Peng Li, Jie Luo, Zilong Zheng, Lu Meng, Anqi Zhang, Wei Cao, Xiaomei Gong
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Nomograms were created and tested using multivariate Cox regression models to forecast CSS and OS at intervals of 1, 2, and 3 years.</p><p><strong>Results: </strong>The research involved 3413 individuals diagnosed with NSCLC brain metastases who had undergone radiotherapy but had not experienced surgery. These participants were randomly divided into two categories. The analysis revealed that gender, age, ethnicity, marital status, tumor location, tumor laterality, tumor grade, histology, T stage, N stage, chemotherapy, tumor size, lung metastasis, bone metastasis, and liver metastasis were significant independent predictors for OS and CSS. The C-index for the training set for predicting OS was .709 (95% CI, .697-.721), and for the validation set, it was .705 (95% CI, .686-.723), respectively. The C-index for predicting CSS was .710 (95% CI, .697-.722) in the training set and .703 (95% CI, .684-.722) in the validation set, respectively. The nomograms model, as suggested by the impressive C-index, exhibits outstanding differentiation ability. Moreover, the ROC and calibration curves reveal its commendable precision and distinguishing potential.</p><p><strong>Conclusions: </strong>For the first time, highly accurate and reliable nomograms were developed to predict OS and CSS in NSCLC patients with non-surgical brain metastases, who have undergone radiotherapy treatment. The nomograms may assist in tailoring counseling strategies and choosing the most effective treatment method.</p>","PeriodicalId":49093,"journal":{"name":"Cancer Control","volume":null,"pages":null},"PeriodicalIF":2.5000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11110521/pdf/","citationCount":"0","resultStr":"{\"title\":\"Survival Predictive Nomograms for Non-Surgical Brain Metastases Patients From Non-Small Cell Lung Cancer Receiving Radiotherapy: A Population-Based Study.\",\"authors\":\"Peng Li, Jie Luo, Zilong Zheng, Lu Meng, Anqi Zhang, Wei Cao, Xiaomei Gong\",\"doi\":\"10.1177/10732748241255212\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>A high number of Non-Small Cell Lung Cancer (NSCLC) patients with brain metastasis who have not had surgery often have a negative outlook. 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引用次数: 0
摘要
目的:大量非小细胞肺癌(NSCLC)脑转移患者如果没有接受手术治疗,其前景往往不容乐观。放疗仍然是最常用、最有效的方法。本研究开发了预测接受放疗的非手术脑转移 NSCLC 患者癌症特异性生存率(CSS)和总生存率(OS)的提名图:方法:从监测、流行病学和最终结果(SEER)数据库中收集被诊断为不适合手术的脑转移瘤 NSCLC 患者的信息。使用多变量考克斯回归模型创建并测试了预测1年、2年和3年间隔期CSS和OS的提名图:研究涉及 3413 名确诊为 NSCLC 脑转移患者,这些患者接受过放疗,但未进行过手术。这些参与者被随机分为两类。分析显示,性别、年龄、种族、婚姻状况、肿瘤位置、肿瘤侧位、肿瘤分级、组织学、T期、N期、化疗、肿瘤大小、肺转移、骨转移和肝转移是OS和CSS的重要独立预测因素。训练集预测OS的C指数为0.709(95% CI,0.697-0.721),验证集预测OS的C指数为0.705(95% CI,0.686-0.723)。在训练集和验证集中,预测 CSS 的 C 指数分别为 0.710(95% CI,0.697-0.722)和 0.703(95% CI,0.684-0.722)。令人印象深刻的 C 指数表明,提名图模型具有出色的区分能力。此外,ROC 和校准曲线也显示了其值得称道的精确度和区分潜力:该研究首次开发出高度准确可靠的提名图,用于预测接受放疗的非手术脑转移 NSCLC 患者的 OS 和 CSS。该提名图有助于制定咨询策略和选择最有效的治疗方法。
Survival Predictive Nomograms for Non-Surgical Brain Metastases Patients From Non-Small Cell Lung Cancer Receiving Radiotherapy: A Population-Based Study.
Objective: A high number of Non-Small Cell Lung Cancer (NSCLC) patients with brain metastasis who have not had surgery often have a negative outlook. Radiotherapy remains a most common and effective method. Nomograms were developed to forecast the cancer-specific survival (CSS) and overall survival (OS) in NSCLC individuals with nonoperative brain metastases who underwent radiotherapy.
Methods: Information was gathered from the Surveillance, Epidemiology, and End Results (SEER) database about patients diagnosed with NSCLC who had brain metastases not suitable for surgery. Nomograms were created and tested using multivariate Cox regression models to forecast CSS and OS at intervals of 1, 2, and 3 years.
Results: The research involved 3413 individuals diagnosed with NSCLC brain metastases who had undergone radiotherapy but had not experienced surgery. These participants were randomly divided into two categories. The analysis revealed that gender, age, ethnicity, marital status, tumor location, tumor laterality, tumor grade, histology, T stage, N stage, chemotherapy, tumor size, lung metastasis, bone metastasis, and liver metastasis were significant independent predictors for OS and CSS. The C-index for the training set for predicting OS was .709 (95% CI, .697-.721), and for the validation set, it was .705 (95% CI, .686-.723), respectively. The C-index for predicting CSS was .710 (95% CI, .697-.722) in the training set and .703 (95% CI, .684-.722) in the validation set, respectively. The nomograms model, as suggested by the impressive C-index, exhibits outstanding differentiation ability. Moreover, the ROC and calibration curves reveal its commendable precision and distinguishing potential.
Conclusions: For the first time, highly accurate and reliable nomograms were developed to predict OS and CSS in NSCLC patients with non-surgical brain metastases, who have undergone radiotherapy treatment. The nomograms may assist in tailoring counseling strategies and choosing the most effective treatment method.
期刊介绍:
Cancer Control is a JCR-ranked, peer-reviewed open access journal whose mission is to advance the prevention, detection, diagnosis, treatment, and palliative care of cancer by enabling researchers, doctors, policymakers, and other healthcare professionals to freely share research along the cancer control continuum. Our vision is a world where gold-standard cancer care is the norm, not the exception.