Zhao Yuting, Li Shouyu, Yan Lutong, Yang Zejian, Chai Na, Qiu Pei, Zhang Jian, Zhang Huimin, He Jianjun, Zhou Can
Department of Breast Surgery, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
School of Medicine, Xi'an Jiaotong University, Xi'an, China.
Front Surg. 2022 Oct 21;9:1009149. doi: 10.3389/fsurg.2022.1009149. eCollection 2022.
Due to the loss of prediction of overall survival (OS) for patients with invasive micropapillary carcinoma (IMPC) after breast-conserving surgery (BCS), this study aimed to construct a nomogram for predicting OS in IMPC patients after BCS.
In total, 481 eligible cases staged 0-III IMPC from 2000 to 2016 were retrieved from the SEER database. A nomogram was built based on the variables selected by LASSO regression to predict the 3-year and 5-year probabilities of OS.
A total of 336 patients were randomly assigned to the training cohort and 145 cases in the validation cohort. The LASSO regression revealed that six variables (age at diagnosis, AJCC stage, marital status, ER status, PR status, and chemotherapy) were predictive variables of OS, and then a nomogram model and an easy-to-use online tool were constructed. The C-indices 0.771 in the training cohort and 0.715 in the validation cohort suggested the robustness of the model. The AUC values for 3-year and 5-year OS in the training cohort were 0.782, 0.790, and 0.674, and 0.682 in the validation cohort, respectively. Based on the cutoff values of 147.23 and 222.44 scores calculated by X-tile analysis, participants in the low-risk group (≤147.23 scores) had a more favorable OS in comparison with those in the medium (>147.23, but <222.44 scores)- and high-risk groups (≥222.44 scores).
By risk stratification, this model is expected to provide a precise and personalized prediction of the cumulative risk and guide treatment decision-making in improving OS strategies for IMPC patients.
由于保乳手术（BCS）后浸润性微乳头状癌（IMPC）患者总生存期（OS）预测的缺失，本研究旨在构建一个预测BCS后IMPC患者OS的列线图。
从监测、流行病学与最终结果（SEER）数据库中检索出2000年至2016年期间分期为0-III期的481例符合条件的IMPC病例。基于通过套索回归选择的变量构建列线图，以预测OS的3年和5年概率。
总共336例患者被随机分配到训练队列，145例在验证队列。套索回归显示六个变量（诊断时年龄、美国癌症联合委员会（AJCC）分期、婚姻状况、雌激素受体（ER）状态、孕激素受体（PR）状态和化疗）是OS的预测变量，然后构建了一个列线图模型和一个易于使用的在线工具。训练队列中的一致性指数（C指数）为0.771，验证队列中为0.715，表明该模型的稳健性。训练队列中3年和5年OS的曲线下面积（AUC）值分别为0.782、0.790，验证队列中分别为0.674和0.682。根据X-tile分析计算的147.23分和222.44分的临界值，低风险组（≤147.23分）的参与者与中风险组（>147.23分但<222.44分）和高风险组（≥222.44分）相比，OS更有利。
通过风险分层，该模型有望为IMPC患者改善OS策略提供累积风险的精确和个性化预测，并指导治疗决策。
