Scoring hidradenitis suppurativa: How to simplify data collection?

Dear Editor, Hidradenitis suppurativa (HS) is a chronic inflammatory skin disease, diagnosed clinically based on the type and location of the lesions, and on the disease course.1 The severity of HS varies greatly between patients and is difficult to quantify. This is strongly influenced by the phenotypical heterogeneity of the disease and implies that a broad range of very different elements must be assessed to encompass the variation adequately. There is no ‘gold standard’ score that would be useful for a universal grading of disease severity, assessing the efficacy of treatments and serving as a basis for management algorithms. More than 30 scores have been developed2 using physicianreported items (elements) like the clinical examination or subjectivebased items like patient reported outcomes (PRO) such as pain. Hitherto, biological biomarkers have not been sufficiently validated. The establishment of HS registries has helped to improve the understanding of the disease. However, an important limitation is the lack of time for the physician to fill the entire registry questionnaire and to calculate the complex and timeconsuming scoring systems. To save time in calculating the scores at the time of data collection, we collect the items needed to calculate certain scores (rather than calculating the score itself) and then calculate the score automatically, for example using Excel formulas. This procedure is used in the European Registry of HS (ERHS) and is one of the major changes between the initial version in 2016 and its update in 2021.3,4 The main advantage of this approach is obviously the time saved by automating the calculations. Moreover, if a new score combining already collected items is developed, it can be calculated retrospectively just by creating the appropriate formula that relates the relevant items. Finally, another advantage is that there is no risk of making a calculation error at the time of consultation, as the calculation is done automatically. It is obviously essential to avoid any error when entering the data as this would be a systematic error. Concerning the ERHS, the formulas used in the spreadsheet (Excel, Microsoft, US) were all done with Received: 29 August 2022 | Accepted: 25 October 2022