Abstract
Current validated hidradenitis suppurativa (HS) severity assessment tools are time-consuming and impractical in fast-paced, ambulatory clinic settings. This study evaluated the construct validity of the most severe or ‘worst’ area local Hidradenitis suppurativa Activity and Severity Index-Revised (W-HASI-R) as a novel target area assessment tool for clinical setting use. W-HASI-R had strong association with the International Hidradenitis Suppurativa Severity Score System and abscess and nodule count, moderate association with Hurley stage and HS physician global assessment and weak, negative association with reverse-scored Dermatology Quality Life Index. The resulting data suggest that W-HASI-R may be an option as an efficient target area assessment tool for fast-paced, ambulatory settings.
Dear Editor, In 2018, international consensus was reached on a core outcome set of domains to be included in hidradenitis suppurativa (HS) clinical trials (pain, physical signs, HS-specific quality of life, global assessment, progression of course and symptoms).1 However, a globally accepted, reliable outcome measure for the physical signs domain has not yet been established. The Hidradenitis Suppurativa Clinical Response (HiSCR) is the most commonly used outcome measure in HS clinical trials. HiSCR is a dichotomous outcome measure achieved by a 50% reduction in the total abscess and inflammatory nodule (AN) count with no increase in abscesses or draining tunnels compared with baseline.2 The International Hidradenitis Suppurativa Severity Score System (IHS4) dynamically measures the total number of inflammatory nodules, abscesses and draining tunnels.3 While tools relying on lesion counts, including the HiSCR and IHS4, are preferred measures in clinical trials, concerns have been raised regarding their reliability.4 This prompted the development of the Hidradenitis suppurativa Activity and Severity Index-Revised (HASI-R), a HS severity assessment tool that measures inflammatory colour change, inflammatory induration, open skin surface, and tunnels on a Likert scale (0–3), as well as an estimate of body surface area involved. These variables were established through literature review, concept elicitation from focus groups and cognitive debriefing interviews.4,5 HASI-R avoids lesion counts that are subject to naming discrepancies, rater fatigue and time constraints in fast-paced ambulatory settings.4,6 Given the historical use of Hurley classification for HS, based on the most severe or ‘worst’ area, our aim was to evaluate the potential use of the HASI-R as a target area assessment with greater capacity to assess treatment response.7
We utilized the local HASI-R score from the most severe or ‘worst’ area to determine HS severity in clinical practice and assess the construct (convergent/divergent) validity of this proposed tool compared with total IHS4, Hurley classification, AN count, HS physician global assessment (HS-PGA) and Dermatology Life Quality Index (DLQI). We hypothesized that the worst area local HASI-R (W-HASI-R) would correlate strongly with these other measures, and have a low correlation with reverse-scored DLQI.
Fifty-six participants, with a total of 140 active HS sites, from the University of Minnesota Department of Dermatology consented and were enrolled into a HS registry between September 2020 and September 2021. This study was approved by the University of Minnesota Institutional Review Board (IRB# STUDY00009518). The average age of participants was 38 years. The cohort was predominantly female (n = 39; 70%). The majority of participants identified as White (n = 37; 66%), followed by Black (n = 13; 23%) and Asian (n = 4; 7%). Participants were classified as Hurley Stage I (n = 21; 38%), Hurley Stage II (n = 25; 45%) or Hurley Stage III (n = 6, 11%).
Local HASI-R was determined at 10 anatomic sites for each participant at the time of enrolment.4 Additionally, total HASI-R, IHS4, AN count, Hurley classification, HS-PGA and DLQI were obtained. Evaluations were performed by a single physician (N.G.).
W-HASI-R was defined as the affected site with the highest HASI-R score. Construct validity was determined by calculating the Pearson correlation coefficient for W-HASI-R and individual HASI-R components with the IHS4, AN count, Hurley classification, HS-PGA and reverse-scored DLQI. Post hoc, we also evaluated the construct validity of the HASI-R excluding open skin surface, due to the comparably lower values with respect to that domain. Correlation coefficients of 0.00–0.19 were classified as no association, and 0.20–0.49 as weak, 0.50–0.79 as moderate, and ≥ 0.80 as strong association.
W-HASI-R had strong association with the IHS4 (r = 0.850) and AN count (r = 0.863), moderate association with Hurley classification (r = 0.734) and HS-PGA (r = 0.768), and weak negative association with reverse-scored DLQI (r = –0.373), similar to other HS physician-reported measures in prior studies.4 Excluding the open skin surface domain resulted in similar associations with the physician- and patient-reported outcomes. All W-HASI-R components had moderate-to-strong association with the evaluated physician-reported outcome measures (Table 1).
