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新辅助化疗后接受保乳手术的原发性乳腺癌患者局部区域复发预测的列线图。

A nomogram for predicting locoregional recurrence in primary breast cancer patients who received breast-conserving surgery after neoadjuvant chemotherapy.

机构信息

Department of Breast Surgical Oncology, St. Luke's International Hospital, Tokyo, Japan.

出版信息

J Surg Oncol. 2014 Jun;109(8):764-9. doi: 10.1002/jso.23586. Epub 2014 Mar 20.

Abstract

BACKGROUND

We sought to develop and validate a predictive model of locoregional recurrence (LRR) in patients who underwent breast-conserving therapy (BCT) after neoadjuvant chemotherapy (NAC).

PATIENTS AND METHODS

The clinicopathological characteristics of 520 consecutive primary breast cancer patients with residual tumor who underwent BCT after NAC between 2001 and 2008 were evaluated. Predictive variables of LRR were determined using a multivariate Cox proportional hazards model. The model was validated for discrimination and calibration by bootstrap re-sampling.

RESULTS

At a median follow-up period of 51 months, 64 patients (12%) had developed LRR. Clinical stage T3 or T4, lymphovascular invasion, nuclear grade >3, and ≥4 positive lymph nodes metastasis were positively correlated with LRR. The nomogram for predicting LRR developed by using these four-clinicopathologic variables demonstrated high concordance. Patients with score 0-1 derived by the prediction model had significantly low LRR rate compared with patients with score 2 or higher (P < 0.001).

CONCLUSIONS

This nomogram may be useful to predict LRR in primary breast cancer patients who underwent BCT after NAC with high reproducibility. This model is useful to conduct a study-identifying patients who may need an additional treatment to standard adjuvant therapy because of a high probability of LRR.

摘要

背景

我们旨在开发和验证接受新辅助化疗(NAC)后保乳治疗(BCT)的患者局部区域复发(LRR)的预测模型。

患者与方法

评估了 2001 年至 2008 年间接受 NAC 后接受 BCT 的 520 例原发性乳腺癌患者的临床病理特征。使用多变量 Cox 比例风险模型确定 LRR 的预测变量。通过自举重采样验证模型的区分度和校准度。

结果

在中位随访 51 个月期间,64 例患者(12%)发生 LRR。临床分期 T3 或 T4、脉管侵犯、核分级>3 和≥4 个阳性淋巴结转移与 LRR 呈正相关。使用这四个临床病理变量开发的预测 LRR 的列线图显示出高度一致性。与评分 2 或更高的患者相比,评分 0-1 的患者 LRR 发生率显著降低(P<0.001)。

结论

该列线图可用于预测接受 NAC 后接受 BCT 的原发性乳腺癌患者的 LRR,具有较高的可重复性。该模型可用于开展研究,确定因 LRR 概率高而可能需要标准辅助治疗以外的额外治疗的患者。

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