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Nomogram for predicting cancer-specific survival in undifferentiated pleomorphic sarcoma: A Surveillance, Epidemiology, and End Results -based study.
Xu, Fengshuo; Zhao, Fanfan; Feng, Xiaojie; Li, Chengzhuo; Han, Didi; Zheng, Shuai; Liu, Yue; Lyu, Jun.
Affiliation
  • Xu F; Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, China.
  • Zhao F; School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China.
  • Feng X; Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, China.
  • Li C; School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China.
  • Han D; Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, China.
  • Zheng S; School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China.
  • Liu Y; Department of Clinical Research, The First Affiliated Hospital of Jinan University, Guangzhou, China.
  • Lyu J; School of Public Health, Xi'an Jiaotong University Health Science Center, Xi'an, China.
Cancer Control ; 28: 10732748211036775, 2021.
Article in En | MEDLINE | ID: mdl-34405711
ABSTRACT

INTRODUCTION:

The purpose of this study was to construct and validate a nomogram for predicting cancer-specific survival (CSS) in undifferentiated pleomorphic sarcoma (UPS) patients at 3, 5, and 8 years after the diagnosis.

METHODS:

Data for UPS patients were extracted from the SEER (Surveillance, Epidemiology, and End Results) database. The patients were randomly divided into a training cohort (70%) and a validation cohort (30%). The backward stepwise Cox regression model was used to select independent prognostic factors. All of the factors were integrated into the nomogram to predict the CSS rates in UPS patients at 3, 5, and 8 years after the diagnosis. The nomogram' s performance was then validated using multiple indicators, including the area under the time-dependent receiver operating characteristic curve (AUC), consistency index (C-index), calibration curve, decision-curve analysis (DCA), integrated discrimination improvement (IDI), and net reclassification improvement (NRI).

RESULTS:

This study included 2,009 UPS patients. Ten prognostic factors were identified after analysis of the Cox regression model in the training cohort, which were year of diagnosis, age, race, primary site, histological grade, T, N, M stage, surgery status, and insurance status. The nomogram was then constructed and validated internally and externally. The relatively high C-indexes and AUC values indicated that the nomogram has good discrimination ability. The calibration curves revealed that the nomogram was well calibrated. NRI and IDI values were both improved, indicating that our nomogram was superior to the AJCC (American Joint Committee on Cancer) system. DCA curves demonstrated that the nomogram was clinically useful.

CONCLUSIONS:

The first nomogram for predicting the prognosis of UPS patients has been constructed and validated. Its usability and performance showed that the nomogram can be applied to clinical practice. However, further external validation is still needed.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Nomograms / Histiocytoma, Malignant Fibrous Type of study: Prognostic_studies / Risk_factors_studies / Screening_studies Limits: Aged / Female / Humans / Male / Middle aged Language: En Journal: Cancer Control Journal subject: NEOPLASIAS Year: 2021 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Nomograms / Histiocytoma, Malignant Fibrous Type of study: Prognostic_studies / Risk_factors_studies / Screening_studies Limits: Aged / Female / Humans / Male / Middle aged Language: En Journal: Cancer Control Journal subject: NEOPLASIAS Year: 2021 Document type: Article Affiliation country: China
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