Table 1.
Construct (convergent/divergent) validity [r (95% confidence interval)] of the highest-scored ‘worst area’ local Hidradenitis suppurativa Activity and Severity Index-Revised (W-HASI-R)
| Worst area | HASI-R | IHS4 | AN count | Hurley | HS-PGA | Reverse-scored DLQI |
|---|---|---|---|---|---|---|
| Local HASI-R | 0.95*** (0.92–0.97) |
0.85*** (0.75–0.91) |
0.86*** (0.77–0.92) |
0.73*** (0.57–0.84) |
0.77*** (0.62–0.86) |
–0.37** (–0.59 to –0.11) |
| Local HASI-R without open skin surface domain | 0.96*** (0.92–0.97) |
0.85*** (0.75–0.91) |
0.87*** (0.78–0.92) |
0.73*** (0.56–0.84) |
0.77*** (0.62–0.86) |
–0.38** (–0.59 to –0.11) |
| Inflammatory colour change | 0.65*** (0.46–0.78) |
0.70*** (0.53–0.82) |
0.67*** (0.49–0.80) |
0.53*** (0.29–0.70) |
0.81*** (0.68–0.89) |
–0.40** (–0.61 to –0.14) |
| Inflammatory induration | 0.68*** (0.50–0.80) |
0.68*** (0.51–0.81) |
0.66*** (0.47–0.79) |
0.55*** (0.32–0.72) |
0.88*** (0.79–0.93) |
–0.46** (–0.65 to –0.21) |
| Total open skin surface | 0.67*** (0.48–0.80) |
0.66*** (0.47–0.79) |
0.66*** (0.47–0.79) |
0.63*** (0.70–0.90) |
0.64*** (0.44–0.78) |
–0.36* (–0.58 to –0.09) |
| Extent of tunnels | 0.82*** (0.71–0.90) |
0.80*** (0.67–0.88) |
0.80*** (0.68–0.89) |
0.82*** (0.70–0.90) |
0.75*** (0.59–0.86) |
–0.25 (–0.50 to 0.03) |
| Body surface area | 0.87*** (0.78–0.92) |
0.77*** (0.64–0.86) |
0.77*** (0.63–0.86) |
0.68*** (0.51–0.80) |
0.86*** (0.76–0.92) |
–0.37** (–0.58 to –0.12) |
Pearson correlation coefficients *P < 0.05; **P < 0.01; ***P < 0.001
AN, total abscess and inflammatory nodule count; DLQI, Dermatology Life Quality Index; HS, hidradenitis suppurativa; HS-PGA, HS physician global assessment; IHS4, International Hidradenitis Suppurativa Severity Score System
The data suggest that W-HASI-R, excluding open skin surface domain for an even more efficient assessment, may be an option as a target area evaluation for fast-paced, ambulatory settings. This method is efficient and avoids lesion counts. Additionally, HASI-R has been found to have relatively higher inter- and intra-rater reliability compared with other HS severity assessment tools, and therefore may also be useful for interventional clinical trials.4
Limitations of this study include small sample size and single rater evaluations. Future studies should include multiple raters to evaluate the inter- and intra-rater reliability, as well as prospective studies to evaluate responsiveness and investigate the best method for selecting the ‘worst’ area. The data underlying this article will be shared on reasonable request to the senior author.
Contributor Information
Gretchen Bellefeuille, Departments of Dermatology and.
Briana Paiewonsky, Departments of Dermatology and; Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, FL, USA.
Bisma Khalid, Departments of Dermatology and.
Rebecca L Freese, Biostatistical Design and Analysis Center, Clinical and Translational Science Institute, University of Minnesota, Minneapolis, MN, USA.
Michelle A Lowes, The Rockefeller University, New York, NY, USA.
Joslyn S Kirby, Department of Dermatology, Penn State Health Milton S. Hershey Medical Center, Hershey, PA, USA.
Afsaneh Alavi, Department of Dermatology, Mayo Clinic, Rochester, MN, USA.
Noah Goldfarb, Departments of Dermatology and; Medicine, University of Minnesota Academic Health Center, Minneapolis, MN, USA; Departments of Medicine and Dermatology, Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, USA.
Funding sources
this research was supported by the National Institutes of Health’s National Center for Advancing Translational Sciences, grant UL1TR002494. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health’s National Center for Advancing Translational Sciences.
References
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