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Validation of nomograms to predict the risk of non-sentinels lymph node metastases in North African Tunisian breast cancer patients with sentinel node involvement.

机译:诺模图验证可预测前哨淋巴结受累的北非突尼斯乳腺癌患者发生非前哨淋巴结转移的风险。

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INTRODUCTION: In approximately half of patients with breast cancer and lymph node metastases, the sentinel node (SN) is the only involved axillary node. Scoring systems have been developed to predict probability of non-SN metastases among those with a positive SN. The goal of the present study was to determine whether the five models (Memorial Sloan-Kettering Cancer Center (MSKCC), Stanford, Tenon, Cambridge and the Turkish model) accurately predicted non-SN involvement in a North African Tunisian population. METHODS: During a five years period, we identified 87 cases of invasive breast cancer which had a positive SN biopsy and complete axillary lymph node dissection (CALND). The MSKCC, Stanford, Tenon, Cambridge and Turkish models were tested. Results were compared using the area under the curve (AUC) of the receiver operating characteristics for each model. False negative and false positive rates were also calculated. RESULTS: The AUC of the MSKCC, Stanford, Tenon, Cambridge and Turkish models was respectively 0.73 (95% CI 0.6-0.86), 0.76 (95% CI 0.65-0.87), 0.75 (95% CI 0.63-0.87), 0.67 (95% CI 0.53-0.82) and 0.75 (95% CI 0.63-0.88). The threshold for a 10% false negative of non-SN involvement was obtained with a cut off value of 10% for MSKCC, 25% for Stanford, a score of 3 for Tenon, 6% for Cambridge and 15% for the Turkish nomogram. CONCLUSIONS: Meaningfully applied to our population, although AUC values had overlapping of 95% confidence intervals but combined our data suggest that the Stanford nomogram may be the most accurate. Before prospective trials validate these nomograms, CALND remains the standard for patients who have SN metastases.
机译:简介:在大约一半患有乳腺癌和淋巴结转移的患者中,前哨淋巴结(SN)是唯一受累的腋窝淋巴结。已经开发了计分系统以预测具有阳性SN的患者中非SN转移的可能性。本研究的目的是确定五个模型(斯隆-凯特琳纪念癌症中心(MSKCC),斯坦福大学,特农大学,剑桥大学和土耳其大学的模型)是否准确预测了北非突尼斯人口中的非SN感染。方法:在五年的时间里,我们确定了87例浸润性乳腺癌患者,这些患者的SN活检阳性并且完成了腋窝淋巴结清扫术(CALND)。测试了MSKCC,斯坦福大学,Tenon大学,剑桥大学和土耳其大学的模型。使用每个模型的接收器工作特性曲线下面积(AUC)比较结果。还计算了假阴性和假阳性率。结果:MSKCC,斯坦福,特农,剑桥和土耳其模型的AUC分别为0.73(95%CI 0.6-0.86),0.76(95%CI 0.65-0.87),0.75(95%CI 0.63-0.87),0.67( 95%CI 0.53-0.82)和0.75(95%CI 0.63-0.88)。获得了10%的非SN假阴性阈值,MSKCC的截止值为10%,斯坦福的截止值为25%,Tenon的得分为3,Cambridge的得分为6%,土耳其列线图的得分为15%。结论:尽管AUC值具有95%的置信区间重叠,但有意义地适用于我们的人群,但结合我们的数据表明,斯坦福列线图可能是最准确的。在前瞻性试验验证这些诺模图之前,CALND仍然是患有SN转移的患者的标准。

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