基于SEER数据预测肺癌伴肺转移患者生存的Nomogram。

IF 1.5 4区 医学 Q4 ONCOLOGY
Translational cancer research Pub Date : 2025-02-28 Epub Date: 2025-02-17 DOI:10.21037/tcr-24-1047
Cheng-Liang Chen, Ni-Ya Chen, Shuo Wu, Xiao Lin, Xin-Wei He, Ying Qiu, Di-Xin Xue, Jie Li, Meng-Die He, Xi-Xi Dong, Wei-Ya Zhuang, Mei-Zhen Liang
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引用次数: 0

摘要

背景:乳腺癌(breast cancer, BC)的发病率一直在稳步上升,迫切需要一种预测模型来评估BC患者的生存预后。本研究的目的是制定一个预后nomogram框架,以预测诊断为BC合并肺转移(BCLM)患者的生存。方法:我们的信息来源于监测、流行病学和最终结果(SEER)数据库。选择2010年至2015年诊断为BC的个体。收集的4309名参与者被随机分为训练队列(n= 3231)和验证队列(n= 1078)。在本研究中,年龄、婚姻状况、种族、肿瘤位置、侧边性、原发手术类型、手术切缘、肿瘤分级、肿瘤(T)分期、淋巴结(N)分期以及放疗和化疗的使用被确定为潜在的预后因素。总生存期(OS)和乳腺癌特异性生存期(CSS)被定义为本研究的主要终点。通过单因素和多因素分析评估不同因素对预后的影响。为了提高对OS和CSS的预测,我们开发了结构化图。采用一致性指数(C-index)、受试者工作特征(ROC)曲线、校准曲线和决策曲线分析(DCA)来评估nomogram的性能。结果:nomogram包括年龄、婚姻状况、种族、是否原发手术、BC亚型、分级、T分期、是否使用化疗等。OS组c指数为0.77,训练组CSS的c指数为0.77。对照组预测OS和CSS的c指数分别为0.78和0.78。ROC曲线、校正图、DCA曲线均显示良好的预测效度。结果显示中位生存时间为1.67年[95%可信区间(CI): 1.58-1.83],共记录了3,640例死亡。发现生存时间与年龄、婚姻状况、种族、是否进行原发部位手术、BC亚型、肿瘤分级、T期和化疗管理等因素相关。结论:创建nomogram来预测诊断为BCLM的个体的OS和CSS。该模态图具有可靠有效的预测能力;它或许可以帮助医生计算病人的死亡风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nomogram for predicting survival in breast cancer with lung metastasis based on SEER data.

Background: The incidence of breast cancer (BC) has been steadily increasing, highlighting the need for a predictive model to assess the survival prognosis of BC patients. The objective of this research was to formulate a prognostic nomogram framework tailored to forecast survival among individuals diagnosed with BC with lung metastasis (BCLM).

Methods: Our information was sourced from the Surveillance, Epidemiology, and End Results (SEER) database. Individuals who were diagnosed with BC from 2010 to 2015 were selected. The 4,309 collected participants were randomly separated into a training cohort (n=3,231) and a validation cohort (n=1,078). In this study, age, marital status, race, tumor location, laterality, type of primary surgery, surgical margin, tumor grade, tumor (T) stage, node (N) stage, as well as the use of radiotherapy and chemotherapy, were identified as potential prognostic factors. The overall survival (OS) and breast cancer-specific survival (CSS) were defined as the primary endpoints of this study. Univariate and multivariate analyses were conducted to assess the impact of different factors on prognosis. Structured nomograms were developed to improve the prediction of OS and CSS. The concordance index (C-index), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were employed to estimate the performance of the nomogram.

Results: The nomograms incorporated age, marital status, race, primary surgery or not, BC subtype, grade, T stage, and the use of chemotherapy or not. The C-index for OS was 0.77, and it was 0.77 in CSS for the training group. The C-indexes for the control group of OS and CSS prediction were 0.78 and 0.78, respectively. ROC curves, calibration plots, and DCA curves displayed excellent predictive validity. The results indicate a median survival time of 1.67 years [95% confidence interval (CI): 1.58-1.83], with a total of 3,640 deaths recorded. Survival time was found to be associated with factors such as age, marital status, race, whether primary site surgery was performed, BC subtype, tumor grade, T stage, and the administration of chemotherapy.

Conclusions: Nomograms were created to predict OS and CSS for individuals diagnosed with BCLM. The nomogram has a reliable and valid prediction power; it could perhaps assist physicians in calculating patients' mortality risk.

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来源期刊
CiteScore
2.10
自引率
0.00%
发文量
252
期刊介绍: Translational Cancer Research (Transl Cancer Res TCR; Print ISSN: 2218-676X; Online ISSN 2219-6803; http://tcr.amegroups.com/) is an Open Access, peer-reviewed journal, indexed in Science Citation Index Expanded (SCIE). TCR publishes laboratory studies of novel therapeutic interventions as well as clinical trials which evaluate new treatment paradigms for cancer; results of novel research investigations which bridge the laboratory and clinical settings including risk assessment, cellular and molecular characterization, prevention, detection, diagnosis and treatment of human cancers with the overall goal of improving the clinical care of cancer patients. The focus of TCR is original, peer-reviewed, science-based research that successfully advances clinical medicine toward the goal of improving patients'' quality of life. The editors and an international advisory group of scientists and clinician-scientists as well as other experts will hold TCR articles to the high-quality standards. We accept Original Articles as well as Review Articles, Editorials and Brief Articles.
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