Construction of a Nomogram Model for Predicting Peritoneal Dissemination in Gastric Cancer Based on Clinicopathologic Features and Preoperative Serum Tumor Markers

BackgroundPeritoneal dissemination (PD) is the most common mode of metastasis for advanced gastric cancer (GC) with poor prognosis. It is of great significance to accurately predict preoperative PD and develop optimal treatment strategies for GC patients. Our study assessed the diagnostic potential...

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Main Authors: Dandan Bao, Zhangwei Yang, Senrui Chen, Keqin Li, Yiren Hu
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-06-01
Series:Frontiers in Oncology
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.844786/full
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author Dandan Bao
Zhangwei Yang
Senrui Chen
Keqin Li
Yiren Hu
Yiren Hu
author_facet Dandan Bao
Zhangwei Yang
Senrui Chen
Keqin Li
Yiren Hu
Yiren Hu
author_sort Dandan Bao
collection DOAJ
description BackgroundPeritoneal dissemination (PD) is the most common mode of metastasis for advanced gastric cancer (GC) with poor prognosis. It is of great significance to accurately predict preoperative PD and develop optimal treatment strategies for GC patients. Our study assessed the diagnostic potential of serum tumor markers and clinicopathologic features, to improve the accuracy of predicting the presence of PD in GC patients.MethodsIn our study, 1264 patients with GC at Fudan University Shanghai Cancer Center and Wenzhou people’s hospital from 2018 to 2020 were retrospectively analyzed, including 316 cases of PD and 948 cases without PD. All patients underwent enhanced CT scan or magnetic resonance imaging (MRI) before surgery and treatment. Clinicopathological features, including tumor diameter and tumor stage (depth of tumor invasion, nearby lymph node metastasis and distant metastasis), were obtained by imaging examination. The independent risk factors for PD were screened through univariate and multivariate logistic regression analyses, and the results were expressed with 95% confidence intervals (CIs). A model of PD diagnosis and prediction was established by using Cox proportional hazards regression model of training set. Furthermore, the accuracy of the prediction model was verified by ROC curve and calibration plots.ResultsUnivariate analysis showed that PD in GC was significantly related to tumor diameter (odds ratio (OR)=12.06, p<0.0006), depth of invasion (OR=14.55, p<0.0001), lymph node metastases (OR=5.89, p<0.0001), carcinoembryonic antigen (CEA) (OR=2.50, p<0.0001), CA125 (OR=11.46, p<0.0001), CA72-4 (OR=4.09, p<0.0001), CA19-9 (OR=2.74, p<0.0001), CA50 (OR=5.20, p<0.0001) and CA242 (OR=3.83, p<0.0001). Multivariate analysis revealed that clinical invasion depth and serum marker of CA125 and CA72-4 were independent risk factors for PD. The prediction model was established based on the risk factors using the R program. The area under the curve (AUC) of the receiver operating characteristics (ROC) was 0.931 (95% CI: 0.900–0.960), with the accuracy, sensitivity and specificity values of 90.5%, 86.2% and 82.2%, respectively.ConclusionThe nomogram model constructed using CA125, CA72-4 and depth of invasion increases the accuracy and sensitivity in predicting the incidence of PD in GC patients and can be used as an important tool for preoperative diagnosis.
