Department of Breast Radiotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China.
Department of Radiotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China.
Clin Breast Cancer. 2021 Aug;21(4):e368-e376. doi: 10.1016/j.clbc.2020.12.003. Epub 2020 Dec 16.
The risk of locoregional recurrence (LRR) after mastectomy for breast invasive micropapillary carcinoma (IMPC) remains poorly defined. We aimed to construct an effective prognostic nomogram to estimate the individualized risk of LRR for providing accurate information for long-term follow-up.
A total of 388 patients with breast IMPC were included in the current study. Based on the Cox regression and clinical significance, a nomogram with an online prediction version was created. This model was evaluated and internally validated by concordance index and calibration plot. Receiver operating characteristic curve and decision curve analysis were used to assess the discrimination and clinical utility, and Kaplan-Meier curves estimated the probability of LRR.
The variables (age, lymph node metastasis, hormone receptor status, lymphovascular invasion, histologic grade, and adjuvant radiotherapy) were included in the nomogram. This model was well-calibrated to predict the possibility of LRR and displayed favorable clinical utility; the concordance index was 0.86 (95% confidence interval, 0.81-0.91), which was higher than any single predictor. The area under the curve of the nomogram was 0.89, whereas that of the conventional staging system was 0.72. An online prognostic nomogram was built for convenient use. Kaplan-Meier curves showed that the nomogram had a better risk stratification than the conventional staging system.
The nomogram could accurately predict the individualized risk of LRR after mastectomy for breast IMPC. By identifying the risk stratification, this model is expected to assist clinicians and patients in improving long-term follow-up strategies.
乳腺癌浸润性微乳头状癌（IMPC）行乳房切除术患者的局部区域复发（LRR）风险仍定义不明确。我们旨在构建有效的预后列线图来估计 LRR 的个体风险，从而为长期随访提供准确信息。
本研究共纳入 388 例 IMPC 患者。基于 Cox 回归和临床意义，构建了列线图和在线预测版本。通过一致性指数和校准图评估该模型，并进行内部验证。采用接受者操作特征曲线和决策曲线分析评估区分度和临床实用性，通过 Kaplan-Meier 曲线估计 LRR 概率。
该列线图纳入年龄、淋巴结转移、激素受体状态、脉管侵犯、组织学分级和辅助放疗等变量。该模型对 LRR 可能性的预测具有良好的校准能力，显示出良好的临床实用性；一致性指数为 0.86（95%置信区间，0.81-0.91），高于任何单一预测因子。列线图的曲线下面积为 0.89，而传统分期系统为 0.72。为方便使用，构建了在线预后列线图。Kaplan-Meier 曲线显示，该列线图的风险分层优于传统分期系统。
列线图可准确预测 IMPC 行乳房切除术患者的 LRR 个体风险。通过识别风险分层，该模型有望帮助临床医生和患者改善长期随访策略。
