Importance of Both Clinical and Dermoscopic Findings in Predicting High-Risk Histopathological Subtype in Facial Basal Cell Carcinomas.

IF 2.5 4区 医学 Q2 DERMATOLOGY Dermatology practical & conceptual Pub Date : 2024-07-01 DOI:10.5826/dpc.1403a212
Hannah Ceder, Eva Backman, Ashfaq Marghoob, Cristián Navarrete-Dechent, Sam Polesie, Ofer Reiter, John Paoli
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Abstract

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.

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临床和皮肤镜检查结果对预测面部基底细胞癌高危组织病理学亚型的重要性
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。
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CiteScore
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