Subdivision of M1 category and prognostic stage for de novo metastatic breast cancer to enhance prognostic prediction and guide the selection of locoregional therapy.

IF 2.3 3区 医学 Q3 ONCOLOGY Thoracic Cancer Pub Date : 2024-10-01 Epub Date: 2024-09-15 DOI:10.1111/1759-7714.15452
Lei Ji, Ge Song, Min Xiao, Xi Chen, Qing Li, Jiayu Wang, Ying Fan, Yang Luo, Qiao Li, Shanshan Chen, Fei Ma, Binghe Xu, Pin Zhang
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Abstract

Background: Although de novo metastatic breast cancer (dnMBC) is acknowledged as a heterogeneous disease, the current staging systems do not distinguish between patients within the M1 or stage IV category. This study aimed to refine the M1 category and prognostic staging for dnMBC to enhance prognosis prediction and guide the choice of locoregional treatment.

Methods: We selected patients with dnMBC from the SEER database (2010-2019), grouping them into training (N = 8048) and internal validation (N = 3450) cohorts randomly at a 7:3 ratio. An independent external validation cohort (N = 660) was enrolled from dnMBC patients (2010-2023) treated in three hospitals. Nomogram-based risk stratification was employed to refine the M1 category and prognostic stage, incorporating T/N stage, histologic grade, subtypes, and the location and number of metastatic sites. Both internal and external validation sets were used for validation analyses.

Results: Brain, liver, or lung involvement and multiple metastases were independent prognostic factors for overall survival (OS). The nomogram-based stratification effectively divided M1 stage into three groups: M1a (bone-only involvement), M1b (liver or lung involvement only, with or without bone metastases), and M1c (brain metastasis or involvement of both liver and lung, regardless of other metastatic sites). Only subtype and M1 stage were included to define the final prognostic stage. Significant differences in OS were observed across M1 and prognostic subgroups. Patients with the M1c stage benefited less from primary tumor surgery in comparison with M1a stage.

Conclusion: Subdivision of the M1 and prognostic stage could serve as a supplement to the current staging guidelines for dnMBC and guide locoregional treatment.

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细分新发转移性乳腺癌的 M1 类别和预后分期,以加强预后预测并指导局部治疗的选择。
背景:虽然新发转移性乳腺癌(dnMBC)被认为是一种异质性疾病,但目前的分期系统并未区分M1或IV期患者。本研究旨在完善 M1 类别和 dnMBC 的预后分期,以加强预后预测并指导局部治疗的选择:我们从SEER数据库(2010-2019年)中选取了dnMBC患者,按7:3的比例将其随机分为训练队列(N = 8048)和内部验证队列(N = 3450)。一个独立的外部验证队列(N = 660)是从三家医院治疗的dnMBC患者(2010-2023年)中招募的。采用基于提名图的风险分层来完善 M1 类别和预后分期,其中包括 T/N 分期、组织学分级、亚型以及转移部位的位置和数量。内部和外部验证集均用于验证分析:结果:脑、肝或肺受累以及多处转移是总生存期(OS)的独立预后因素。基于提名图的分层方法有效地将M1分期分为三组:M1a(仅累及骨骼)、M1b(仅累及肝脏或肺脏,伴有或不伴有骨转移)和M1c(脑转移或肝脏和肺脏均受累,与其他转移部位无关)。最终的预后分期只包括亚型和M1分期。在不同的M1和预后亚组中,观察到OS存在显著差异。与M1a分期相比,M1c分期患者从原发肿瘤手术中获益较少:结论:M1分期和预后分期的细分可作为目前dnMBC分期指南的补充,并指导局部治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Thoracic Cancer
Thoracic Cancer ONCOLOGY-RESPIRATORY SYSTEM
CiteScore
5.20
自引率
3.40%
发文量
439
审稿时长
2 months
期刊介绍: Thoracic Cancer aims to facilitate international collaboration and exchange of comprehensive and cutting-edge information on basic, translational, and applied clinical research in lung cancer, esophageal cancer, mediastinal cancer, breast cancer and other thoracic malignancies. Prevention, treatment and research relevant to Asia-Pacific is a focus area, but submissions from all regions are welcomed. The editors encourage contributions relevant to prevention, general thoracic surgery, medical oncology, radiology, radiation medicine, pathology, basic cancer research, as well as epidemiological and translational studies in thoracic cancer. Thoracic Cancer is the official publication of the Chinese Society of Lung Cancer, International Chinese Society of Thoracic Surgery and is endorsed by the Korean Association for the Study of Lung Cancer and the Hong Kong Cancer Therapy Society. The Journal publishes a range of article types including: Editorials, Invited Reviews, Mini Reviews, Original Articles, Clinical Guidelines, Technological Notes, Imaging in thoracic cancer, Meeting Reports, Case Reports, Letters to the Editor, Commentaries, and Brief Reports.
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