Lu Wen, Chen Xiaoyue, Ni Jingyi, Li Zhen, Su Tao, Li Shuangdi, Wan Xiaoping
Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tong Ji University, Shanghai, China.
Department of Clinical Research Center, Shanghai First Maternity and Infant Hospital, School of Medicine, Tong Ji University, Shanghai, China.
Front Oncol. 2022 Jun 20;12:895834. doi: 10.3389/fonc.2022.895834. eCollection 2022.
The Mayo criteria are the most widely accepted algorithm for predicting the risk of lymph node metastasis in endometrial endometrioid carcinoma (EEC). However, the clinical value of these criteria in high-risk patients is limited and inconclusive.
A total of 240 patients with EEC meeting the Mayo high-risk criteria between January 1, 2015, and December 31, 2018 were included in our study. We retrospectively collected the laboratory reports, basic clinical information, clinicopathological and immunohistochemistry (IHC) findings, and the sequences of molecular pathological markers of these patients. A nomogram for predicting the likelihood of positive lymph node status was established based on these parameters.
Among the 240 patients, 17 were diagnosed with lymph node metastasis. The univariable analyses identified myometrial invasion >50%, aberrant p53 expression, microsatellite instable (MSI), and cancer antigen 125 (CA125) ≥35 U/ml as potential risk factors for lymph node metastasis. The multivariable analyses showed that aberrant p53 expression, MSI, and CA125 ≥35 U/ml were independent predictors of lymph node metastasis. The area under the curve (AUC) for the nomogram was 0.870, as compared to 0.665 for the Mayo criteria.
Our novel prediction model effectively identifies patients at high risk for lymphatic metastasis. This model is a promising strategy for personalized surgery in patients with high risk according to the Mayo criteria.
梅奥标准是预测子宫内膜样腺癌(EEC)淋巴结转移风险最广泛接受的算法。然而,这些标准在高危患者中的临床价值有限且尚无定论。
本研究纳入了2015年1月1日至2018年12月31日期间符合梅奥高危标准的240例EEC患者。我们回顾性收集了这些患者的实验室报告、基本临床信息、临床病理和免疫组化(IHC)结果以及分子病理标志物序列。基于这些参数建立了预测淋巴结阳性状态可能性的列线图。
在240例患者中,17例被诊断为淋巴结转移。单因素分析确定肌层浸润>50%、p53表达异常、微卫星不稳定(MSI)和癌抗原125(CA125)≥35 U/ml为淋巴结转移的潜在危险因素。多因素分析显示,p53表达异常、MSI和CA125≥35 U/ml是淋巴结转移的独立预测因素。列线图的曲线下面积(AUC)为0.870,而梅奥标准的AUC为0.665。
我们的新型预测模型有效地识别了有淋巴转移高危风险的患者。该模型是根据梅奥标准对高危患者进行个性化手术的一种有前景的策略。