Hu Tingting, Huang Juanjuan, Fang Kun
Department of Chemoradiation Oncology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, People's Republic of China.
Wenzhou Medical University, Wenzhou, Zhejiang, 325000, People's Republic of China.
Int J Gen Med. 2021 Dec 18;14:9991-10001. doi: 10.2147/IJGM.S343137. eCollection 2021.
Mucinous carcinoma of the breast (MCB) is a rare malignant tumour. Therefore, it is urgent to establish a survival prediction model for MCB patients.
Clinicopathological and follow-up data of MCB patients diagnosed between 2010 and 2015 were retrieved from the Surveillance, Epidemiology, and End Result (SEER) database. The significant factors were screened out and generated Kaplan-Meier (K-M) curves for each prognostic factor. Additionally, these factors were then utilized to build a nomogram for predicting 3-, 4-, and 5-year overall survival (OS) of MCB patients. The nomogram was evaluated using calibration curves, receiver operating characteristic (ROC) curves and decision curve analysis (DCA).
Moreover, a total of 4326 MCB patients were retrieved. Age, American Joint Committee on Cancer (AJCC) stage, surgery, radiotherapy and bone metastasis were identified as independently prognosis factors for OS. The corresponding areas under the ROC curves (AUCs) of the nomogram at 3, 4 and 5 years in the training and validation set were 0.770, 0.788, 0.805, 0.778, 0.797, and 0.802, respectively. The calibration curves and DCA revealed that the prediction model had an excellent performance. Finally, the risk stratification system confirmed that the powerful role of the nomogram in distinguishing results and risk stratification.
Briefly, the nomogram incorporating various clinicopathological indicators was established for MCB patients and may facilitate clinical decision-making.
乳腺黏液癌（MCB）是一种罕见的恶性肿瘤。因此，为MCB患者建立生存预测模型迫在眉睫。
从监测、流行病学和最终结果（SEER）数据库中检索2010年至2015年诊断的MCB患者的临床病理和随访数据。筛选出显著因素，并为每个预后因素生成Kaplan-Meier（K-M）曲线。此外，然后利用这些因素构建一个列线图，用于预测MCB患者3年、4年和5年的总生存期（OS）。使用校准曲线、受试者工作特征（ROC）曲线和决策曲线分析（DCA）对列线图进行评估。
此外，共检索到4326例MCB患者。年龄、美国癌症联合委员会（AJCC）分期、手术、放疗和骨转移被确定为OS的独立预后因素。训练集和验证集中列线图在3年、4年和5年时的ROC曲线下面积（AUC）分别为0.770、0.788、0.805、0.778、0.797和0.802。校准曲线和DCA显示预测模型具有良好的性能。最后，风险分层系统证实了列线图在区分结果和风险分层方面的强大作用。
简而言之，为MCB患者建立了包含各种临床病理指标的列线图，可能有助于临床决策。
