Department of Pathology, The Third Affiliated Hospital, Zhengzhou University, Zhengzhou, 450052, China.
Department of Pathology, The Third Affiliated Hospital, Zhengzhou University, Zhengzhou, 450052, China.
Asian J Surg. 2023 Sep;46(9):3734-3740. doi: 10.1016/j.asjsur.2023.02.090. Epub 2023 Mar 16.
Invasive micropapillary carcinoma (IMPC) is a rare subtype of breast cancer that lacks a prognostic prediction model. Its treatment and prognostic factors remain controversial. Our study aimed to develop nomograms to predict overall survival (OS) and cancer-specific survival (CSS) in IMPC patients.
A total of 2149 patients confirmed to have IMPC between 2003 and 2018 were selected from the Surveillance, Epidemiology and End Results (SEER) database. They were divided into training and validation cohorts. Univariate and multivariate Cox regression analyses were used to identify significant independent prognostic factors. The nomograms were used to predict 3- and 5-year OS and CSS. The training and validation cohorts were used to verify the nomograms internally and externally. The predictive capability of the nomograms was evaluated by the consistency index (C-index), calibration curve, receiver operating characteristic (ROC) curve and decision curve analysis (DCA) curve.
In the study, 2149 IMPC patients were randomized to a training group (n = 1611) and a validation group (n = 538). Age, T stage, N stage, ER, radiotherapy, and surgery were identified as independent prognostic factors for OS and CSS. These variables were selected to construct nomograms for IMPC. The C-index (0.768 for OS and 0.811 for CSS) and the time-dependent AUC (>0.7) indicated satisfactory discriminative ability of the nomograms. Additionally, DCA showed that the nomograms had higher clinical value than traditional TNM tumor staging.
The models can accurately predict the prognosis of IMPC patients and can aid in providing individualized treatment for patients.
浸润性微乳头状癌(IMPC)是一种罕见的乳腺癌亚型,缺乏预后预测模型。其治疗和预后因素仍存在争议。本研究旨在建立诺莫图以预测 IMPC 患者的总生存(OS)和癌症特异性生存(CSS)。
从监测、流行病学和最终结果(SEER)数据库中选择了 2003 年至 2018 年间确诊为 IMPC 的 2149 例患者。将其分为训练和验证队列。采用单因素和多因素 Cox 回归分析确定显著的独立预后因素。使用诺莫图预测 3 年和 5 年 OS 和 CSS。使用训练和验证队列内部和外部验证诺莫图。通过一致性指数(C-index)、校准曲线、接收者操作特征(ROC)曲线和决策曲线分析(DCA)曲线评估诺莫图的预测能力。
本研究中,2149 例 IMPC 患者被随机分配到训练组(n=1611)和验证组(n=538)。年龄、T 分期、N 分期、ER、放疗和手术被确定为 OS 和 CSS 的独立预后因素。这些变量被选择用于构建 IMPC 的诺莫图。C-index(OS 为 0.768,CSS 为 0.811)和时间依赖性 AUC(>0.7)表明诺莫图具有良好的区分能力。此外,DCA 表明诺莫图比传统的 TNM 肿瘤分期具有更高的临床价值。
该模型可准确预测 IMPC 患者的预后,并有助于为患者提供个体化治疗。