Institute of Hair and Cosmetic Medicine, Department of Dermatology, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea.
JAMA Dermatol. 2019 May 1;155(5):564-571. doi: 10.1001/jamadermatol.2018.5894.
Diverse assessment tools and classification have been used for alopecia areata; however, their prognostic values are limited.
To identify the topographic phenotypes of alopecia areata using cluster analysis and to establish a prediction model and grading system for stratifying prognoses.
DESIGN, SETTING, AND PARTICIPANTS: A retrospective cohort study of 321 patients with alopecia areata who visited a single tertiary referral center between October 2012 and February 2017 and underwent 4-view photographic assessment.
Clinical photographs were reviewed to evaluate hair loss using the Severity of Alopecia Tool 2. Topographic phenotypes of alopecia areata were identified using hierarchical clustering with Ward's method. Differences in clinical characteristics and prognosis were compared across the clusters. The model was evaluated for its performance, accuracy, and interobserver reliability by comparison to conventional methods.
Topographic phenotypes of alopecia areata and their major (60%-89%) and complete regrowth probabilities (90%-100%) within 12 months.
A total of 321 patients were clustered into 5 subgroups. Grade 1 (n = 200; major regrowth, 93.4%; complete regrowth, 65.2%) indicated limited hair loss, whereas grades 2A (n = 66; major regrowth, 87.8%; complete regrowth, 64.2%) and 2B (n = 20; major regrowth, 73.3%; complete regrowth, 45.5%) exhibited greater hair loss than grade 1. The temporal area was predominantly involved in grade 2B, but not in grade 2A, despite being comparable in total extent of hair loss. Grade 3 (n = 20; major regrowth, 45.5%; complete regrowth, 25.5%) included diffuse or extensive alopecia areata, and grade 4 (n = 15; major regrowth, 28.2%; complete regrowth, 16.7%) corresponded to alopecia (sub)totalis. No significant differences in prognosis (hazard ratio [HR] for major regrowth, 0.79; 95% CI, 0.56-1.12) were found between grades 2A and 1, whereas grades 2B (HR, 0.41; 95% CI, 0.21-0.81), 3 (HR, 0.24; 95% CI, 0.12-0.50), and 4 (HR, 0.16; 95% CI, 0.06-0.39) had significantly poorer response. Among multiple models, the cluster solution had the greatest prognostic performance and accuracy. The tree model of the cluster solution was converted into the Topography-based Alopecia Areata Severity Tool (TOAST), which revealed an excellent interobserver reliability among 4 dermatologists (median quadratic-weighted κ, 0.89).
Temporal area involvement should be independently measured for better prognostic stratification. The TOAST is an effective tool for describing the topographical characteristics and prognosis of hair loss and may enable clinicians to establish better treatment plans.
重要性：斑秃的评估工具和分类方法多种多样，但它们的预后价值有限。
目的：使用聚类分析确定斑秃的拓扑表型，并建立预测模型和分级系统来分层预后。
设计、地点和参与者：这是一项回顾性队列研究，纳入了 2012 年 10 月至 2017 年 2 月期间在一家三级转诊中心就诊的 321 例斑秃患者，这些患者接受了 4 视图摄影评估。
暴露：对临床照片进行回顾性评估，使用严重程度脱发工具 2 评估脱发情况。使用 Ward 方法的层次聚类确定斑秃的拓扑表型。比较各聚类之间的临床特征和预后差异。通过与传统方法比较，评估模型的性能、准确性和观察者间可靠性。
主要结果和措施：斑秃的拓扑表型，以及在 12 个月内主要（60%-89%）和完全再生（90%-100%）的概率。
结果：321 例患者分为 5 个亚组。1 级（n=200；主要再生率 93.4%；完全再生率 65.2%）提示脱发有限，而 2A 级（n=66；主要再生率 87.8%；完全再生率 64.2%）和 2B 级（n=20；主要再生率 73.3%；完全再生率 45.5%）的脱发程度高于 1 级。2B 级的颞部受累为主，但在总脱发面积方面与 2A 级相当。3 级（n=20；主要再生率 45.5%；完全再生率 25.5%）包括弥漫性或广泛性斑秃，4 级（n=15；主要再生率 28.2%；完全再生率 16.7%）相当于斑秃（部分）totalis。2A 级和 1 级之间的预后（主要再生的危险比 [HR]，0.79；95%CI，0.56-1.12）无显著差异，而 2B 级（HR，0.41；95%CI，0.21-0.81）、3 级（HR，0.24；95%CI，0.12-0.50）和 4 级（HR，0.16；95%CI，0.06-0.39）的反应明显较差。在多种模型中，聚类解决方案具有最佳的预后性能和准确性。聚类解决方案的树模型被转化为基于拓扑的斑秃严重程度工具（TOAST），4 位皮肤科医生的观察者间可靠性非常好（中位数二次加权 κ，0.89）。
结论和相关性：颞部受累应单独测量，以进行更好的预后分层。TOAST 是一种描述脱发的拓扑特征和预后的有效工具，它可以帮助临床医生制定更好的治疗计划。
