Department of Gastroenterology and Hepatology, Mayo Clinic, Jacksonville, Florida 32224, USA.
Gastrointest Endosc. 2010 Aug;72(2):265-71. doi: 10.1016/j.gie.2010.02.037. Epub 2010 Jun 11.
EUS is useful in determining mediastinal lymph node (LN) metastases in patients undergoing staging for lung cancer. However, FNA of LNs is often performed only if suspicious features are present. The utility of individual LN features in predicting malignant cytology remains unclear.
To evaluate the utility of EUS-determined LN features for predicting malignant cytology.
Prospective observational study.
Two U.S. tertiary-care centers.
This study involved 425 patients with primary lung cancer who underwent EUS.
All mediastinal LNs were described according to size, shape, echogenicity, and margin characteristics. FNA was performed on LNs with any features suggestive of malignancy. EUS-guided FNA cytology was classified as benign or abnormal (suspicious/malignant). The utility of LN features in predicting malignant cytology was determined and further analyzed by logistic regression, and a predictive model was established.
Accuracy of individual LN features for predicting malignancy.
EUS detected 836 LNs in 425 patients, and FNA was obtained in 698 patients. On multivariable analysis, only round shape, a short axis of >8.3 mm, and sharp margins were predictive of malignant cytology. According to the predictive model, the calculated probability of having malignancy is less than 4% (95% confidence interval [CI], 0.022-0.064) when none of the LN features are present and 63% (95% CI, 51%-72.2%) when all features were seen.
No surgical histology as the criterion standard.
Among patients with lung cancer, EUS features of round shape, sharp margins, and short axis of >8.3 mm are significant predictors of malignancy. The probability of malignancy is low when none of the features are present.
EUS 有助于确定肺癌分期患者的纵隔淋巴结(LN)转移。然而,只有在可疑特征存在的情况下,才对 LN 进行 FNA。LN 特征预测恶性细胞学的实用性仍不清楚。
评估 EUS 确定的 LN 特征预测恶性细胞学的实用性。
前瞻性观察研究。
美国的 2 个三级保健中心。
本研究纳入 425 例接受 EUS 的原发性肺癌患者。
根据大小、形状、回声特性和边缘特征描述所有纵隔 LN。对具有任何提示恶性特征的 LN 进行 FNA。EUS 引导下 FNA 细胞学分类为良性或异常(可疑/恶性)。确定 LN 特征预测恶性细胞学的准确性,并通过逻辑回归进行进一步分析,建立预测模型。
预测恶性细胞学的单个 LN 特征的准确性。
EUS 在 425 例患者中检测到 836 个 LN,698 例患者进行了 FNA。多变量分析显示,只有圆形、短轴>8.3mm 和锐利的边缘与恶性细胞学相关。根据预测模型,当不存在任何 LN 特征时,恶性肿瘤的计算概率小于 4%(95%置信区间[CI],0.022-0.064),而当所有特征均存在时,概率为 63%(95% CI,51%-72.2%)。
没有外科组织学作为金标准。
在肺癌患者中,EUS 的圆形、锐利边缘和短轴>8.3mm 的特征是恶性的显著预测因子。当不存在任何特征时,恶性肿瘤的可能性较低。