Literature DB >> 33811513

Development and evaluation of a ceMDCT-based preoperative risk stratification model to predict disease-free survival after radical surgery in patients with gastric cancer.

Caizhen Feng1, Jin Cheng1, Xiao Zeng1, Yinli Zhang2, Nan Hong1, Yingjiang Ye3, Yi Wang4.   

Abstract

PURPOSE: To develop and evaluate a preoperative risk stratification model for predicting disease-free survival (DFS) based on contrast-enhanced multidetector computed tomography (ceMDCT) images in patients with gastric cancer (GC) undergoing radical surgery.
METHODS: We retrospectively enrolled patients with GC who underwent ceMDCT followed by radical surgery. A preoperative risk stratification model was constructed (including risk factor selection, risk status scoring, and risk level assignment) using Cox proportional hazard regression and log-rank analyses in the training cohort; the model was tested in the validation cohort. A nomogram was used to compare the preoperative risk stratification model with a postoperative DFS prediction model.
RESULTS: A total of 462 patients (training/validation: 271/191) were included. The ceMDCT features of T category (score of 0 or 2), N category (0, 1, 2, or 3), extramural vessel invasion (0 or 2), and tumor location (0 or 1) were selected to construct the preoperative risk stratification model, with 4 risk levels defined based on risk score. There were significant differences in DFS among the risk levels in both cohorts (p < 0.001). The predictive value of the preoperative model was similar to that of the postoperative model, with concordance indices of 0.791 (95% CI, 0.743-0.837) and 0.739 (95% CI, 0.666-0.812), respectively, in the training cohort and 0.762 (95% CI, 0.696-0.828) and 0.738 (95% CI, 0.684-0.792), respectively, in the validation cohort.
CONCLUSION: A preoperative risk stratification model based on ceMDCT images could be used to predict DFS and thus classify GC cases into various risk levels.
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Gastric cancer; Nomogram; Preoperative; Prognosis; Risk

Mesh:

Year:  2021        PMID: 33811513     DOI: 10.1007/s00261-021-03049-0

Source DB:  PubMed          Journal:  Abdom Radiol (NY)


  3 in total

1.  Nomograms for Predicting Disease-Free Survival in Patients With Siewert Type II/III Adenocarcinoma of the Esophagogastric Junction Receiving Neoadjuvant Therapy and Radical Surgery.

Authors:  Zhenjiang Guo; Honghai Guo; Yuan Tian; Ze Zhang; Qun Zhao
Journal:  Front Oncol       Date:  2022-06-08       Impact factor: 5.738

2.  CT-detected extramural venous invasion-related gene signature for the overall survival prediction in patients with gastric cancer.

Authors:  Bo Gao; Caizhen Feng; Fan Chai; Shengcai Wei; Nan Hong; Yingjiang Ye; Yi Wang; Jin Cheng
Journal:  Cancer Med       Date:  2021-09-12       Impact factor: 4.452

3.  A computed tomography-based preoperative risk scoring system to distinguish lymphoepithelioma-like gastric carcinoma from non-lymphoepithelioma-like gastric carcinoma.

Authors:  Liming Li; Wenpeng Huang; Ping Hou; Weiwei Li; Menyun Feng; Yiyang Liu; Jianbo Gao
Journal:  Front Oncol       Date:  2022-09-15       Impact factor: 5.738

  3 in total

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