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ABSTRACT: Background
To investigate the association between CT signs and clinicopathological features and disease recurrence in patients with hepatoid adenocarcinoma of stomach (HAS).Methods
Forty nine HAS patients undergoing radical surgery were retrospectively collected. Association between CT and clinicopathological features and disease recurrence was analyzed. Multivariate logistic model was constructed and evaluated for predicting recurrence by using receiver operating characteristic (ROC) curve. Survival curves between model-defined risk groups was compared using Kaplan-Meier method.Results
24(49.0%) patients developed disease recurrence. Multivariate logistic analysis results showed elevated serum CEA level, peritumoral fatty space invasion and positive pathological vascular tumor thrombus were independent factors for disease recurrence. Odds ratios were 10.87 (95%CI, 1.14-103.66), 6.83 (95%CI, 1.08-43.08) and 42.67 (95%CI, 3.66-496.85), respectively. The constructed model showed an area under ROC of 0.912 (95%CI,0.825-0.999). The model-defined high-risk group showed poorer overall survival and recurrence-free survival than the low-risk group (both P < 0.001).Conclusions
Preoperative CT appearance of peritumoral fatty space invasion, elevated serum CEA level, and pathological vascular tumor thrombus indicated poor prognosis of HAS patients.
SUBMITTER: Yan XY
PROVIDER: S-EPMC10604919 | biostudies-literature | 2023 Oct
REPOSITORIES: biostudies-literature
Yan Xin-Yue XY Ju Hai-Yue HY Hou Fang-Jing FJ Li Xiao-Ting XT Yang Ding D Tang Lei L Wang Ya-Kun YK Li Zhong-Wu ZW Sun Ying-Shi YS Gao Shun-Yu SY
BMC medical imaging 20231026 1
<h4>Background</h4>To investigate the association between CT signs and clinicopathological features and disease recurrence in patients with hepatoid adenocarcinoma of stomach (HAS).<h4>Methods</h4>Forty nine HAS patients undergoing radical surgery were retrospectively collected. Association between CT and clinicopathological features and disease recurrence was analyzed. Multivariate logistic model was constructed and evaluated for predicting recurrence by using receiver operating characteristic ...[more]