Analysis of the Relationship Between Primary Tumor Site and Clinicopathological Characteristics and Survival Prognosis of Breast Cancer Patients Based on SEER Database

IF 2.9 3区医学 Q2 ONCOLOGY

Clinical breast cancer Pub Date : 2024-08-27 DOI:10.1016/j.clbc.2024.08.021

Yumeng Wei , Peinan Liu , Xingyu Liu , Meng Wang , Dandan Liu , Hanxiao Cui , Shuai Lin , Hao Wu , Xiaobin Ma , Huafeng Kang

{"title":"Analysis of the Relationship Between Primary Tumor Site and Clinicopathological Characteristics and Survival Prognosis of Breast Cancer Patients Based on SEER Database","authors":"Yumeng Wei , Peinan Liu , Xingyu Liu , Meng Wang , Dandan Liu , Hanxiao Cui , Shuai Lin , Hao Wu , Xiaobin Ma , Huafeng Kang","doi":"10.1016/j.clbc.2024.08.021","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><div>This study aimed to analyze the association between the primary tumor site and clinicopathological characteristics and survival prognosis of breast cancer (BC) patients using a large population database.</div></div><div><h3>Methods</h3><div>BC patients screened in the Surveillance, Epidemiology, and End Results (SEER) database were categorized into 6 groups based on primary sites. Descriptive statistics, Kaplan-Meier curves, Cox regression models, forest plots were used to assess the effect of primary sites on overall survival (OS) and breast cancer-specific survival (BCSS). Multivariate Cox proportional analyses were conducted to calculate hazard ratios (HRs) and adjusted subgroups’ hazard ratios (AHRs). Nomograms were utilized to predict OS and BCSS.</div></div><div><h3>Results</h3><div>Among 193,043 BC patients, the highest incidence was found in the upper outer quadrant (52.60%). Central portion patients are associated with more clinical features indicating a poor prognosis, and had worse OS and BCSS than other sites. Univariate and multifactorial Cox analyses showed associations between OS/BCSS and various factors. Subgroup analyses revealed differences in OS and BCSS between central portion and upper outer quadrant varied among age, T and N stage. The nomogram was established to predict the survival of central portion BC patients.</div></div><div><h3>Conclusions</h3><div>Primary tumor site is associated with clinicopathological features and prognosis of BC, may be influenced by age at diagnosis and T and N stage. Central portion BC patients have worse prognosis due to older age at diagnosis, higher T stage and higher likelihood of lymph node metastasis. Early diagnosis and treatment may help to improve survival of central portion BC.</div></div>","PeriodicalId":10197,"journal":{"name":"Clinical breast cancer","volume":"24 8","pages":"Pages 728-745"},"PeriodicalIF":2.9000,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical breast cancer","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1526820924002337","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Purpose

This study aimed to analyze the association between the primary tumor site and clinicopathological characteristics and survival prognosis of breast cancer (BC) patients using a large population database.

Methods

BC patients screened in the Surveillance, Epidemiology, and End Results (SEER) database were categorized into 6 groups based on primary sites. Descriptive statistics, Kaplan-Meier curves, Cox regression models, forest plots were used to assess the effect of primary sites on overall survival (OS) and breast cancer-specific survival (BCSS). Multivariate Cox proportional analyses were conducted to calculate hazard ratios (HRs) and adjusted subgroups’ hazard ratios (AHRs). Nomograms were utilized to predict OS and BCSS.

Results

Among 193,043 BC patients, the highest incidence was found in the upper outer quadrant (52.60%). Central portion patients are associated with more clinical features indicating a poor prognosis, and had worse OS and BCSS than other sites. Univariate and multifactorial Cox analyses showed associations between OS/BCSS and various factors. Subgroup analyses revealed differences in OS and BCSS between central portion and upper outer quadrant varied among age, T and N stage. The nomogram was established to predict the survival of central portion BC patients.

Conclusions

Primary tumor site is associated with clinicopathological features and prognosis of BC, may be influenced by age at diagnosis and T and N stage. Central portion BC patients have worse prognosis due to older age at diagnosis, higher T stage and higher likelihood of lymph node metastasis. Early diagnosis and treatment may help to improve survival of central portion BC.

查看原文本刊更多论文

基于 SEER 数据库的乳腺癌患者原发肿瘤部位与临床病理特征和生存预后的关系分析

本研究旨在利用大型人口数据库分析乳腺癌（BC）患者的原发肿瘤部位与临床病理特征和生存预后之间的关系。在监测、流行病学和最终结果（SEER）数据库中筛查出的乳腺癌患者根据原发部位分为 6 组。采用描述性统计、卡普兰-梅耶曲线、Cox回归模型和森林图来评估原发部位对总生存期（OS）和乳腺癌特异性生存期（BCSS）的影响。采用多变量考克斯比例分析法计算危险比（HRs）和调整亚组危险比（AHRs）。采用提名图预测OS和BCSS。在 193 043 名 BC 患者中，外上象限的发病率最高（52.60%）。与其他部位相比，中央部位患者具有更多预后不良的临床特征，其OS和BCSS也更差。单变量和多因素Cox分析显示，OS/BCSS与各种因素有关。亚组分析显示，中央部分和外上象限的OS和BCSS因年龄、T期和N期而异。建立了预测中央型 BC 患者生存期的提名图。原发肿瘤部位与BC的临床病理特征和预后有关，可能受诊断时的年龄、T期和N期的影响。中央型 BC 患者的预后较差，原因是诊断时年龄较大、T 分期较高以及淋巴结转移的可能性较高。早期诊断和治疗可能有助于提高中央型 BC 的生存率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Clinical breast cancer 医学-肿瘤学

CiteScore

5.40

自引率

3.20%

发文量

174

审稿时长

48 days

期刊介绍： Clinical Breast Cancer is a peer-reviewed bimonthly journal that publishes original articles describing various aspects of clinical and translational research of breast cancer. Clinical Breast Cancer is devoted to articles on detection, diagnosis, prevention, and treatment of breast cancer. The main emphasis is on recent scientific developments in all areas related to breast cancer. Specific areas of interest include clinical research reports from various therapeutic modalities, cancer genetics, drug sensitivity and resistance, novel imaging, tumor genomics, biomarkers, and chemoprevention strategies.