Melanoma Institute Australia, The University of Sydney, Sydney, New South Wales, Australia.
Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia.
J Eur Acad Dermatol Venereol. 2023 Jul;37(7):1293-1301. doi: 10.1111/jdv.18998. Epub 2023 Mar 25.
Lentigo maligna (LM), a form of melanoma in situ, has no risk of causing metastasis unless dermal invasive melanoma (LMM) supervenes. Furthermore, the detection of invasion impacts prognosis and management.
To assess the accuracy of RCM for the detection of invasion component on LM/LMM lesions.
In the initial case-control study, the performance of one expert in detecting LMM at the time of initial RCM assessment of LM/LMM lesions was recorded prospectively (n = 229). The cases were assessed on RCM-histopathology correlation sessions and a panel with nine RCM features was proposed to identify LMM, which was subsequently tested in a subset of initial cohort (n = 93) in the matched case-control study by two blinded observers. Univariable and multivariable logistic regression models were performed to evaluate RCM features predictive of LMM. Reproducibility of assessment of the nine RCM features was also evaluated.
A total of 229 LM/LMM cases evaluated by histopathology were assessed blindly and prospectively by an expert confocalist. On histopathology, 210 were LM and 19 were LMM cases. Correct identification of an invasive component was achieved for 17 of 19 LMM cases (89%) and the absence of a dermal component was correctly diagnosed in 190 of 210 LM cases (90%). In the matched case-control (LMM n = 35, LM n = 58), epidermal and junctional disarray, large size of melanocytes and nests of melanocytes were independent predictors of LMM on multivariate analysis. The interobserver analysis demonstrated that these three features had a fair reproducibility between the two investigators (K = 0.4). The multivariable model including those three features showed a high predictive performance AUC = 74% (CI 95% 64-85%), with sensitivity of 63% (95% CI 52-78%) and specificity of 79% (CI 95% 74-88%), and likelihood ratio of 18 (p-value 0.0026).
Three RCM features were predictive for identifying invasive melanoma in the background of LM.
原位黑色素瘤（LM）是一种黑色素瘤，除非出现真皮浸润性黑色素瘤（LMM），否则不会有转移的风险。此外，浸润的检测会影响预后和治疗。
评估共聚焦显微镜（RCM）检测 LM/LMM 病变中侵袭性成分的准确性。
在初始病例对照研究中，前瞻性记录一位专家在首次 RCM 评估 LM/LMM 病变时检测 LMM 的表现（n=229）。对病例进行 RCM-组织病理学相关性评估，并提出了一个包含 9 个 RCM 特征的小组来识别 LMM，然后在初始队列的一个子集（n=93）中由两名盲法观察者在匹配的病例对照研究中进行测试。采用单变量和多变量逻辑回归模型评估预测 LMM 的 RCM 特征。还评估了 9 个 RCM 特征评估的可重复性。
对 229 例经组织病理学评估的 LM/LMM 病例进行了盲法前瞻性评估。在组织病理学上，210 例为 LM，19 例为 LMM。在 19 例 LMM 病例中，正确识别出 17 例有侵袭性成分，在 210 例 LM 病例中，正确诊断出 190 例无真皮成分。在匹配的病例对照研究（LMM n=35，LM n=58）中，表皮和连接紊乱、黑素细胞大小和黑素细胞巢增大是多变量分析中 LMM 的独立预测因素。观察者间分析表明，这三个特征在两位研究者之间具有良好的可重复性（K=0.4）。包括这三个特征的多变量模型显示出较高的预测性能 AUC=74%（95%CI 64-85%），敏感性为 63%（95%CI 52-78%），特异性为 79%（95%CI 74-88%），优势比为 18（p 值 0.0026）。
三种 RCM 特征可预测 LM 背景下的侵袭性黑色素瘤。
