologies to create longitudinal records for unique patients. The data are standardized and
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curated according to common controlled vocabularies and classifications systems (SNOMED CT, 2017;
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Nelson et al., 2011; McDonald et al., 2003; Shen et al., 2001; Foraker et al., 2010). At present, the
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database encompasses 27 participating integrated healthcare organizations. Over 50 million unique lives,
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representing approximately 15% of the population across all four census regions of the United States, are
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captured. Patients with all types of insurance as well as those who are self-pay are represented. In order to
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maintain data confidentiality, Explorys provides population level counts rounded to the nearest 10, and
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reports counts between 1 and 9 as less than 10.
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The SNOMED-CT term ‘hidradenitis’ has one-to-one mapping to the ICD-9 code 705.83, and
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was used to identify patients with HS. In validating the case cohort, we observed a positive predictive
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value (PPV) of 79.3% and an accuracy of 90% for diagnosis of HS using a single ICD-9 code for HS
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(Strunk et al., 2017). This case identification method was previously validated by an independent group,
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and it was shown to have a positive predictive value of 77% (Shlyankevich et al., 2014). This method has
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also been used to establish disease burden in the United States (Garg et al., 2017a; 2017b). Patients with
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PCOS were identified by the ICD-9 code 256.4 which maps to the SNOMED-CT term “polycystic ovary
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syndrome”. This method was previously shown to have a PPV of 74% (Castro et al., 2015).
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Statistical Analysis
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The analysis was limited to female patients aged 18 years or older with an active status in the database within the past 3 years (November, 2014-November, 2017) who were not missing demographic
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data on age, gender, race, and body mass index (BMI). Age in years was recorded as a categorical
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variable within one of three groups: 18-29, 30-39, and 40-49. The race variable was dichotomized as
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white vs. nonwhite. BMI was dichotomized into obese (BMI > 30.0) vs. non-obese (BMI < 30.0). The
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SNOMED-CT terms ‘tobacco user’ (ICD-9 code 305.1) and ‘nicotine dependence’ (ICD-10 code F17.2)
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were used to identify active tobacco smokers. Individuals with no record of either of these terms were
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considered non-smokers. Study size was determined by the number of patients satisfying all eligibility
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criteria. Given the millions of patients who are active in the database, and tens of thousands of patients
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with HS, sample size calculations were not performed.
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We obtained population level counts of the number of patients with and without a diagnosis of PCOS for each combination of categorical explanatory variables (HS status, age, race, BMI status,
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diabetes mellitus status, and smoking status). We assessed crude associations between PCOS and each
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explanatory variable using separate univariable logistic regression models. Multivariable logistic
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regression was performed to evaluate the relationship between HS and PCOS while controlling for age,
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race, BMI status, diagnosis of diabetes mellitus, and smoking status). Differences in the association
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between HS and PCOS across patient subgroups were tested individually by including an interaction term
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for HS and the subgroup variable of interest in separate logistic regression models. Patients with any
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missing covariate data were excluded from the study sample, and thus a complete case analysis was used.
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In order to assess the potential impact of missing race and BMI data on our findings, we compared the
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crude prevalence of PCOS among female patients aged 18-49 with missing data in each exposure group.
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Although the crude prevalences were slightly lower for patients with missing data, PCOS remained more
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than four times as common in those with HS than those without HS (5.6% and 1.2%, respectively). All
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analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC). Human Subjects Committee
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review was waived since there are no identifiers associated with the data.
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CONFLICT OF INTEREST:
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Dr. Garg has served as an advisor for AbbVie and received honoraria. AbbVie has provided the
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corresponding author an unrestricted educational grant which has been used to support this study. The
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sponsor has had no role in the study design; in the collection, analysis and interpretation of the data; in the
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writing of the report; or in the decision to submit the manuscript for publication.
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None
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Table 1: Demographic characteristics. Non-HS Patients (n=3,369,150)
Polycystic ovarian syndrome
2,070 (9.0%)
96,940 (2.9%)
Age 18-29 30-39 40-49
7,565 (32.9%) 6,895 (30.0%) 8,530 (37.1%)
1,242,150 (36.9%) 1,108,930 (32.9%) 1,018,070 (30.2%)
Race White Non-white
12,950 (56.3%) 10,040 (43.7%)
2,489,910 (73.9%) 879,240 (26.1%)
Tobacco smoker Obese (BMI > 30.0) Diabetes mellitus
13,090 (56.9%) 17,280 (75.2%) 3,815 (16.6%)
1,033,320 (30.7%) 1,417,840 (42.1%) 208,220 (6.2%)
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Figure 1. Hidradenitis suppurativa.
