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首页> 外文期刊>Annals of surgical oncology >Minimal disease in the sentinel lymph node: how to best measure sentinel node micrometastases to predict risk of additional non-sentinel lymph node disease.
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Minimal disease in the sentinel lymph node: how to best measure sentinel node micrometastases to predict risk of additional non-sentinel lymph node disease.

机译:前哨淋巴结的最小疾病:如何最好地测量前哨淋巴结微转移,以预测其他非前哨淋巴结疾病的风险。

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BACKGROUND: Volume of disease in the sentinel lymph node (SLN) is a significant predictor of additional nodal metastasis. This study assesses incidence of residual non-SLN disease in a large cohort of women with minimal SLN metastases and compares three methods of SLN micrometastasis volume measurement to determine which best predicts residual disease on completion axillary lymph node dissection (cALND). METHODS: A total of 505 patients with invasive breast cancer and minimal SLN metastasis (pN1mi or pN0(i+)) underwent cALND and had complete data. All SLNs were evaluated by three measurement methods for volume of metastasis: (1) method of detection (frozen section, routine hematoxylin and eosin, serial hematoxylin and eosin, immunohistochemistry), (2) American Joint Committee on Cancer's AJCC Cancer Staging Manual, 7th edition, N category, and (3) number of metastatic cells (1-100, 101-999, >/=1000). Multivariable logistic regression models were used to predict the presence of additional non-SLN disease. RESULTS: A total of 251 patients (50%) had pN0(i+) and 254 patients (50%) had pN1mi disease. Twelve percent of those with pN0(i+) and 20% with pN1mi had additional non-SLN disease. On multivariate analyses including eight variables, only lymphovascular invasion (odds ratio >2.2, P < 0.01) and volume of nodal metastasis as assessed by any method of measurement (method of detection, AJCC, and cell count) were significantly correlated with additional non-SLN disease (P = 0.04, 0.03, and 0.02, respectively). All three models had similar goodness of fit and discrimination (Akaike information criterion = 442, 442, 441; -2log likelihood = 416, 420, 417; concordance index = 0.680, 0.675, 0.676, respectively). CONCLUSIONS: A significant proportion of women with minimal SLN metastases have additional non-SLN disease at cALND. Assessments of SLN volume of disease by three different methods of measurement are equivalent for prediction of additional non-SLN metastases.
机译:背景:前哨淋巴结(SLN)中的疾病量是其他淋巴结转移的重要预测指标。这项研究评估了大量SLN转移最少的女性队列中残留非SLN疾病的发生率,并比较了三种SLN微转移量测量方法,以确定哪种方法可以最好地预测完成腋窝淋巴结清扫术(cALND)时的残留疾病。方法:共有505例浸润性乳腺癌和最小的SLN转移(pN1mi或pN0(i +))患者接受了cALND评估并获得了完整的数据。所有SLN均通过三种测量转移体积的方法进行评估:(1)检测方法(冷冻切片,常规苏木精和曙红,系列苏木精和曙红,免疫组化),(2)美国癌症联合委员会AJCC癌症分期手册,第7版版本,N类和(3)转移细胞数(1-100、101-999,> / = 1000)。多变量逻辑回归模型用于预测其他非SLN疾病的存在。结果:共有251例患者(50%)患有pN0(i +),而254例患者(50%)患有pN1mi疾病。患有pN0(i +)的患者中有12%,患有pN1mi的患者中有20%患有其他非SLN疾病。在包括8个变量的多变量分析中,只有通过任何测量方法(检测方法,AJCC和细胞计数)评估的淋巴管浸润(比值> 2.2,P <0.01)和淋巴结转移量与其他非淋巴结转移密切相关。 SLN疾病(分别为P = 0.04、0.03和0.02)。这三个模型都具有相似的拟合度和区分度(Akaike信息准则= 442、442、441; -2对数似然度分别为416、420、417;一致​​性指数分别为0.680、0.675和0.676)。结论:大量患有SLN转移最少的女性在cALND时有其他非SLN疾病。通过三种不同的测量方法对SLN疾病量的评估等效于预测其他非SLN转移。

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