Noah Goldfarb

Background The hidradenitis suppurativa (HS) clinical response (HiSCR) has come under scrutiny as several HS clinical trials failed to meet primary endpoints with high placebo responses. This may be due to limitations of the tool and raters' ability to accurately characterize and count lesions, rather than lack of efficacy of the studied drug. Due to HS lesion complexity and potential differences in rater training, it was hypothesized that there would be discrepancies in how providers characterize and count lesions for HS clinical trials. Objective To evaluate how HS providers and patients name and count HS lesions and to identify discrepancies among providers to initiate the development of consensus‐driven guidance for HS rater training. Methods An online survey was distributed to the members of HIdradenitis SuppuraTiva cORe outcomes set International Collaboration (HISTORIC). Respondents were asked to classify lesion images composed of multiple and different morphology types and answer questions regarding inclusion of associated dermatological conditions. Results Forty‐seven HISTORIC members responded (29 providers; 18 patients). There was variability in how respondents classified HS lesions. Of 12 questions containing images, four had ≥50% of respondents choosing the same answer. With an image of a lesion composed of different morphologies, 45% of providers counted it as a single lesion and 45% counted it as multiple distinct lesions. With an image of multiple interconnected draining tunnels, 7% of providers classified it as a single draining tunnel while 79% categorized it as multiple draining tunnels with the number estimated by visual inspection. There was also variability in deciding whether lesions occurring in associated conditions should be considered separately or included in HS lesion counts. Patient responses were also variable. Conclusions The result of the current study reaffirms the gap in how providers characterize and count HS lesions for clinical trials and the need to develop consensus‐driven rater training related to HS outcome measures.