Evidence map›Paper›PMID 41139173›Full record

ArticleEuropean radiology2026

Identify high-risk patients of T1-2N1M0 breast cancer who benefit from postmastectomy radiotherapy: a dual-center retrospective propensity score-matched study.

Ziting Xu, Yanyan Zhang, Yudie Zou, Yalin He, Li Zhang, Jiekun Huo, Yu Liang, Weimin Xu, Yang Gao, Deli Chen and 4 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors.

Ziting Xu *Department of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, PR China.
Yanyan Zhang *Department of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, PR China.
Yudie Zou *Department of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, PR China.
Yalin HeDepartment of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, PR China.
Li ZhangDepartment of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, PR China.
Jiekun HuoDepartment of Imaging, Zengcheng Branch of Nanfang Hospital, Southern Medical University, Guangzhou, PR China.
Yu LiangDepartment of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, PR China.
Weimin XuDepartment of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, PR China.
Yang GaoDepartment of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, PR China.
Deli ChenDepartment of Ultrasound, First People's Hospital of Foshan, Foshan, PR China.
Shuochun ChenDepartment of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, PR China.
Weijun HuangDepartment of Ultrasound, First People's Hospital of Foshan, Foshan, PR China. hwjun1716@163.com.
Ge WenDepartment of Medical Imaging, Nanfang Hospital, Southern Medical University, Guangzhou, PR China. m13360022166@163.com.
Yingjia LiDepartment of Ultrasound, Nanfang Hospital, Southern Medical University, Guangzhou, PR China. lyjia@smu.edu.cn.ORCID http://orcid.org/0000-0002-8885-2317

Funding

Guangzhou Municipal Science and Technology Program key projects 2023B03J1350National Natural Science Foundation of China 82271998
6 · The paper itself

Abstract

objectiveTo develop a personalized risk stratification nomogram, integrating clinicopathological, sonographic, and mammographic features, to identify high-risk patients who may benefit from postmastectomy radiotherapy (PMRT). MATERIALS AND

methodsA retrospective analysis was conducted on 408 patients from Medical Center 1 (January 2011 to June 2019) and 190 patients from Medical Center 2 (January 2017 to June 2019) with pathologically staged pT1-2N1M0 breast cancer following mastectomy, with preoperative mammography (MG) and ultrasound (US) imaging. After propensity score matching (PSM), the multimodal nomogram was developed using univariate and multivariate Cox regression analyses.

resultsWith multivariate analysis, independent risk factors were identified, including age, pathologic T stage, positive axillary lymph nodes, lymphovascular invasion, microcalcifications, and vascularity on US, architectural distortion, and suspicious calcifications on MG (all p < 0.05). The C-index for the multimodal nomogram was 0.816 (95% CI: 0.774-0.859) in the training and 0.846 (95% CI: 0.772-0.920) in the external validation cohort, demonstrating superior prognostic accuracy, discriminative ability, and clinical applicability than clinicopathological and imaging-only models. Risk stratification using this nomogram showed that PMRT significantly improved RFS in the high-risk group (training cohort: HR = 0.392; external validation cohort: HR = 0.358, both p < 0.05), while patients in the low-risk group did not derive benefit from PMRT (training cohort: HR = 0.173; external validation cohort: HR = 0, both p > 0.05).

conclusionThis multimodal nomogram served as a clinical decision-support tool for clinicians to assess the risk-benefit balance of PMRT and had potential clinical application to guide further personalized adjuvant therapy for women with pT1-2N1M0 breast cancer. KEY POINTS: Question Can the multimodal nomogram integrating clinicopathological, ultrasonic, and mammographic parameters identify high-risk pT1-2N1M0 patients who may benefit from postmastectomy radiation therapy? Findings By effectively risk-stratifying, the nomogram identified high-risk patients who derived significant benefit from PMRT while distinguishing low-risk patients who could potentially avoid unnecessary treatment. Clinical relevance The multimodal nomogram served as a clinical decision-support tool for clinicians to optimize personalized adjuvant therapeutic approaches and improve survival outcomes for patients with pT1-2N1M0 breast cancer.

Indexed as

Breast NeoplasmsAdultAgedFemaleHumansMammographyMastectomyMiddle AgedNeoplasm StagingNomogramsPropensity ScoreRadiotherapy, AdjuvantRetrospective StudiesRisk AssessmentRisk FactorsUltrasonography, MammaryMammographyNomogramPostmastectomy radiation therapyRecurrence-free survivalUltrasonography

Identifiers

What Socratic holds

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Registered trials

None linked

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 Socratic graph.