Prediction of preoperative peritoneal cancer index for pseudomyxoma peritonei by multiple linear regression analysis
BackgroundThe aim of the present study was to establish a predictive model to predict the peritoneal cancer index (PCI) preoperatively in patients with pseudomyxoma peritonei (PMP).MethodsA total of 372 PMP patients were consecutively included from a prospective follow-up database between 1 June 201...
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Frontiers Media S.A.
2024-12-01
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| Series: | Frontiers in Molecular Biosciences |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fmolb.2024.1512937/full |
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| author | Mingjian Bai Jing Feng Jie Liu Yunxiang Li Yueming Xu Fucun Ma Ruiqing Ma Guowei Liang Xuekai Liu Na Zhao |
| author_facet | Mingjian Bai Jing Feng Jie Liu Yunxiang Li Yueming Xu Fucun Ma Ruiqing Ma Guowei Liang Xuekai Liu Na Zhao |
| author_sort | Mingjian Bai |
| collection | DOAJ |
| description | BackgroundThe aim of the present study was to establish a predictive model to predict the peritoneal cancer index (PCI) preoperatively in patients with pseudomyxoma peritonei (PMP).MethodsA total of 372 PMP patients were consecutively included from a prospective follow-up database between 1 June 2013 and 1 June 2023. Nine potential variables, namely, gender, age, Barthel Index (BAI), hemoglobin (Hb), albumin (Alb), D-dimer, carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA 125), and CA 19-9, were estimated using multiple linear regression (MLR) analysis with a stepwise selection procedure. The established MLR model was internally validated using K-fold cross-validation. The agreement between the predicted and surgical PCI was assessed using Bland–Altman plots and intraclass correlation (ICC). A p-value of less than 0.05 was considered statistically significant.ResultsSix independent predictors were confirmed by the stepwise MLR analysis with an R2 value of 0.570. The predicted PCI formula was represented as follows: PCI = 19.567 + 2.091 * Gender (male = 1, female = 0) − 0.643 * Alb +4.201 * Lg (D-dimer) + 2.938 * Lg (CEA) + 5.441 * Lg (CA 125) + 1.802 * Lg (CA 19-9). The agreement between predicted and surgical PCI was assessed using Bland–Altman plots, showing a limit of agreement (LoA) between −15.847 (95%CI: −17.2646 to −14.4292) and +15.847 (95%CI: 14.4292–17.2646).ConclusionThis study represents the first attempt to use an MLR model for the preoperative prediction of PCI in PMP patients. Nevertheless, the MLR model did not perform well enough in predicting preoperative PCI. In the future, more advanced statistical techniques and a radiomics-based CT-PCI-participated MLR model will be developed, which may enhance the predictive ability of PCI. |
| format | Article |
| id | doaj-art-9c244a1ce8684327adddb3d9031317f6 |
| institution | Kabale University |
| issn | 2296-889X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Molecular Biosciences |
| spelling | doaj-art-9c244a1ce8684327adddb3d9031317f62024-12-23T05:10:21ZengFrontiers Media S.A.Frontiers in Molecular Biosciences2296-889X2024-12-011110.3389/fmolb.2024.15129371512937Prediction of preoperative peritoneal cancer index for pseudomyxoma peritonei by multiple linear regression analysisMingjian Bai0Jing Feng1Jie Liu2Yunxiang Li3Yueming Xu4Fucun Ma5Ruiqing Ma6Guowei Liang7Xuekai Liu8Na Zhao9Department of Clinical Laboratory, Aerospace Center Hospital, Beijing, ChinaDepartment of Clinical Laboratory, Aerospace Center Hospital, Beijing, ChinaDepartment of Clinical Laboratory, Aerospace Center Hospital, Beijing, ChinaDepartment of Clinical Laboratory, Aerospace Center Hospital, Beijing, ChinaDepartment of Literature and Science, University of Wisconsin-Madison, Madison, WI, United StatesDepartment of Clinical Laboratory, Aerospace Center Hospital, Beijing, ChinaDepartment of Myxoma, Aerospace Center Hospital, Beijing, ChinaDepartment of Clinical Laboratory, Aerospace Center Hospital, Beijing, ChinaDepartment of Clinical Laboratory, Aerospace Center Hospital, Beijing, ChinaDepartment of Nephrology, Aerospace Center Hospital, Beijing, ChinaBackgroundThe aim of the present study was to establish a predictive model to predict the peritoneal cancer index (PCI) preoperatively in patients with pseudomyxoma peritonei (PMP).MethodsA total of 372 PMP patients were consecutively included from a prospective follow-up database between 1 June 2013 and 1 June 2023. Nine potential variables, namely, gender, age, Barthel Index (BAI), hemoglobin (Hb), albumin (Alb), D-dimer, carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA 125), and CA 19-9, were estimated using multiple linear regression (MLR) analysis with a stepwise selection procedure. The established MLR model was internally validated using K-fold cross-validation. The agreement between the predicted and surgical PCI was assessed using Bland–Altman plots and intraclass correlation (ICC). A p-value of less than 0.05 was considered statistically significant.ResultsSix independent predictors were confirmed by the stepwise MLR analysis with an R2 value of 0.570. The predicted PCI formula was represented as follows: PCI = 19.567 + 2.091 * Gender (male = 1, female = 0) − 0.643 * Alb +4.201 * Lg (D-dimer) + 2.938 * Lg (CEA) + 5.441 * Lg (CA 125) + 1.802 * Lg (CA 19-9). The agreement between predicted and surgical PCI was assessed using Bland–Altman plots, showing a limit of agreement (LoA) between −15.847 (95%CI: −17.2646 to −14.4292) and +15.847 (95%CI: 14.4292–17.2646).ConclusionThis study represents the first attempt to use an MLR model for the preoperative prediction of PCI in PMP patients. Nevertheless, the MLR model did not perform well enough in predicting preoperative PCI. In the future, more advanced statistical techniques and a radiomics-based CT-PCI-participated MLR model will be developed, which may enhance the predictive ability of PCI.https://www.frontiersin.org/articles/10.3389/fmolb.2024.1512937/fullpseudomyxoma peritoneiperitoneal cancer indexpredictionmultiple linear regressionsurgery |
| spellingShingle | Mingjian Bai Jing Feng Jie Liu Yunxiang Li Yueming Xu Fucun Ma Ruiqing Ma Guowei Liang Xuekai Liu Na Zhao Prediction of preoperative peritoneal cancer index for pseudomyxoma peritonei by multiple linear regression analysis Frontiers in Molecular Biosciences pseudomyxoma peritonei peritoneal cancer index prediction multiple linear regression surgery |
| title | Prediction of preoperative peritoneal cancer index for pseudomyxoma peritonei by multiple linear regression analysis |
| title_full | Prediction of preoperative peritoneal cancer index for pseudomyxoma peritonei by multiple linear regression analysis |
| title_fullStr | Prediction of preoperative peritoneal cancer index for pseudomyxoma peritonei by multiple linear regression analysis |
| title_full_unstemmed | Prediction of preoperative peritoneal cancer index for pseudomyxoma peritonei by multiple linear regression analysis |
| title_short | Prediction of preoperative peritoneal cancer index for pseudomyxoma peritonei by multiple linear regression analysis |
| title_sort | prediction of preoperative peritoneal cancer index for pseudomyxoma peritonei by multiple linear regression analysis |
| topic | pseudomyxoma peritonei peritoneal cancer index prediction multiple linear regression surgery |
| url | https://www.frontiersin.org/articles/10.3389/fmolb.2024.1512937/full |
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