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Survival prediction by Bayesian network modeling for pseudomyxoma peritonei after cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy
OBJECTIVES: To establish a survival prognostic model for pseudomyxoma peritonei (PMP) treated with cytoreductive surgery (CRS) plus hyperthermic intraperitoneal chemotherapy (HIPEC) based on Bayesian network (BN). METHODS: 453 PMP patients were included from the database at our center. The dataset w...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9939117/ https://www.ncbi.nlm.nih.gov/pubmed/36054637 http://dx.doi.org/10.1002/cam4.5138 |
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author | Zhao, Xin Li, Xinbao Lin, Yulin Ma, Ru Zhang, Ying Xu, Dazhao Li, Yan |
author_facet | Zhao, Xin Li, Xinbao Lin, Yulin Ma, Ru Zhang, Ying Xu, Dazhao Li, Yan |
author_sort | Zhao, Xin |
collection | PubMed |
description | OBJECTIVES: To establish a survival prognostic model for pseudomyxoma peritonei (PMP) treated with cytoreductive surgery (CRS) plus hyperthermic intraperitoneal chemotherapy (HIPEC) based on Bayesian network (BN). METHODS: 453 PMP patients were included from the database at our center. The dataset was divided into a training set to establish BN model and a testing set to perform internal validation at a ratio of 8:2. From the training set, univariate and multivariate analyses were performed to identify independent prognostic factors for BN model construction. The confusion matrix, receiver operating characteristic (ROC) curve and the area under curve (AUC) were used to evaluate the performance of the BN model. RESULTS: The univariate and multivariate analyses identified 7 independent prognostic factors: gender, previous operation history, histological grading, lymphatic metastasis, peritoneal cancer index, completeness of cytoreduction and splenectomy (all p < 0.05). Based on independent factors, the BN model of training set was established. After internal validation, the accuracy and AUC of the BN model were 70.3% and 73.5%, respectively. CONCLUSION: The BN model provides a reasonable level of predictive performance for PMP patients undergoing CRS + HIPEC. |
format | Online Article Text |
id | pubmed-9939117 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99391172023-02-20 Survival prediction by Bayesian network modeling for pseudomyxoma peritonei after cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy Zhao, Xin Li, Xinbao Lin, Yulin Ma, Ru Zhang, Ying Xu, Dazhao Li, Yan Cancer Med RESEARCH ARTICLES OBJECTIVES: To establish a survival prognostic model for pseudomyxoma peritonei (PMP) treated with cytoreductive surgery (CRS) plus hyperthermic intraperitoneal chemotherapy (HIPEC) based on Bayesian network (BN). METHODS: 453 PMP patients were included from the database at our center. The dataset was divided into a training set to establish BN model and a testing set to perform internal validation at a ratio of 8:2. From the training set, univariate and multivariate analyses were performed to identify independent prognostic factors for BN model construction. The confusion matrix, receiver operating characteristic (ROC) curve and the area under curve (AUC) were used to evaluate the performance of the BN model. RESULTS: The univariate and multivariate analyses identified 7 independent prognostic factors: gender, previous operation history, histological grading, lymphatic metastasis, peritoneal cancer index, completeness of cytoreduction and splenectomy (all p < 0.05). Based on independent factors, the BN model of training set was established. After internal validation, the accuracy and AUC of the BN model were 70.3% and 73.5%, respectively. CONCLUSION: The BN model provides a reasonable level of predictive performance for PMP patients undergoing CRS + HIPEC. John Wiley and Sons Inc. 2022-08-21 /pmc/articles/PMC9939117/ /pubmed/36054637 http://dx.doi.org/10.1002/cam4.5138 Text en © 2022 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 Zhao, Xin Li, Xinbao Lin, Yulin Ma, Ru Zhang, Ying Xu, Dazhao Li, Yan Survival prediction by Bayesian network modeling for pseudomyxoma peritonei after cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy |
title | Survival prediction by Bayesian network modeling for pseudomyxoma peritonei after cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy |
title_full | Survival prediction by Bayesian network modeling for pseudomyxoma peritonei after cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy |
title_fullStr | Survival prediction by Bayesian network modeling for pseudomyxoma peritonei after cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy |
title_full_unstemmed | Survival prediction by Bayesian network modeling for pseudomyxoma peritonei after cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy |
title_short | Survival prediction by Bayesian network modeling for pseudomyxoma peritonei after cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy |
title_sort | survival prediction by bayesian network modeling for pseudomyxoma peritonei after cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy |
topic | RESEARCH ARTICLES |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9939117/ https://www.ncbi.nlm.nih.gov/pubmed/36054637 http://dx.doi.org/10.1002/cam4.5138 |
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