Cargando…
Development and validation of a nomogram for predicting survival in patients with malignant myofibroblastic tumor
BACKGROUND: Malignant myofibroblastic tumors are a rare group of soft tissue sarcomas, for which a prognosis prediction model is lacking. Based on the Surveillance, Epidemiology, and End Results (SEER) database and cases from Nanjing Drum Tower Hospital, the current study constructed and validated a...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10166985/ https://www.ncbi.nlm.nih.gov/pubmed/36951597 http://dx.doi.org/10.1002/cam4.5668 |
_version_ | 1785038564831002624 |
---|---|
author | Wang, Xiaolu Liu, Baorui Li, Rutian |
author_facet | Wang, Xiaolu Liu, Baorui Li, Rutian |
author_sort | Wang, Xiaolu |
collection | PubMed |
description | BACKGROUND: Malignant myofibroblastic tumors are a rare group of soft tissue sarcomas, for which a prognosis prediction model is lacking. Based on the Surveillance, Epidemiology, and End Results (SEER) database and cases from Nanjing Drum Tower Hospital, the current study constructed and validated a nomogram to assess overall survival of patients with malignant myofibroblastic tumors. METHODS: Data of patients with myofibroblastic tumors diagnosed between 2000 and 2018 were extracted from the SEER database. Similarly, data of patients with myofibroblastic tumor in Nanjing Drum Tower Hospital between May 2016 and March 2022 were collected. Then, we conducted univariate and multivariate Cox analyses to identify independent prognostic parameters to develop the nomogram. The model was evaluated by concordance index (C‐index), calibration curve, the area under the curve (AUC), decision curve analysis (DCA), Kaplan–Meier analysis, and subgroup analyses. RESULTS: Seven variables were selected to construct the nomogram. The results of the C‐index (0.783), calibration curve, the AUCs, and subgroup analyses demonstrated the accurate predictive capacity and excellent discriminative ability of the nomogram. The DCA of the model indicated its better clinical net benefit than that of the traditional system. CONCLUSION: Evaluation of the predictive performance of the nomogram revealed the superior sensitivity and specificity of the model and the higher prediction accuracy of the outcomes compared with those of the traditional system. The established nomogram may assist patients in consultation and help physicians in clinical decision‐making. |
format | Online Article Text |
id | pubmed-10166985 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101669852023-05-10 Development and validation of a nomogram for predicting survival in patients with malignant myofibroblastic tumor Wang, Xiaolu Liu, Baorui Li, Rutian Cancer Med RESEARCH ARTICLES BACKGROUND: Malignant myofibroblastic tumors are a rare group of soft tissue sarcomas, for which a prognosis prediction model is lacking. Based on the Surveillance, Epidemiology, and End Results (SEER) database and cases from Nanjing Drum Tower Hospital, the current study constructed and validated a nomogram to assess overall survival of patients with malignant myofibroblastic tumors. METHODS: Data of patients with myofibroblastic tumors diagnosed between 2000 and 2018 were extracted from the SEER database. Similarly, data of patients with myofibroblastic tumor in Nanjing Drum Tower Hospital between May 2016 and March 2022 were collected. Then, we conducted univariate and multivariate Cox analyses to identify independent prognostic parameters to develop the nomogram. The model was evaluated by concordance index (C‐index), calibration curve, the area under the curve (AUC), decision curve analysis (DCA), Kaplan–Meier analysis, and subgroup analyses. RESULTS: Seven variables were selected to construct the nomogram. The results of the C‐index (0.783), calibration curve, the AUCs, and subgroup analyses demonstrated the accurate predictive capacity and excellent discriminative ability of the nomogram. The DCA of the model indicated its better clinical net benefit than that of the traditional system. CONCLUSION: Evaluation of the predictive performance of the nomogram revealed the superior sensitivity and specificity of the model and the higher prediction accuracy of the outcomes compared with those of the traditional system. The established nomogram may assist patients in consultation and help physicians in clinical decision‐making. John Wiley and Sons Inc. 2023-03-23 /pmc/articles/PMC10166985/ /pubmed/36951597 http://dx.doi.org/10.1002/cam4.5668 Text en © 2023 The Authors. Cancer Medicine published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | RESEARCH ARTICLES Wang, Xiaolu Liu, Baorui Li, Rutian Development and validation of a nomogram for predicting survival in patients with malignant myofibroblastic tumor |
title | Development and validation of a nomogram for predicting survival in patients with malignant myofibroblastic tumor |
title_full | Development and validation of a nomogram for predicting survival in patients with malignant myofibroblastic tumor |
title_fullStr | Development and validation of a nomogram for predicting survival in patients with malignant myofibroblastic tumor |
title_full_unstemmed | Development and validation of a nomogram for predicting survival in patients with malignant myofibroblastic tumor |
title_short | Development and validation of a nomogram for predicting survival in patients with malignant myofibroblastic tumor |
title_sort | development and validation of a nomogram for predicting survival in patients with malignant myofibroblastic tumor |
topic | RESEARCH ARTICLES |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10166985/ https://www.ncbi.nlm.nih.gov/pubmed/36951597 http://dx.doi.org/10.1002/cam4.5668 |
work_keys_str_mv | AT wangxiaolu developmentandvalidationofanomogramforpredictingsurvivalinpatientswithmalignantmyofibroblastictumor AT liubaorui developmentandvalidationofanomogramforpredictingsurvivalinpatientswithmalignantmyofibroblastictumor AT lirutian developmentandvalidationofanomogramforpredictingsurvivalinpatientswithmalignantmyofibroblastictumor |