NYU Langone Medical Center, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Histopathology. 2021 Nov;79(5):847-860. doi: 10.1111/his.14434. Epub 2021 Sep 3.
Perivascular epithelioid cell tumours (PEComas) are rare mesenchymal tumours that coexpress smooth muscle and melanocytic markers. They have a predilection for gynaecological organs, where they present a unique diagnostic challenge, because of morphological and immunohistochemical overlap with more common smooth muscle and stromal tumours. Limited information regarding the natural history, owing to the rarity of this tumour, makes accurate risk stratification difficult. We aimed to review clinicopathological features of gynaecological PEComa and compare accuracy of five different classification systems for prediction of prognosis.
We have described the clinicopathological features of 13 new cases and tested five prognostic algorithms in a total of 67 cases of gynaecological PEComa. Receiver operating characteristic curves were constructed and areas under the curve (AUCs) were calculated to evaluate predictive accuracy. The modified gynaecological-specific algorithm showed high sensitivity and specificity and yielded the highest AUC (0.864). It's earlier version, the gynaecological-specific algorithm, suffered from lower specificity (AUC = 0.843). The post-hoc McNemar test confirmed significant differences between the performances of the modified gynaecological-specific algorithm and the gynaecological-specific algorithm (P = 0.008). The original Folpe algorithm for PEComas of all sites showed low specificity, had a lower AUC (0.591), and was inapplicable in 18% of cases. Its two later versions (the revised Folpe algorithm and the modified Folpe algorithm) also yielded lower AUCs (0.690 and 0.591, respectively).
We have shown that the modified gynaecological-specific algorithm predicts the clinical outcome of gynaecological PEComa with high accuracy, and have validated its use for prognostic stratification of gynaecological PEComa.
血管周上皮样细胞瘤(PEComa)是一种罕见的间叶性肿瘤,共同表达平滑肌和黑色素细胞标志物。它们偏爱妇科器官,由于与更常见的平滑肌和基质肿瘤在形态学和免疫组织化学上存在重叠,因此在这些部位具有独特的诊断挑战性。由于这种肿瘤的罕见性,关于其自然史的信息有限,使得准确的风险分层变得困难。我们旨在回顾妇科 PEComa 的临床病理特征,并比较五种不同分类系统预测预后的准确性。
我们描述了 13 例新病例的临床病理特征,并在总共 67 例妇科 PEComa 中测试了五种预后算法。构建了受试者工作特征曲线,并计算了曲线下面积(AUC)以评估预测准确性。改良的妇科特异性算法显示出高灵敏度和特异性,并产生了最高的 AUC(0.864)。它的早期版本,妇科特异性算法,特异性较低(AUC=0.843)。事后 McNemar 检验证实了改良妇科特异性算法和妇科特异性算法之间的性能差异具有统计学意义(P=0.008)。用于所有部位的 PEComa 的原始 Folpe 算法特异性低,AUC 较低(0.591),并且在 18%的病例中不适用。其两个后来的版本(修订后的 Folpe 算法和改良的 Folpe 算法)也产生了较低的 AUC(分别为 0.690 和 0.591)。
我们已经证明,改良的妇科特异性算法可以准确预测妇科 PEComa 的临床结局,并验证了其在妇科 PEComa 预后分层中的应用。