Hannah Ceder, Eva Backman, Ashfaq Marghoob, Cristián Navarrete-Dechent, Sam Polesie, Ofer Reiter, John Paoli
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The strongest associations with high-risk subtype were: \"bumpy\" topography (OR 3.8, 95% CI, 3.1-4.7), ill-defined borders (OR 3.4, 95% CI 3.1-4.7), white porcelain area (OR 3.5, 95% CI 2.8-4.5), and vessels within ulceration (OR 3.1, 95% CI 2.4-4.1). Predominantly focused vessels were a positive diagnostic criterium for either nodular (OR 1.7, 95% CI 1.3-2.2) or high-risk (OR 2.0, 95% CI 1.6-2.5) subtypes and a strong negative diagnostic criterium for superficial BCC (OR 14.0, 95% CI 9.6-20.8). Interobserver agreement ranged from fair to substantial (κ = 0.36 to 0.72). A diagnostic algorithm based on these findings demonstrated a sensitivity of 81.4% (95% CI, 78.9-83.7%) and a specificity of 53.3% (95% CI, 49.7-56.9%) for predicting high-risk BCC subtype.</p><p><strong>Conclusions: </strong>Integration of both clinical and dermoscopic features (including novel features such as topography and vessels within ulceration) are essential to improve subtype prediction of facial BCCs and management decisions.</p>","PeriodicalId":11168,"journal":{"name":"Dermatology practical & conceptual","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11314728/pdf/","citationCount":"0","resultStr":"{\"title\":\"Importance of Both Clinical and Dermoscopic Findings in Predicting High-Risk Histopathological Subtype in Facial Basal Cell Carcinomas.\",\"authors\":\"Hannah Ceder, Eva Backman, Ashfaq Marghoob, Cristián Navarrete-Dechent, Sam Polesie, Ofer Reiter, John Paoli\",\"doi\":\"10.5826/dpc.1403a212\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>Being able to recognize high-risk facial basal cell carcinoma (BCC) may lead to fewer incomplete excisions and inappropriate treatments.</p><p><strong>Objectives: </strong>We sought to investigate clinical and dermoscopic criteria for predicting facial BCC subtypes, analyze the interobserver agreement between readers, and develop a diagnostic algorithm to predict high-risk histopathological subtype.</p><p><strong>Methods: </strong>In this single-center, retrospective investigation, 6 independent readers evaluated predefined clinical and dermoscopic criteria in images of histopathologically verified primary facial BCCs including: topography, border demarcation, vessels, ulceration, white porcelain areas, shiny white blotches and strands, and pigmented structures and vessels within ulceration.</p><p><strong>Results: </strong>Overall, 297 clinical and dermoscopic image pairs were analyzed. 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引用次数: 0
摘要
导言:能够识别高风险面部基底细胞癌(BCC)可能会减少不完全切除和不适当的治疗:我们试图研究预测面部 BCC 亚型的临床和皮肤镜标准,分析读者之间的观察者间一致性,并开发一种诊断算法来预测高风险组织病理学亚型:在这项单中心回顾性调查中,6位独立读者评估了经组织病理学验证的原发性面部BCC图像中预定义的临床和皮肤镜标准,包括:地形、边界分界、血管、溃疡、白瓷区、发亮的白色斑点和条纹,以及溃疡内的色素结构和血管:共分析了 297 对临床和皮肤镜图像。与高风险亚型关系最密切的是"凹凸不平 "的地形(OR 3.8,95% CI,3.1-4.7)、边界不清晰(OR 3.4,95% CI 3.1-4.7)、白瓷区域(OR 3.5,95% CI 2.8-4.5)和溃疡内的血管(OR 3.1,95% CI 2.4-4.1)。主要集中的血管是结节型(OR 1.7,95% CI 1.3-2.2)或高危型(OR 2.0,95% CI 1.6-2.5)亚型的阳性诊断标准,是浅表 BCC 的强阴性诊断标准(OR 14.0,95% CI 9.6-20.8)。观察者之间的一致性从一般到相当高(κ=0.36 到 0.72)不等。基于这些结果的诊断算法显示,预测高风险 BCC 亚型的灵敏度为 81.4%(95% CI,78.9-83.7%),特异度为 53.3%(95% CI,49.7-56.9%):综合临床和皮肤镜特征(包括地形和溃疡内血管等新特征)对于改善面部 BCC 亚型预测和管理决策至关重要。
Importance of Both Clinical and Dermoscopic Findings in Predicting High-Risk Histopathological Subtype in Facial Basal Cell Carcinomas.
Introduction: Being able to recognize high-risk facial basal cell carcinoma (BCC) may lead to fewer incomplete excisions and inappropriate treatments.
Objectives: We sought to investigate clinical and dermoscopic criteria for predicting facial BCC subtypes, analyze the interobserver agreement between readers, and develop a diagnostic algorithm to predict high-risk histopathological subtype.
Methods: In this single-center, retrospective investigation, 6 independent readers evaluated predefined clinical and dermoscopic criteria in images of histopathologically verified primary facial BCCs including: topography, border demarcation, vessels, ulceration, white porcelain areas, shiny white blotches and strands, and pigmented structures and vessels within ulceration.
Results: Overall, 297 clinical and dermoscopic image pairs were analyzed. The strongest associations with high-risk subtype were: "bumpy" topography (OR 3.8, 95% CI, 3.1-4.7), ill-defined borders (OR 3.4, 95% CI 3.1-4.7), white porcelain area (OR 3.5, 95% CI 2.8-4.5), and vessels within ulceration (OR 3.1, 95% CI 2.4-4.1). Predominantly focused vessels were a positive diagnostic criterium for either nodular (OR 1.7, 95% CI 1.3-2.2) or high-risk (OR 2.0, 95% CI 1.6-2.5) subtypes and a strong negative diagnostic criterium for superficial BCC (OR 14.0, 95% CI 9.6-20.8). Interobserver agreement ranged from fair to substantial (κ = 0.36 to 0.72). A diagnostic algorithm based on these findings demonstrated a sensitivity of 81.4% (95% CI, 78.9-83.7%) and a specificity of 53.3% (95% CI, 49.7-56.9%) for predicting high-risk BCC subtype.
Conclusions: Integration of both clinical and dermoscopic features (including novel features such as topography and vessels within ulceration) are essential to improve subtype prediction of facial BCCs and management decisions.