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预测中国西南部老年黏液性乳腺癌女性患者结局的列线图:一项回顾性研究并外部验证

Nomogram for predicting outcomes in elderly women with mucinous breast cancer: A retrospective study combined with external validation in southwest China.

机构信息

Department of Urology; Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering; Chongqing Key Laboratory of Pediatrics; Ministry of Education Key Laboratory of Child Development and Disorders; National Clinical Research Center for Child Health and Disorders; China International Science and Technology Cooperation base of Child development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, People's Republic of China.

Department of Cardiothoracic Surgery, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation Base of Child Development and Critical Disorders, Children's Hospital of Chongqing Medical University, Chongqing, China.

出版信息

Cancer Rep (Hoboken). 2024 Jul;7(7):e2112. doi: 10.1002/cnr2.2112.

DOI:10.1002/cnr2.2112
PMID:39051553
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11270325/
Abstract

OBJECTIVE

Mucinous breast cancer (MBC) is a kind of breast cancer (BC), which is rare in clinic, mainly for women, because of the low incidence rate, so there is no unified standard treatment protocol. Elderly patients have a poor prognosis due to their combined comorbidities. This study aims to investigate the effect of surgery and chemoradiotherapy on the prognosis of elderly female MBC patients and construct nomograms for predicting the OS and CSS in elderly female MBC patients.

METHODS

Data for female MBC patients over 65 years are obtained from the Surveillance, Epidemiology and End Results (SEER) database, patients were divided into two groups: the training set and the validation set. External validation data of the prediction model were provided by Kunming Hospital of Traditional Chinese Medicine. We used Cox regression modeling, which was used to identify independent risk factors affecting patient prognosis. After avoiding confounding bias according to the multifactorial Cox regression model, we used these screened statistically significant results to construct column-line plots. The performance of the model was tested using the consistency index (c-index), the calibration curve, and the area under the operating characteristic curve of the receiver (AUC). Subsequently, we used decision curve analysis (DCA) to examine the potential clinical value of our nomograms.

RESULTS

A total of 8103 elderly MBC female patients were extracted from the database SEER and were assigned to the training and validation set, randomly. A total of 83 patients from Kunming Hospital of Traditional Chinese Medicine were used in the external verification set. After multifactorial Cox regression analysis, we found that age, race, T-stage, M-stage, surgical approach, radiotherapy, and tumor size were independent risk factors for OS in elderly MBC patients. Similarly, independent risk factors of CSS included age, marital status, N stage, M stage, surgical approach, chemotherapy, and tumor size. The C-index for the OS training, validation, and external verification set were 0.731 (95%CI 0.715-0.747), 0.738 (95%CI 0.724-0.752), and 0.809 (95%CI 0.731-0.8874). The C-index of the training set, the validation set, and external verification set for CSS were 0.786 (95%CI 0.747-0.825), 0.776 (95%CI 0.737-0.815), and 0.84 (95%CI0.754-0.926), respectively. The AUC, calibration curves and DCA also showed good accuracy.

CONCLUSIONS

In this study, we construct a new nomogram to predict the prognosis of elderly patients with MBC. The nomograms have undergone internal and external validation and have been confirmed to have good clinical applicability. At the same time, we found that for elderly female MBC patients, surgery and radiotherapy significantly benefit their survival, but chemotherapy is not conducive to patient survival.

摘要

目的

黏液性乳腺癌(MBC)是一种罕见的乳腺癌(BC),主要发生于女性,由于发病率低,因此没有统一的标准治疗方案。老年患者由于合并多种合并症,预后较差。本研究旨在探讨手术和放化疗对老年女性 MBC 患者预后的影响,并构建预测老年女性 MBC 患者总生存期(OS)和无病生存期(CSS)的列线图。

方法

从监测、流行病学和最终结果(SEER)数据库中获取 65 岁以上女性 MBC 患者的数据,将患者分为两组:训练集和验证集。预测模型的外部验证数据由昆明中医院提供。我们使用 Cox 回归模型来识别影响患者预后的独立危险因素。根据多因素 Cox 回归模型避免混杂偏倚后,我们使用这些筛选出的具有统计学意义的结果构建列线图。使用一致性指数(c-index)、校准曲线和接收者工作特征曲线下的面积(AUC)来测试模型的性能。随后,我们使用决策曲线分析(DCA)来评估我们的列线图的潜在临床价值。

结果

从 SEER 数据库中提取了 8103 名老年 MBC 女性患者,并随机分配到训练集和验证集。昆明中医院共 83 例患者用于外部验证集。经过多因素 Cox 回归分析,我们发现年龄、种族、T 期、M 期、手术方式、放疗和肿瘤大小是老年 MBC 患者 OS 的独立危险因素。同样,CSS 的独立危险因素包括年龄、婚姻状况、N 期、M 期、手术方式、化疗和肿瘤大小。OS 的训练、验证和外部验证集的 C 指数分别为 0.731(95%CI 0.715-0.747)、0.738(95%CI 0.724-0.752)和 0.809(95%CI 0.731-0.8874)。CSS 的训练集、验证集和外部验证集的 C 指数分别为 0.786(95%CI 0.747-0.825)、0.776(95%CI 0.737-0.815)和 0.84(95%CI0.754-0.926)。AUC、校准曲线和 DCA 也显示出良好的准确性。

结论

本研究构建了一种新的列线图来预测老年 MBC 患者的预后。该列线图经过内部和外部验证,被证实具有良好的临床适用性。同时,我们发现对于老年女性 MBC 患者,手术和放疗明显有益于其生存,但化疗不利于患者生存。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/7cdd744ae199/CNR2-7-e2112-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/53b8435ef63a/CNR2-7-e2112-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/4890b49f3f4f/CNR2-7-e2112-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/576c7382b9fa/CNR2-7-e2112-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/7f770ec8a678/CNR2-7-e2112-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/3486dfb7bba3/CNR2-7-e2112-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/6f6c2816c151/CNR2-7-e2112-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/7c8d348231ab/CNR2-7-e2112-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/7cdd744ae199/CNR2-7-e2112-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/53b8435ef63a/CNR2-7-e2112-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/4890b49f3f4f/CNR2-7-e2112-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/576c7382b9fa/CNR2-7-e2112-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/7f770ec8a678/CNR2-7-e2112-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/3486dfb7bba3/CNR2-7-e2112-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/6f6c2816c151/CNR2-7-e2112-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/7c8d348231ab/CNR2-7-e2112-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/65bf/11270325/7cdd744ae199/CNR2-7-e2112-g006.jpg

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