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Description of overall and subgroup prevalences for polycystic ovarian syndrome among hidradenitis
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suppurativa patients, as well as the overall and subgroup odds of polycystic ovarian syndrome among
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patient with hidradenitis suppurativa.
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S0022-202X(18)30027-7
DOI:
10.1016/j.jid.2018.01.009
Reference:
JID 1257
To appear in:
The Journal of Investigative Dermatology
Received Date: 19 September 2017 Revised Date:
5 December 2017
Accepted Date: 4 January 2018
Please cite this article as: Garg A, Neuren E, Strunk A, Hidradenitis suppurativa is associated with polycystic ovary syndrome: a population-based analysis in the United States, The Journal of Investigative Dermatology (2018), doi: 10.1016/j.jid.2018.01.009. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Hidradenitis suppurativa is associated with polycystic ovary syndrome: a population-based analysis
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in the United States
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Short title:
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HS is associated with PCOS
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Amit Garg, MD, Erica Neuren, BA, Andrew Strunk, MA
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Department of Dermatology, Donald and Barbara Zucker School of Medicine at Hofstra/Northwell
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New Hyde Park, New York, USA
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Correspondence: Amit Garg, MD, Department of Dermatology, 1991 Marcus Avenue, Suite 300, New
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Hyde Park, NY, 11042. Phone: 516-321-8543. Fax: 516-321-8516. Email: [email protected]
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ORCID ID for Amit Garg: 0000-0003-0886-6856
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Abbreviations: BMI, body mass index; HS, hidradenitis suppurativa; PCOS, polycystic ovary syndrome;
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US, United States
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ABSTRACT Polycystic ovary syndrome (PCOS) has been linked to hidradenitis suppurativa (HS). However, evidence establishing a relationship between the two conditions is limited. We sought to determine
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prevalence of PCOS among HS patients and the strength of the association. We performed a cross-
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sectional analysis involving 22,990 HS patients using clinical data from a multi-health system analytics
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platform (Explorys Inc., 2017) comprising over 50 million unique patients across all census regions of the
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United States. Prevalence of PCOS among patients with HS was 9.0%, compared to 2.9% in patients
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without HS (p<.0001). Likelihood of HS patients having PCOS was 2.14 [95% CI 2.04-2.24] times that of
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non-HS patients, and PCOS was associated with HS across all subgroups. Strength of the HS association
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with PCOS was similar to that of diabetes mellitus [OR 2.88, 95% CI 2.83-2.93] and obesity [OR 3.93,
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95% CI 3.87-3.99] with PCOS. Influence of disease severity on strength of association with PCOS could
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not be assessed, nor could an HS phenotype for patients also having PCOS. This analysis could not
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establish directionality of relationship, nor causal link. In conclusion, PCOS is associated with HS, and
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HS patients with symptoms or signs of androgen excess should be screened for PCOS.
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INTRODUCTION Hidradenitis suppurativa (HS) is an inflammatory disease involving the pilosebaceous unit which results in painful nodules and draining abscesses, and which results in formation of fistulas, sinus tracts
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and scarring, commonly affecting the axillae, breasts, groin, and perineum (Jemec, 2012). HS
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predominantly affects young adult women, and the incidence within this demographic appears to be rising
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in the United States (US) (Garg et al., 2017a; 2017b).
Polycystic ovary syndrome (PCOS), characterized by hyperandrogenism, irregular menses, and
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polycystic ovaries (Castro et al., 2015), is one of the most common endocrine and metabolic disorders in
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young women (Diamanti-Kandarakis et al., 1999; March et al., 2010). Comorbidity burden associated
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with PCOS is substantial and includes premature adrenarche (Rosenfield, 2007), oligo-ovulatory
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infertility (Kousta et al., 1999), as well as those which may overlap with HS such as obesity (Alvarez-
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Blasco et al., 2006; Ehrmann et al., 2006), diabetes mellitus (Peppard et al., 2001), and the metabolic
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syndrome (Ehrmann et al., 2006; Coviello et al., 2006; Miller et al., 2016). Given the overlap in demographics and co-morbidities, and since response to anti-androgen
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therapy has been observed in both conditions (Mortimer et al., 1986a; Kraft and Searles, 2007; Verdolini
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et al., 2013; Lee and Fischer, 2015; Nestler, 2008; Goodman et al., 2015), we sought to compare the
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prevalence of PCOS among patients with and without HS while controlling for potential confounders.
