Background: A validated tool for the dynamic severity assessment of hidradenitis suppurativa/acne inversa (HS) is lacking. Objectives: To develop and validate a novel dynamic scoring system to assess the severity of HS. Methods: A Delphi voting procedure was conducted among the members of the European Hidradenitis Suppurativa Foundation (EHSF) to achieve consensus towards an initial HS Severity Score System (HS4). Strengths and weaknesses of HS4 were examined by a multicentre prospective study. Multivariate logistic regression, discriminant analysis and receiver operating characteristic curves, as well as examination for correlation (Spearman's rho) and agreement (Cohen's kappa) with existing scores, were engaged to recognize the variables for a new International HS4 (IHS4) that was established by a second Delphi round. Results: Consensus HS4 was based on number of skin lesions, number of skin areas involved and Dermatology Life Quality Index (DLQI), and was evaluated by a sample of 236 patients from 11 centres. Subsequently, a multivariate regression model calculated adjusted odds ratios for several clinical signs. Nodules, abscesses and draining tunnels resulted as the scoring variables. Three candidate scores were presented to the second Delphi round. The resulting IHS4 score is arrived at by the number of nodules (multiplied by 1) plus the number of abscesses (multiplied by 2) plus the number of draining tunnels (multiplied by 4). A total score of 3 or less signifies mild, 4–10 signifies moderate and 11 or higher signifies severe disease. Cohen's kappa was fair (κ = 0·32) compared with Hurley classification, and moderate (κ = 0·49) compared with Expert Opinion. Correlation was good (ρ > 0·6) with Hurley classification, Expert Opinion, Physician's Global Assessment and Modified Sartorius score, and moderate for DLQI (ρ = 0·36). Conclusions: The novel IHS4 is a validated tool to dynamically assess HS severity and can be used both in real-life and the clinical trials setting.
|Tidsskrift||British Journal of Dermatology|
|Status||Udgivet - nov. 2017|