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Background <p>Male breast cancer (MBC) is rare, and indications for chemotherapy (ChT) in luminal early MBC remain understudied. We aimed to develop a model to predict outcomes for these patients and identify candidates for ChT omission.</p> Methods <p>Luminal early MBC patients from the Surveillance, Epidemiology, and End Results (SEER) program (diagnosed in 2010–2018, <i>N</i> = 2845) and a Chinese cohort (diagnosed in 2000–2020, <i>N</i> = 586) were included. SEER-derived patients (diagnosed in 2010–2016) were split into training (<i>N</i> = 1405) and test (<i>N</i> = 758) sets in a 65:35 ratio; others (diagnosed in 2017–2018) formed the US validation set (<i>N</i> = 682). Chinese patients constituted the CHN validation set. The response variable and primary outcome was overall survival (OS). Four machine learning models and a Cox-based nomogram were evaluated. Low- and high-risk groups were stratified utilizing the 5-year risk scores predicted by the optimal model. Survival analysis employed Kaplan-Meier method and Cox regression.</p> Results <p>Patients in two risk groups exhibited significantly different OS across all datasets (all <i>P</i> &lt; 0.001). ChT conferred no OS benefit in low-risk patients [ChT-free as reference: training set, hazard ratio (HR) = 1.19, 95% confidence interval (CI), 0.88 to 1.60, <i>P</i> = 0.249; test set, HR = 1.19, 95% CI, 0.81 to 1.76, <i>P</i> = 0.375; US validation set, HR = 1.47, 95% CI, 0.73 to 2.94, <i>P</i> = 0.276; CHN validation set, HR = 0.95, 95% CI, 0.45 to 1.99, <i>P</i> = 0.891. Multivariable: comparable results]. For high-risk patients, ChT was significantly associated with superior OS [ChT-free as reference: training set, HR = 0.59, 95% CI, 0.47 to 0.74, <i>P</i> &lt; 0.001; test set, HR = 0.68, 95% CI, 0.49 to 0.94, <i>P</i> = 0.019; US validation set, HR = 0.49, 95% CI, 0.29 to 0.84, <i>P</i> = 0.007; CHN validation set, HR = 0.42, 95% CI, 0.19 to 0.93, <i>P</i> = 0.027. Multivariable: comparable results]. The web-based tool has been deployed.</p> Conclusions <p>Our model accurately predicts and stratifies OS in American and Chinese male patients with luminal early breast cancer. This risk stratification may aid in identifying low-risk candidates to omit ChT.</p>

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Development and validation of an online prognostic risk stratification tool to assist decisions on perioperative chemotherapy for men with luminal early breast cancer

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  • 出版模式：

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  • 发表日期：

    2026年3月28日

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  • Yuxuan Gao,
  • Marshall Xu,
  • Mengmeng Zhang,
  • Gang Sun,
  • Guolin Ye,
  • Jianyun Nie,
  • Li Ma,
  • Wendy Chen,
  • Zefei Jiang,
  • Ying Lin

摘要

Background

Male breast cancer (MBC) is rare, and indications for chemotherapy (ChT) in luminal early MBC remain understudied. We aimed to develop a model to predict outcomes for these patients and identify candidates for ChT omission.

Methods

Luminal early MBC patients from the Surveillance, Epidemiology, and End Results (SEER) program (diagnosed in 2010–2018, N = 2845) and a Chinese cohort (diagnosed in 2000–2020, N = 586) were included. SEER-derived patients (diagnosed in 2010–2016) were split into training (N = 1405) and test (N = 758) sets in a 65:35 ratio; others (diagnosed in 2017–2018) formed the US validation set (N = 682). Chinese patients constituted the CHN validation set. The response variable and primary outcome was overall survival (OS). Four machine learning models and a Cox-based nomogram were evaluated. Low- and high-risk groups were stratified utilizing the 5-year risk scores predicted by the optimal model. Survival analysis employed Kaplan-Meier method and Cox regression.

Results

Patients in two risk groups exhibited significantly different OS across all datasets (all P < 0.001). ChT conferred no OS benefit in low-risk patients [ChT-free as reference: training set, hazard ratio (HR) = 1.19, 95% confidence interval (CI), 0.88 to 1.60, P = 0.249; test set, HR = 1.19, 95% CI, 0.81 to 1.76, P = 0.375; US validation set, HR = 1.47, 95% CI, 0.73 to 2.94, P = 0.276; CHN validation set, HR = 0.95, 95% CI, 0.45 to 1.99, P = 0.891. Multivariable: comparable results]. For high-risk patients, ChT was significantly associated with superior OS [ChT-free as reference: training set, HR = 0.59, 95% CI, 0.47 to 0.74, P < 0.001; test set, HR = 0.68, 95% CI, 0.49 to 0.94, P = 0.019; US validation set, HR = 0.49, 95% CI, 0.29 to 0.84, P = 0.007; CHN validation set, HR = 0.42, 95% CI, 0.19 to 0.93, P = 0.027. Multivariable: comparable results]. The web-based tool has been deployed.

Conclusions

Our model accurately predicts and stratifies OS in American and Chinese male patients with luminal early breast cancer. This risk stratification may aid in identifying low-risk candidates to omit ChT.