Open AccessSurvival prediction by Bayesian network modeling for pseudomyxoma peritonei after cytoreductive surgery plus hyperthermic intraperitoneal chemotherapy
Author(s) -
Zhao Xin,
Li Xinbao,
Lin Yulin,
Ma Ru,
Zhang Ying,
Xu Dazhao,
Li Yan
Publication year - 2023
Publication title -
cancer medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.403
H-Index - 53
ISSN - 2045-7634
DOI - 10.1002/cam4.5138
Subject(s) - pseudomyxoma peritonei , cytoreductive surgery , hyperthermic intraperitoneal chemotherapy , medicine , intraperitoneal chemotherapy , surgery , chemotherapy , appendix , cancer , paleontology , ovarian cancer , biology
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.