Evidence map›Paper›PMID 40335870›Full record

ArticleBreast cancer (Tokyo, Japan)2025

A nomogram to predict the benefit of postmastectomy radiotherapy in breast cancer with nodal micrometastases.

Zhen-Zhen Lu, Lin-Feng Guo, Juan Zhou, San-Gang Wu

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Article in Breast cancer (Tokyo, Japan), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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5 · Who and what money

Authors and funding

4 authors.

Zhen-Zhen Lu *The School of Clinical Medicine, Fujian Medical University, Fuzhou, People's Republic of China.
Lin-Feng Guo *Department of Radiation Oncology, Xiamen Cancer Quality Control Center, Xiamen Cancer Center, Xiamen Key Laboratory of Radiation Oncology, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, People's Republic of China.
Juan ZhouDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, 361003, People's Republic of China. zhoujuan@xmu.edu.cn.
San-Gang WuThe School of Clinical Medicine, Fujian Medical University, Fuzhou, People's Republic of China. wusg@xmu.edu.cn.ORCID http://orcid.org/0000-0002-0556-2614

Funding

Medical Innovation Research Project of the Science and Technology Plan for High-Quality Development of Health in Xiamen City 2024GZL-CX16Natural Science Foundation of Fujian Province 2024J011363Young and Middle-Aged Key Talent Cultivation Program of the Science and Technology Plan for High-Quality Development of Health in Xiamen City 2024GZL-GG58
6 · The paper itself

Abstract

backgroundThe role of postmastectomy radiotherapy (PMRT) in breast cancer (BC) with nodal micrometastases (N1mic) remains unclear. This study aimed to evaluate the efficacy of PMRT in T1-2N1mic BC patients who have undergone mastectomy.

methodsFemale patients with T1-2N1mic BC who underwent mastectomy and were registered in the Surveillance, Epidemiology, and End Results database between 2010 and 2017. The chi-square test, logistic regression analysis, Kaplan-Meier methods, and multivariate Cox proportional hazards analysis were used for statistical analyses. Nomograms for predicting breast cancer-specific survival (BCSS) and overall survival (OS) were created by integrating the independent prognostic factors.

resultsA total of 5948 eligible patients were included in this study. A total of 1207 patients (20.3%) received PMRT, while 4741 patients (79.7%) did not. The use of PMRT increased over the study period, from 15.7% in 2010 to 23.8% in 2017 (P < 0.001). The multivariate Cox proportional hazards analysis showed that PMRT did not improve BCSS and OS. Nomograms were established based on the independent prognostic factors to predict the BCSS and CSS of patients. Regarding BCSS, there were 3627 patients (61.0%) classified as low-risk and 2321 patients (39.0%) classified as high-risk using a cutoff point of 125, PMRT did not improve BCSS in patients with low-risk (P = 0.697) and high-risk (P = 0.149) groups. Regarding OS, there were 4791 patients (80.5%) classified as low-risk and 1157 patients (19.5%) classified as high-risk using a cutoff point of 130, patients who received PMRT had significantly better 5-year OS than those who did not receive PMRT (P = 0.047), while similar outcomes were found between the treatment arms in the low-risk group (P = 0.575).

conclusionsWhile our findings suggest that PMRT does not enhance survival outcomes in T1-T2N1mic BC patients, it may offer a survival advantage in high-risk subgroups.

Indexed as

Breast NeoplasmsNomogramsAdultAgedFemaleHumansKaplan-Meier EstimateLymphatic MetastasisMastectomyMiddle AgedNeoplasm MicrometastasisPrognosisRadiotherapy, AdjuvantRetrospective StudiesSEER ProgramBreast cancerMastectomyNodal micrometastaticRadiotherapySurvival

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.