A novel nomogram for predicting cancer-specific survival in women with uterine sarcoma: a large population-based study

Abstract Background Uterine sarcoma (US) is a rare malignant uterine tumor with aggressive behavior and rapid progression. The purpose of this study was to constructa comprehensive nomogram to predict cancer-specific survival (CSS) of patients with US-based on the Surveillance, Epidemiology, and End...

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Main Authors: Yuan-jie Li, Jun Lyu, Chen Li, Hai-rong He, Jin-feng Wang, Yue-ling Wang, Jing Fang, Jing Ji
Format: Article
Language:English
Published: BMC 2022-05-01
Series:BMC Women's Health
Subjects:
Online Access:https://doi.org/10.1186/s12905-022-01739-5
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author Yuan-jie Li
Jun Lyu
Chen Li
Hai-rong He
Jin-feng Wang
Yue-ling Wang
Jing Fang
Jing Ji
author_facet Yuan-jie Li
Jun Lyu
Chen Li
Hai-rong He
Jin-feng Wang
Yue-ling Wang
Jing Fang
Jing Ji
author_sort Yuan-jie Li
collection DOAJ
description Abstract Background Uterine sarcoma (US) is a rare malignant uterine tumor with aggressive behavior and rapid progression. The purpose of this study was to constructa comprehensive nomogram to predict cancer-specific survival (CSS) of patients with US-based on the Surveillance, Epidemiology, and End Results (SEER) database. Methods A retrospective population-based study was conducted using data from patients with US between 2010 and 2015 from the SEER database. They were randomly divided into a training cohort and a validation cohort ata 7-to-3 ratio. Multivariate Cox analysis was performed to identify independent prognostic factors. Subsequently, a nomogram was established to predict patient CSS. The discrimination and calibration of the nomogram were evaluated by the concordance index (C-index) and the area under the curve (AUC). Finally, net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration plotting, and decision-curve analysis (DCA) were used to evaluate the benefits of the new prediction model. Results A total of 3861 patients with US were included in our study. As revealed in multivariate Cox analysis, age at diagnosis, race, marital status, insurance record, tumor size, pathology grade, histological type, SEER stage, AJCC stage, surgery status, radiotherapy status, and chemotherapy status were found to be independent prognostic factors. In our nomogram, pathology grade had strongest correlation with CSS, followed by age at diagnosis and surgery status. Compared to the AJCC staging system, the new nomogram showed better predictive discrimination with a higher C-index in the training and validation cohorts (0.796 and 0.767 vs. 0.706 and 0.713, respectively). Furthermore, the AUC value, calibration plotting, NRI, IDI, and DCA also demonstrated better performance than the traditional system. Conclusion Our study validated the first comprehensive nomogram for US, which could provide more accurate and individualized survival predictions for US patients in clinical practice.
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spelling doaj.art-4a3b0a49d72d4caa9b53c898e9aab57b2022-12-22T00:36:18ZengBMCBMC Women's Health1472-68742022-05-0122111010.1186/s12905-022-01739-5A novel nomogram for predicting cancer-specific survival in women with uterine sarcoma: a large population-based studyYuan-jie Li0Jun Lyu1Chen Li2Hai-rong He3Jin-feng Wang4Yue-ling Wang5Jing Fang6Jing Ji7Department of Human Anatomy, Histology and Embryology, School of Basic Medical Sciences, Xi’an Jiao Tong University Health Science CenterDepartment of Clinical Research, The First Affiliated Hospital of Jinan UniversityDepartment of Gynecology and Obstetrics, The First Affiliated Hospital of Xi’an Jiaotong UniversityDepartment of Clinical Research Center, The First Affiliated Hospital of Xi’an Jiaotong UniversityDepartment of Gynecology and Obstetrics, The First Affiliated Hospital of Xi’an Jiaotong UniversityDepartment of Gynecology and Obstetrics, The First Affiliated Hospital of Xi’an Jiaotong UniversityDepartment of Gynecology and Obstetrics, The First Affiliated Hospital of Xi’an Jiaotong UniversityDepartment of Gynecology and Obstetrics, The First Affiliated Hospital of Xi’an Jiaotong UniversityAbstract Background Uterine sarcoma (US) is a rare malignant uterine tumor with aggressive behavior and rapid progression. The purpose of this study was to constructa comprehensive nomogram to predict cancer-specific survival (CSS) of patients with US-based on the Surveillance, Epidemiology, and End Results (SEER) database. Methods A retrospective population-based study was conducted using data from patients with US between 2010 and 2015 from the SEER database. They were randomly divided into a training cohort and a validation cohort ata 7-to-3 ratio. Multivariate Cox analysis was performed to identify independent prognostic factors. Subsequently, a nomogram was established to predict patient CSS. The discrimination and calibration of the nomogram were evaluated by the concordance index (C-index) and the area under the curve (AUC). Finally, net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration plotting, and decision-curve analysis (DCA) were used to evaluate the benefits of the new prediction model. Results A total of 3861 patients with US were included in our study. As revealed in multivariate Cox analysis, age at diagnosis, race, marital status, insurance record, tumor size, pathology grade, histological type, SEER stage, AJCC stage, surgery status, radiotherapy status, and chemotherapy status were found to be independent prognostic factors. In our nomogram, pathology grade had strongest correlation with CSS, followed by age at diagnosis and surgery status. Compared to the AJCC staging system, the new nomogram showed better predictive discrimination with a higher C-index in the training and validation cohorts (0.796 and 0.767 vs. 0.706 and 0.713, respectively). Furthermore, the AUC value, calibration plotting, NRI, IDI, and DCA also demonstrated better performance than the traditional system. Conclusion Our study validated the first comprehensive nomogram for US, which could provide more accurate and individualized survival predictions for US patients in clinical practice.https://doi.org/10.1186/s12905-022-01739-5NomogramUterine sarcomaSEER databaseCancer-specific survival
spellingShingle Yuan-jie Li
Jun Lyu
Chen Li
Hai-rong He
Jin-feng Wang
Yue-ling Wang
Jing Fang
Jing Ji
A novel nomogram for predicting cancer-specific survival in women with uterine sarcoma: a large population-based study
BMC Women's Health
Nomogram
Uterine sarcoma
SEER database
Cancer-specific survival
title A novel nomogram for predicting cancer-specific survival in women with uterine sarcoma: a large population-based study
title_full A novel nomogram for predicting cancer-specific survival in women with uterine sarcoma: a large population-based study
title_fullStr A novel nomogram for predicting cancer-specific survival in women with uterine sarcoma: a large population-based study
title_full_unstemmed A novel nomogram for predicting cancer-specific survival in women with uterine sarcoma: a large population-based study
title_short A novel nomogram for predicting cancer-specific survival in women with uterine sarcoma: a large population-based study
title_sort novel nomogram for predicting cancer specific survival in women with uterine sarcoma a large population based study
topic Nomogram
Uterine sarcoma
SEER database
Cancer-specific survival
url https://doi.org/10.1186/s12905-022-01739-5
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