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一种用于识别非转移性男性乳腺癌中可能从化疗中获益人群的风险分层模型的开发、验证及比较。

Development, verification, and comparison of a risk stratification model to identify potential population benefiting from chemotherapy in non-metastatic male breast cancer.

作者信息

Zhang Mingkun, Yao Qing, Qin Yuan, Hou Niuniu, Tang Xueyuan, Zhang Juliang

机构信息

Department of Thyroid, Breast and Vascular Surgery, Xijing Hospital, The Fourth Military Medical University, Xi'an, 710032, Shanxi, People's Republic of China.

Department of General Surgery, Air Force 986(Th) Hospital, Fourth Military Medical University, Xi'an, 710032, Shaanxi, People's Republic of China.

出版信息

Sci Rep. 2025 Jul 7;15(1):24301. doi: 10.1038/s41598-025-08440-1.

DOI:10.1038/s41598-025-08440-1
PMID:40624063
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12234949/
Abstract

To establish a prognostic stratification nomogram for non-metastatic male breast cancer to determine which patients can benefit from chemotherapy. A population-based study was conducted using data collected from the surveillance, epidemiology, and end results database. Cox proportional hazards analysis identified significant prognostic factors for survival. A prognostic stratification model was developed using R software. Propensity score matching was implemented to balance characteristics between the chemotherapy cohort and the non-chemotherapy cohort. The multivariate analyses indicated that age, race, grade, surgery, primary tumor, marital status, T stage, and N stage were independent prognostic factors for overall survival in non-metastatic metastatic MBC patients who did not receive chemotherapy (all P < 0.05). The C-index was 0.786 (95% CI 0.662-0.870) in the training cohort and 0.763 (95% CI 0.517-0.852) in the validation cohort. The nomogram effectively discriminated between low-risk, moderate-risk, and high-risk groups concerning OS (P < 0.0001). The current study developed the first prognostic stratification nomogram for non-metastatic MBC and identified that patients in the moderate-risk and high-risk groups are more likely to benefit from chemotherapy.

摘要

建立非转移性男性乳腺癌的预后分层列线图，以确定哪些患者能从化疗中获益。利用从监测、流行病学和最终结果数据库收集的数据进行了一项基于人群的研究。Cox比例风险分析确定了生存的显著预后因素。使用R软件开发了一个预后分层模型。实施倾向得分匹配以平衡化疗队列和非化疗队列之间的特征。多变量分析表明，年龄、种族、分级、手术、原发肿瘤、婚姻状况、T分期和N分期是未接受化疗的非转移性MBC患者总生存的独立预后因素（所有P<0.05）。训练队列中的C指数为0.786（95%CI 0.662-0.870），验证队列中的C指数为0.763（95%CI 0.517-0.852）。该列线图在总生存方面有效地区分了低风险、中度风险和高风险组（P<0.0001）。本研究开发了首个非转移性MBC的预后分层列线图，并确定中度风险和高风险组的患者更有可能从化疗中获益。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a024/12234949/a4b80b315217/41598_2025_8440_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a024/12234949/047c9b91e741/41598_2025_8440_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a024/12234949/07af123fbaf0/41598_2025_8440_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a024/12234949/3f703cad5138/41598_2025_8440_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a024/12234949/71c9f54a5327/41598_2025_8440_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a024/12234949/8ea0057cc32d/41598_2025_8440_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a024/12234949/a4b80b315217/41598_2025_8440_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a024/12234949/047c9b91e741/41598_2025_8440_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a024/12234949/07af123fbaf0/41598_2025_8440_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a024/12234949/3f703cad5138/41598_2025_8440_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a024/12234949/71c9f54a5327/41598_2025_8440_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a024/12234949/8ea0057cc32d/41598_2025_8440_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a024/12234949/a4b80b315217/41598_2025_8440_Fig6_HTML.jpg

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Development, verification, and comparison of a risk stratification model to identify potential population benefiting from chemotherapy in non-metastatic male breast cancer.

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本文引用的文献

[1]
-associated hereditary male cancers: can gender affect the prevalence and spectrum of germline pathogenic variants?

Front Oncol. 2024-6-21

[2]
A novel nomogram and survival analysis for different lymph node status in breast cancer based on the SEER database.

Breast Cancer. 2024-9

[3]
Prediction of a Multi-Gene Assay (Oncotype DX and Mammaprint) Recurrence Risk Group Using Machine Learning in Estrogen Receptor-Positive, HER2-Negative Breast Cancer-The BRAIN Study.

Cancers (Basel). 2024-2-13

[4]
Budget Impact of the Oncotype DX Breast Recurrence Score Test in Patients with Early Primary Hormone-Receptor-Positive, HER2-Negative, Node-Positive Breast Cancer in Germany.

Breast Care (Basel). 2024-2

[5]
21-gene recurrence score in predicting the outcome of postoperative radiotherapy in T1-2N1 luminal breast cancer after breast-conserving surgery.

Breast. 2024-4

[6]
Anatomy Versus Biology: What Guides Chemotherapy Decisions in Older Patients With Breast Cancer?

J Surg Res. 2024-4

[7]
Male Breast Cancer: a Review on Diagnosis, Treatment, and Survivorship.

Curr Oncol Rep. 2024-1

[8]
Male Breast: A Review of the Literature and Current State of the Art of Diagnostic Imaging Work-Up.

Diagnostics (Basel). 2023-12-7

[9]
Clinical, Pathological, and Prognostic Features of Male Breast Cancer: A Multicenter Study.

Curr Oncol. 2023-11-11

[10]
Prediction models for hormone receptor status in female breast cancer do not extend to males: further evidence of sex-based disparity in breast cancer.

NPJ Breast Cancer. 2023-11-8

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