首页> 外文期刊>Annals of Surgery >Incorporation of sentinel lymph node metastasis size into a nomogram predicting nonsentinel lymph node involvement in breast cancer patients with a positive sentinel lymph node.
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Incorporation of sentinel lymph node metastasis size into a nomogram predicting nonsentinel lymph node involvement in breast cancer patients with a positive sentinel lymph node.

机译:将前哨淋巴结转移大小纳入诺模图,以预测前哨淋巴结阳性的乳腺癌患者的非前哨淋巴结受累。

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BACKGROUND AND OBJECTIVE: Sentinel lymph node (SLN) metastasis size is an important predictor of non-SLN involvement. The goal of this study was to construct a nomogram incorporating SLN metastasis size to accurately predict non-SLN involvement in patients with SLN-positive disease. METHODS: We identified 509 patients with invasive breast cancer with a positive SLN who underwent completion axillary lymph node dissection (ALND). Clinicopathologic data including age, tumor size, histology, grade, presence of multifocal disease, estrogen and progesterone receptor status, HER2eu status, presence of lymphovascular invasion (LVI), number of SLN(s) identified, number of positive SLN(s), maximum SLN metastasis size and the presence of extranodal extension were recorded. Univariate and multivariate logistic regression analyses identified factors predictive of positive non-SLNs. Using these variables, a nomogram was constructed and subsequently validated using an external cohort of 464 patients. RESULTS: On univariate analysis, the following factors were predictive of positive non-SLNs: number of SLN identified (P < 0.001), number of positive SLN (P < 0.001), SLN metastasis size (P < 0.001), extranodal extension (P < 0.001), tumor size (P = 0.001), LVI (P = 0.019), and histology (P = 0.034). On multivariate analysis, all factors remained significant except LVI. A nomogram was created using these variables (AUC = 0.80; 95% CI, 0.75-0.84). When applied to an external cohort, the nomogram was accurate and discriminating with an AUC = 0.74 (95% CI, 0.68-0.77). CONCLUSION: SLN metastasis size is an important predictor for identifying non-SLN disease. In this study, we incorporated SLN metastasis size into a nomogram that accurately predicts the likelihood of having additional axillary metastasis and can assist in personalizing surgical management of breast cancer.
机译:背景与目的:前哨淋巴结(SLN)转移的大小是非SLN参与的重要预测指标。这项研究的目的是构建一个包含SLN转移大小的列线图,以准确预测SLN阳性疾病患者中非SLN的受累情况。方法:我们确定了509例SLN阳性的浸润性乳腺癌患者,他们均接受了腋窝淋巴结清扫术(ALND)。临床病理数据包括年龄,肿瘤大小,组织学,等级,多灶性疾病的存在,雌激素和孕激素受体的状态,HER2 / neu状态,淋巴管浸润(LVI)的存在,已鉴定的SLN的数量,阳性SLN的数量),记录最大SLN转移大小和结外扩展的存在。单因素和多因素逻辑回归分析确定了预测非SLN阳性的因素。使用这些变量,构造了诺模图,随后使用464位患者的外部队列进行了验证。结果:在单因素分析中,以下因素可预测非SLN阳性:已鉴定的SLN数目(P <0.001),SLN阳性数目(P <0.001),SLN转移大小(P <0.001),结外扩展(P <0.001),肿瘤大小(P = 0.001),LVI(P = 0.019)和组织学(P = 0.034)。在多变量分析中,除LVI外,所有因素均保持显着水平。使用这些变量(AUC = 0.80; 95%CI,0.75-0.84)创建了列线图。当应用于外部队列时,列线图是准确的,并且可以用AUC = 0.74(95%CI,0.68-0.77)进行区分。结论:SLN转移大小是识别非SLN疾病的重要预测指标。在这项研究中,我们将SLN转移量纳入了诺模图,以准确预测发生额外腋窝转移的可能性,并有助于个性化乳腺癌的外科治疗。

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