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

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, Epidemi...

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Main Authors: MingFeng Xue, Gang Chen, JiaPing Dai, JunYu Hu
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-05-01
Series:Frontiers in Oncology
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fonc.2019.00346/full
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spelling doaj-ce5d6f1f84514d148735b9aea26bcfa62020-11-25T01:18:28ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2019-05-01910.3389/fonc.2019.00346450003Development and Validation of a Prognostic Nomogram for Extremity Soft Tissue LeiomyosarcomaMingFeng XueGang ChenJiaPing DaiJunYu HuBackground: 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.https://www.frontiersin.org/article/10.3389/fonc.2019.00346/fullextremitiesleiomyosarcomanomogramspredictorprognosis
collection DOAJ
language English
format Article
sources DOAJ
author MingFeng Xue
Gang Chen
JiaPing Dai
JunYu Hu
spellingShingle MingFeng Xue
Gang Chen
JiaPing Dai
JunYu Hu
Development and Validation of a Prognostic Nomogram for Extremity Soft Tissue Leiomyosarcoma
Frontiers in Oncology
extremities
leiomyosarcoma
nomograms
predictor
prognosis
author_facet MingFeng Xue
Gang Chen
JiaPing Dai
JunYu Hu
author_sort MingFeng Xue
title Development and Validation of a Prognostic Nomogram for Extremity Soft Tissue Leiomyosarcoma
title_short Development and Validation of a Prognostic Nomogram for Extremity Soft Tissue Leiomyosarcoma
title_full Development and Validation of a Prognostic Nomogram for Extremity Soft Tissue Leiomyosarcoma
title_fullStr Development and Validation of a Prognostic Nomogram for Extremity Soft Tissue Leiomyosarcoma
title_full_unstemmed Development and Validation of a Prognostic Nomogram for Extremity Soft Tissue Leiomyosarcoma
title_sort development and validation of a prognostic nomogram for extremity soft tissue leiomyosarcoma
publisher Frontiers Media S.A.
series Frontiers in Oncology
issn 2234-943X
publishDate 2019-05-01
description 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.
topic extremities
leiomyosarcoma
nomograms
predictor
prognosis
url https://www.frontiersin.org/article/10.3389/fonc.2019.00346/full
work_keys_str_mv AT mingfengxue developmentandvalidationofaprognosticnomogramforextremitysofttissueleiomyosarcoma
AT gangchen developmentandvalidationofaprognosticnomogramforextremitysofttissueleiomyosarcoma
AT jiapingdai developmentandvalidationofaprognosticnomogramforextremitysofttissueleiomyosarcoma
AT junyuhu developmentandvalidationofaprognosticnomogramforextremitysofttissueleiomyosarcoma
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