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RESULTS
We identified 22,990 female patients with HS. The prevalence of PCOS among female patients
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with HS was 9.0% (2,070/22,9900), compared to 2.9% (96,940/3,369,150 in the general population of
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patients without HS (p<.0001). (Table 1) Prevalence of PCOS was greatest among diabetic HS patients
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(17.2%), obese HS patients (11.0%), and among HS patients aged 30-39 (11.0%). (Figure 1)
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In unadjusted analysis, HS patients had 3.34 [95% CI 3.19-3.50] times the odds of having PCOS
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compared to non-HS patients. After controlling for age, race, smoking status, obesity, and type II diabetes
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mellitus, the odds of having PCOS remained 2.14 [95% CI 2.04-2.24) times as high in HS patients
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relative to non-HS patients. The strength of the HS association with PCOS was similar to that of diabetes
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mellitus [OR 2.88, 95% CI 2.83-2.93] and obesity [OR 3.93 95% CI 3.87-3.99] with PCOS. PCOS was
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associated with HS across all patient subgroups. (Figure 1) The strength of this relationship differed
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significantly according to age groups (interaction p <.0001), race (p = .0011), diabetes status (p = .02),
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and smoking status (p = .0003). The greatest relative difference in the odds of PCOS between those with
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and without HS was observed in patients aged 18-29 (OR 2.50, 95% CI 2.30-2.71), non-smokers (OR
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2.37, 95% CI 2.21-2.55), Caucasian patients (OR 2.26, 95% CI 2.14-2.40), and those without diabetes
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(OR 2.22, 95% CI 2.10-2.34).
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DISCUSSION
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The prevalence of PCOS among HS patients within a national population-based sample in the US
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has not previously been reported. In this study, we have observed a PCOS prevalence of 9.0% among HS
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patients. The prevalence of PCOS was greatest among HS patients who had diabetes mellitus, who were
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obese, and among young adults. HS patients had more than 3 times the crude prevalence of PCOS
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compared to non-HS patients. The association was somewhat attenuated after adjusting for common risk
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factors, such as obesity, diabetes, and smoking status. However, in adjusted analysis overall likelihood of
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having PCOS among patients with HS remained twice that compared to patients without HS. The
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association was present across all subgroups of HS patients. HS was associated with PCOS in both obese
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and non-obese patient subgroups. This suggests that the relationship between HS and PCOS exists
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independently of the influence of obesity.
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The relationship between PCOS and HS was previously evaluated in a single institution case
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series of 64 women with HS, in which the prevalence of PCOS was observed to be 12.5% (8/64).
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However, prevalence estimates were not compared to a matched population, and as such, there was no
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analysis on strength of association (Kraft and Searles, 2007). Among 1730 patients with HS in a second
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single institution analysis, the prevalence of PCOS was 4%, compared to only 0.17% in the matched
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control cohort. In multivariable analysis, patients with HS had more than 13 times the odds of having
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PCOS compared to those without HS (Shlyankevich et al., 2014).
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Signs of androgen excess, even in the absence of a diagnosis of PCOS, have been observed among women with HS. In two series, there were high frequencies of acne, hirsutism, irregular
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menstruation, and infertility noted (Mortimer et al., 1986b; Barth et al., 1996). In addition to the
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observation of clinical signs suggestive of androgen excess, the relationship between HS and
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hyperandrogenism was further supported by the observation of a high free androgen index in the context
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of low sex hormone binding globulin (SHBG) (Mortimer et al., 1986b). The analysis did not account for
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high body weights among HS patients, which could have been responsible for the low SHBG levels
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observed.
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When compared to age-matched controls however, women with HS do not appear have an
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increase in clinical signs of androgenization (Jemec, 1988). Moreover, other studies have refuted the
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initial observation that androgens may be elevated among patients with HS. In a case controlled series of
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66 women with HS, plasma androgen levels were not significantly different between HS subjects and
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controls matched for age, weight, and hisutism. Testosterone and dehydroepiandrosterone sulphate were
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normal in all patients with HS (Barth et al., 1996). These findings were largely consistent with another
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earlier study evaluating plasma androgens in women with HS (Harrison et al., 1988).