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spelling doaj.art-4f9907a6e9ea4a0fa15eb0465d58278b2022-12-22T00:37:34ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2022-06-011210.3389/fonc.2022.844786844786Construction of a Nomogram Model for Predicting Peritoneal Dissemination in Gastric Cancer Based on Clinicopathologic Features and Preoperative Serum Tumor MarkersDandan Bao0Zhangwei Yang1Senrui Chen2Keqin Li3Yiren Hu4Yiren Hu5Department of General Surgery, The Third Clinical Institute Affiliated to Wenzhou Medical University, The Third Affiliated hospital of Shanghai University, Wenzhou People’s Hospital, Wenzhou, ChinaDepartment of General Surgery, The Third Clinical Institute Affiliated to Wenzhou Medical University, The Third Affiliated hospital of Shanghai University, Wenzhou People’s Hospital, Wenzhou, ChinaDepartment of General Surgery, The Third Clinical Institute Affiliated to Wenzhou Medical University, The Third Affiliated hospital of Shanghai University, Wenzhou People’s Hospital, Wenzhou, ChinaDepartment of General Surgery, The Third Clinical Institute Affiliated to Wenzhou Medical University, The Third Affiliated hospital of Shanghai University, Wenzhou People’s Hospital, Wenzhou, ChinaDepartment of General Surgery, The Third Clinical Institute Affiliated to Wenzhou Medical University, The Third Affiliated hospital of Shanghai University, Wenzhou People’s Hospital, Wenzhou, ChinaDepartment of General Surgery, Medical College of Soochow University, Soochow, ChinaBackgroundPeritoneal dissemination (PD) is the most common mode of metastasis for advanced gastric cancer (GC) with poor prognosis. It is of great significance to accurately predict preoperative PD and develop optimal treatment strategies for GC patients. Our study assessed the diagnostic potential of serum tumor markers and clinicopathologic features, to improve the accuracy of predicting the presence of PD in GC patients.MethodsIn our study, 1264 patients with GC at Fudan University Shanghai Cancer Center and Wenzhou people’s hospital from 2018 to 2020 were retrospectively analyzed, including 316 cases of PD and 948 cases without PD. All patients underwent enhanced CT scan or magnetic resonance imaging (MRI) before surgery and treatment. Clinicopathological features, including tumor diameter and tumor stage (depth of tumor invasion, nearby lymph node metastasis and distant metastasis), were obtained by imaging examination. The independent risk factors for PD were screened through univariate and multivariate logistic regression analyses, and the results were expressed with 95% confidence intervals (CIs). A model of PD diagnosis and prediction was established by using Cox proportional hazards regression model of training set. Furthermore, the accuracy of the prediction model was verified by ROC curve and calibration plots.ResultsUnivariate analysis showed that PD in GC was significantly related to tumor diameter (odds ratio (OR)=12.06, p<0.0006), depth of invasion (OR=14.55, p<0.0001), lymph node metastases (OR=5.89, p<0.0001), carcinoembryonic antigen (CEA) (OR=2.50, p<0.0001), CA125 (OR=11.46, p<0.0001), CA72-4 (OR=4.09, p<0.0001), CA19-9 (OR=2.74, p<0.0001), CA50 (OR=5.20, p<0.0001) and CA242 (OR=3.83, p<0.0001). Multivariate analysis revealed that clinical invasion depth and serum marker of CA125 and CA72-4 were independent risk factors for PD. The prediction model was established based on the risk factors using the R program. The area under the curve (AUC) of the receiver operating characteristics (ROC) was 0.931 (95% CI: 0.900–0.960), with the accuracy, sensitivity and specificity values of 90.5%, 86.2% and 82.2%, respectively.ConclusionThe nomogram model constructed using CA125, CA72-4 and depth of invasion increases the accuracy and sensitivity in predicting the incidence of PD in GC patients and can be used as an important tool for preoperative diagnosis.https://www.frontiersin.org/articles/10.3389/fonc.2022.844786/fullgastric cancerperitoneal disseminationprediction nomogramserum tumor markersrisk factors
spellingShingle Dandan Bao
Zhangwei Yang
Senrui Chen
Keqin Li
Yiren Hu
Yiren Hu
Construction of a Nomogram Model for Predicting Peritoneal Dissemination in Gastric Cancer Based on Clinicopathologic Features and Preoperative Serum Tumor Markers
Frontiers in Oncology
gastric cancer
peritoneal dissemination
prediction nomogram
serum tumor markers
risk factors
title Construction of a Nomogram Model for Predicting Peritoneal Dissemination in Gastric Cancer Based on Clinicopathologic Features and Preoperative Serum Tumor Markers
title_full Construction of a Nomogram Model for Predicting Peritoneal Dissemination in Gastric Cancer Based on Clinicopathologic Features and Preoperative Serum Tumor Markers
title_fullStr Construction of a Nomogram Model for Predicting Peritoneal Dissemination in Gastric Cancer Based on Clinicopathologic Features and Preoperative Serum Tumor Markers
title_full_unstemmed Construction of a Nomogram Model for Predicting Peritoneal Dissemination in Gastric Cancer Based on Clinicopathologic Features and Preoperative Serum Tumor Markers
title_short Construction of a Nomogram Model for Predicting Peritoneal Dissemination in Gastric Cancer Based on Clinicopathologic Features and Preoperative Serum Tumor Markers
title_sort construction of a nomogram model for predicting peritoneal dissemination in gastric cancer based on clinicopathologic features and preoperative serum tumor markers
topic gastric cancer
peritoneal dissemination
prediction nomogram
serum tumor markers
risk factors
url https://www.frontiersin.org/articles/10.3389/fonc.2022.844786/full
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