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Development and Validation of a Prognostic Nomogram for Extremity Soft Tissue Leiomyosarcoma

机译:肢体软组织平滑肌肉瘤的预后Nomogram的开发和验证

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摘要

Background: Extremity soft tissue leiomyosarcoma (LMS) is a rare disease with a poor prognosis. The aim of this study is to develop nomograms to predict the overall survival (OS) and cancer-specific survival (CSS) of patients with extremity soft tissue LMS.Methods: Based on the Surveillance, Epidemiology, and End Results (SEER) database, 1,528 cases of extremity soft tissue LMS diagnosed between 1983 and 2015 were included. Cox proportional hazards regression modeling was used to analyze prognosis and obtain independent predictors. The independent predictors were integrated to develop nomograms predicting 5- and 10-year OS and CSS. Nomogram performance was evaluated by a concordance index (C-index) and calibration plots using R software version 3.5.0.Results: Multivariate analysis revealed that age ≥60 years, high tumor grade, distant metastasis, tumor size ≥5 cm, and lack of surgery were significantly associated with decreased OS and CSS. These five predictors were used to construct nomograms for predicting 5- and 10-year OS and CSS. Internal and external calibration plots for the probability of 5- and 10-year OS and CSS showed excellent agreement between nomogram prediction and observed outcomes. The C-index values for internal validation of OS and CSS prediction were 0.776 (95% CI 0.752–0.801) and 0.835 (95% CI 0.810–0.860), respectively, whereas those for external validation were 0.748 (95% CI 0.721–0.775) and 0.814 (95% CI 0.785–0.843), respectively.Conclusions: The proposed nomogram is a reliable and robust tool for accurate prognostic prediction in patients with extremity soft tissue LMS.
机译:背景:肢端软组织平滑肌肉瘤(LMS)是一种预后较差的罕见疾病。这项研究的目的是开发诺模图以预测肢端软组织LMS患者的总体生存期(OS)和癌症特异性生存期(CSS)。方法:基于监测,流行病学和最终结果(SEER)数据库包括1983年至2015年之间诊断的1,528例肢端软组织LMS病例。 Cox比例风险回归模型用于分析预后并获得独立的预测因子。集成了独立的预测器以开发可预测5年和10年OS和CSS的列线图。使用R软件3.5.0版通过一致性指数(C-index)和标定图评估线型图性能。结果:多变量分析显示年龄≥60岁,高肿瘤分级,远处转移,肿瘤≥5 cm的肿瘤以及缺乏手术与OS和CSS降低显着相关。这五个预测因子用于构建诺模图,以预测5年和10年OS和CSS。 5年和10年OS和CSS概率的内部和外部校准图显示了列线图预测和观察到的结果之间的极好的一致性。内部验证OS和CSS预测的C指数分别为0.776(95%CI 0.752–0.801)和0.835(95%CI 0.810–0.860),而外部验证的C-index值为0.748(95%CI 0.721–0.775) )和0.814(95%CI 0.785–0.843)。结论:建议的列线图是对肢体软组织LMS患者进行准确的预后预测的可靠而强大的工具。

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