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Because HS patients appear to exhibit normal androgen levels, an enhanced peripheral conversion of androgens has been suggested. However, activity of peripheral androgen-converting enzymes in
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apocrine glands of the axillae in HS patients showed no differences when compared to controls (Barth and
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Kealey, 1991). Moreover, androgen and estrogen receptor expression within apocrine glands of lesion
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skin fail to show alterations compared to control samples (Buimer et al., 2015). Skin and adnexae may
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produce peptide and steroid hormones de novo (Slominski et al., 2013; Labrie et al., 2000; Paus et al.,
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2008; Zouboulis, 2000; Zouboulis et al., 2007), which may alter hormone-related homeostasis in HS
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patients and promote early hyperkeratinization and follicular plugging (Kamp et al., 2011).
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Modulation of end organ hormone-related homeostasis may account for the observed efficacy of
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therapies including metformin, spironolactone, and finasteride which may influence the androgen
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environment. In a retrospective series of 64 women with HS, metformin was shown to improve symptoms
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in 55%, compared to 26% of HS patients who received treatment with oral antibiotics (Kraft and Searles,
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2007). In another case series of 22 women and three men with HS who received treatment with metformin
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for 24 weeks, 18 showed substantial improvement in disease severity as measured by Sartorius score and
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quality of life as measured by the Dermatology Life Quality Index score (Verdolini et al., 2013). Among
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20 patients with HS, 17 (85%) responded within three months to anti-androgenic treatment with
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spironolactone 100mg daily. Complete suppression was achieved in 11/20 (55%). There was no
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relationship between the initial severity and response to treatment (Lee and Fischer, 2015). Finally, in a
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small case series involving seven HS patients, six (86%) showed significant clinical improvement on
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finasteride 5 mg daily. Two of those six patients experienced complete remission (Joseph et al., 2005).
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There are limits which warrant consideration when interpreting the results of this study. We could not capture patients who did not seek care in health systems included in the database. Although ICD
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codes for both HS and PCOS have relatively high positive predictive values, the use of administrative
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claims data is an imperfect standard for case identification. While this may result in misclassification bias,
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there is no evidence that the accuracy of a claim for PCOS would differ according to HS status (i.e.
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differential misclassification). Influence of disease severity on strength of association with PCOS could
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not be assessed, nor could an HS phenotype for patients also having PCOS. This analysis could not
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establish directionality of the relationship, nor a causal link. Despite these limitations, the present study
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describes important data describing the association between HS and PCOS. The prevalence and strength
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of association reported in this study is based on the largest and most ethnically diversified cohort of
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patients with HS worldwide, and this has also facilitated subgroup analyses which allow identification of
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groups at highest risk. Because the population sample is drawn from various health care settings across all
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US census regions, this study overcomes selection biases associated with tertiary single or multi-center
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investigations. We believe these results may be generalized to the US population.
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In conclusion, our results indicate that HS has a strong association with PCOS, and is similar to associations of obesity and diabetes mellitus with PCOS. HS patients with symptoms or signs of
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hyperandrogenism should be screened for PCOS. The role of androgens in HS and the potential benefit of
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anti-androgen therapy warrant further exploration.
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MATERIALS AND METHODS
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Data Sources and Study Population
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This was a cross sectional analysis using a multi-health system data analytics and research
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platform (Explorys) developed by International Business Machines (IBM) Corporation, Watson Health™
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(Explorys Inc., 2017). Clinical information from electronic medical records, laboratories, practice
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management systems, and claims systems is matched using the single set of Unified Medical Language
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System ontologies to create longitudinal records for unique patients. The data are standardized and
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curated according to common controlled vocabularies and classifications systems (SNOMED CT, 2017;
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Nelson et al., 2011; McDonald et al., 2003; Shen et al., 2001; Foraker et al., 2010). At present, the
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database encompasses 27 participating integrated healthcare organizations. Over 50 million unique lives,
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representing approximately 15% of the population across all four census regions of the United States, are
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captured. Patients with all types of insurance as well as those who are self-pay are represented. In order to
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maintain data confidentiality, Explorys provides population level counts rounded to the nearest 10, and
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reports counts between 1 and 9 as less than 10.
