Melanoma and Sarcoma Medical Oncology Unit, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China.
State Key Laboratory of Oncology in South China, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Cancer Med. 2022 Jan;11(1):74-85. doi: 10.1002/cam4.4425. Epub 2021 Nov 16.
OBJECTIVE: This study was designed to establish and validate promising and reliable nomograms for predicting the survival of angiosarcoma (AS) patients. METHODS: The Surveillance, Epidemiology, and End Results database was queried to collect the clinical information of 785 AS patients between 2004 and 2015. Data were split into a training cohort (n = 549) and a validation cohort (n = 236) without any preference. Univariate Cox and multivariate Cox regression analyses were performed to analyze the clinical parameters. Independent prognostic factors were then identified. Two nomograms were constructed to predict overall survival (OS) and cancer-specific survival (CSS) at 3 and 5 years. Finally, the models were evaluated using concordance indices (C-indices), calibration plots, and decision curve analysis (DCA). RESULTS: Based on the inclusion and exclusion criteria, 785 individuals were included in this analysis. Univariate and multivariate Cox regression analyses revealed that age, tumor size, and stage were prognostic factors independently associated with the OS of AS. Tumor site, tumor size, and stage were associated with the CSS of AS. Based on the statistical results and clinical significance of variables, nomograms were built. The nomograms for OS and CSS had C-indices of 0.666 and 0.654, respectively. The calibration curves showed good agreement between the predictive values and the actual values. DCA also indicated that the nomograms were clinically useful. CONCLUSION: We established nomograms with good predictive ability that could provide clinicians with better predictions about the clinical outcomes of AS patients.
目的:本研究旨在建立和验证用于预测血管肉瘤(AS)患者生存的有前途且可靠的列线图。
方法:从监测、流行病学和最终结果数据库中检索了 2004 年至 2015 年间的 785 例 AS 患者的临床信息。数据分为训练队列(n=549)和验证队列(n=236),没有任何偏好。使用单变量 Cox 和多变量 Cox 回归分析来分析临床参数。然后确定独立的预后因素。构建了两个列线图来预测 3 年和 5 年的总生存(OS)和癌症特异性生存(CSS)。最后,使用一致性指数(C 指数)、校准图和决策曲线分析(DCA)评估模型。
结果:根据纳入和排除标准,本分析共纳入 785 人。单因素和多因素 Cox 回归分析显示,年龄、肿瘤大小和分期是与 AS 的 OS 独立相关的预后因素。肿瘤部位、肿瘤大小和分期与 AS 的 CSS 相关。根据统计结果和变量的临床意义,建立了列线图。OS 和 CSS 的列线图的 C 指数分别为 0.666 和 0.654。校准曲线显示预测值与实际值之间具有良好的一致性。DCA 还表明列线图具有临床实用性。
结论:我们建立了具有良好预测能力的列线图,可以为临床医生提供关于 AS 患者临床结局的更好预测。
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