Charles University, Prague, Czech Republic.
Neoplasma. 2013;60(3):334-42. doi: 10.4149/neo_2013_045.
The aim of this study is to determine the combination of characteristics in early breast cancer that could estimate the risk of occurrence of metastatic cells in axillary sentinel lymph node(s). If we were able to reliably predict the presence or absence of axillary sentinel involvement, we could spare a considerable proportion of patients from axillary surgery without compromising therapeutic outcomes of their disease. The study is based on retrospective analysis of medical records of 170 patients diagnosed with primary breast cancer. These women underwent primary surgery of the breast and axilla in which at least one sentinel lymph node was obtained. Logistic regression has been employed to construct a model predicting axillary sentinel lymph node involvement using preoperative and postoperative tumor characteristics. Postoperative model uses tumor features obtained from definitive histology samples. Its predictive capability expressed by receiver operating characteristic curve is good, area under curve (AUC) equals to 0.78. The comparison between preoperative and postoperative results showed the only significant differences in values of histopathological grading; we have considered grading not reliably stated before surgery. In preoperative model only the characteristics available and reliably stated at the time of diagnoses were used. The predictive capability of this model is only fair when using the data available at the time of diagnosis (AUC = 0.66). We conclude, that predictive models based on postoperative values enable to reliably estimate the likelihood of occurrence of axillary sentinel node(s) metastases. This can be used in clinical practice in case surgical procedure is divided into two steps, breast surgery first and axillary surgery thereafter. Even if preoperative values were not significantly different from postoperative ones (except for grading), the preoperative model predictive capability is lower compared to postoperative values. The reason for this worse prediction was identified in imperfect preoperative diagnostic.
本研究旨在确定早期乳腺癌的特征组合，以估计腋窝前哨淋巴结中转移性细胞发生的风险。如果我们能够可靠地预测腋窝前哨淋巴结的存在或不存在，我们可以避免相当一部分患者接受腋窝手术，而不会影响他们疾病的治疗效果。该研究基于对 170 例原发性乳腺癌患者病历的回顾性分析。这些女性接受了乳房和腋窝的原发性手术，其中至少获得了一个前哨淋巴结。逻辑回归已被用于构建使用术前和术后肿瘤特征预测腋窝前哨淋巴结受累的模型。术后模型使用从明确组织学样本中获得的肿瘤特征。其通过接收者操作特征曲线表示的预测能力良好，曲线下面积（AUC）等于 0.78。术前和术后结果的比较显示，只有组织病理学分级的值存在显著差异；我们认为术前分级不可靠。在术前模型中，仅使用在诊断时可用且可靠的特征。当使用诊断时可用的数据时，该模型的预测能力仅为中等（AUC = 0.66）。我们得出结论，基于术后值的预测模型能够可靠地估计腋窝前哨淋巴结转移的发生可能性。这可以在临床实践中使用，如果手术程序分为两步进行，先进行乳房手术，然后再进行腋窝手术。即使术前值与术后值没有显著差异（除了分级），术前模型的预测能力也低于术后值。这种预测能力较差的原因是术前诊断不完善。
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