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The SNOMED-CT term ‘hidradenitis’ has one-to-one mapping to the ICD-9 code 705.83, and
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was used to identify patients with HS. In validating the case cohort, we observed a positive predictive
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value (PPV) of 79.3% and an accuracy of 90% for diagnosis of HS using a single ICD-9 code for HS
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(Strunk et al., 2017). This case identification method was previously validated by an independent group,
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and it was shown to have a positive predictive value of 77% (Shlyankevich et al., 2014). This method has
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also been used to establish disease burden in the United States (Garg et al., 2017a; 2017b). Patients with
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PCOS were identified by the ICD-9 code 256.4 which maps to the SNOMED-CT term “polycystic ovary
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syndrome”. This method was previously shown to have a PPV of 74% (Castro et al., 2015).
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Statistical Analysis
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The analysis was limited to female patients aged 18 years or older with an active status in the database within the past 3 years (November, 2014-November, 2017) who were not missing demographic
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data on age, gender, race, and body mass index (BMI). Age in years was recorded as a categorical
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variable within one of three groups: 18-29, 30-39, and 40-49. The race variable was dichotomized as
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white vs. nonwhite. BMI was dichotomized into obese (BMI > 30.0) vs. non-obese (BMI < 30.0). The
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SNOMED-CT terms ‘tobacco user’ (ICD-9 code 305.1) and ‘nicotine dependence’ (ICD-10 code F17.2)
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were used to identify active tobacco smokers. Individuals with no record of either of these terms were
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considered non-smokers. Study size was determined by the number of patients satisfying all eligibility
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criteria. Given the millions of patients who are active in the database, and tens of thousands of patients
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with HS, sample size calculations were not performed.
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We obtained population level counts of the number of patients with and without a diagnosis of PCOS for each combination of categorical explanatory variables (HS status, age, race, BMI status,
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diabetes mellitus status, and smoking status). We assessed crude associations between PCOS and each
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explanatory variable using separate univariable logistic regression models. Multivariable logistic
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regression was performed to evaluate the relationship between HS and PCOS while controlling for age,
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race, BMI status, diagnosis of diabetes mellitus, and smoking status). Differences in the association
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between HS and PCOS across patient subgroups were tested individually by including an interaction term
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for HS and the subgroup variable of interest in separate logistic regression models. Patients with any
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missing covariate data were excluded from the study sample, and thus a complete case analysis was used.
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In order to assess the potential impact of missing race and BMI data on our findings, we compared the
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crude prevalence of PCOS among female patients aged 18-49 with missing data in each exposure group.
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Although the crude prevalences were slightly lower for patients with missing data, PCOS remained more
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than four times as common in those with HS than those without HS (5.6% and 1.2%, respectively). All
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analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC). Human Subjects Committee
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review was waived since there are no identifiers associated with the data.
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CONFLICT OF INTEREST:
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Dr. Garg has served as an advisor for AbbVie and received honoraria. AbbVie has provided the
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corresponding author an unrestricted educational grant which has been used to support this study. The
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sponsor has had no role in the study design; in the collection, analysis and interpretation of the data; in the
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writing of the report; or in the decision to submit the manuscript for publication.
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None
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Table 1: Demographic characteristics. Non-HS Patients (n=3,369,150)
Polycystic ovarian syndrome
2,070 (9.0%)
96,940 (2.9%)
Age 18-29 30-39 40-49
7,565 (32.9%) 6,895 (30.0%) 8,530 (37.1%)
1,242,150 (36.9%) 1,108,930 (32.9%) 1,018,070 (30.2%)
Race White Non-white
12,950 (56.3%) 10,040 (43.7%)
2,489,910 (73.9%) 879,240 (26.1%)
Tobacco smoker Obese (BMI > 30.0) Diabetes mellitus
13,090 (56.9%) 17,280 (75.2%) 3,815 (16.6%)
1,033,320 (30.7%) 1,417,840 (42.1%) 208,220 (6.2%)
RI PT
HS Patients (n=22,990)
M AN U
Characteristic
SC
297
AC C
EP
TE D
298
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Figure 1. Hidradenitis suppurativa.
300
Description of overall and subgroup prevalences for polycystic ovarian syndrome among hidradenitis
301
suppurativa patients, as well as the overall and subgroup odds of polycystic ovarian syndrome among
302
patient with hidradenitis suppurativa.
AC C
EP
TE D
M AN U
SC
RI PT
299
AC C
EP
TE D
M AN U
SC
RI PT
ACCEPTED MANUSCRIPT