Perrot Jean-Luc, Maccari François, Guillem Philippe, Fougerousse Anne-Claire, Nassif Aude, Beneton Nathalie, Cinotti Elisa, Girard Céline, Binois Raphaelle, Reguiaï Ziad
Department of Dermatology, University Hospital of Saint-Etienne, Saint-Etienne, France.
ResoVerneuil, Ville, France.
Clin Cosmet Investig Dermatol. 2022 Jun 16;15:1091-1103. doi: 10.2147/CCID.S362622. eCollection 2022.
Hidradenitis suppurativa (HS) is an inflammatory skin disease characterized by recurrent or chronic painful and suppurating lesions in the apocrine gland-bearing regions. The lack of knowledge about HS and its extremely heterogeneous clinical presentation, in terms of both lesion appearance and sites of involvement, frequently delay its diagnosis for several years. Objectives: in this study, using the latent class analysis, it was demonstrated that severity of HS could be evaluated not only with clinical or surgical characteristics but also with gender specificities.
Clinical and sociodemographic data of HS patients were retrospectively analysed with the latent class method in order to create a classification tool of disease severity.
From the study of 1428 HS patients (544 men and 884 women), two classification models, depending on gender, were developed. Each classification model was composed of three distinct latent classes clearly identified and defined from mild-to-severe cases of HS. These classification models of HS severity were not distorted by patient ages and were coherent with Hurley stages but were more clinically precise.
In this study, a convenient classification tool, useful for facilitating decision support in routine practice, has been developed. This tool could be used to define clinical subgroups within a study population.
化脓性汗腺炎(HS)是一种炎症性皮肤病,其特征为在顶泌汗腺分布区域出现反复发作或慢性疼痛性化脓性病变。由于对HS缺乏了解,且其临床表现(包括病变外观和受累部位)极其多样,HS的诊断常常会延迟数年。目标:在本研究中,通过潜在类别分析表明,HS的严重程度不仅可以通过临床或手术特征来评估,还可以根据性别特异性进行评估。
采用潜在类别方法对HS患者的临床和社会人口统计学数据进行回顾性分析,以创建疾病严重程度的分类工具。
通过对1428例HS患者(544例男性和884例女性)的研究,开发了两种基于性别的分类模型。每个分类模型由三个不同的潜在类别组成,这些类别从HS的轻度到重度病例中清晰地识别和定义出来。这些HS严重程度的分类模型不受患者年龄的影响,与赫尔利分期一致,但在临床上更为精确。
在本研究中,开发了一种方便的分类工具,有助于在常规实践中提供决策支持。该工具可用于在研究人群中定义临床亚组。