Article
Oncology
Hengfei Gao, Kangkang Ji, Linsen Bao, Hao Chen, Chen Lin, Min Feng, Liang Tao, Meng Wang
Summary: A prediction nomogram for occult peritoneal metastasis in gastric cancer has been developed, which shows excellent diagnostic performance and has the potential to enhance diagnostic accuracy for occult peritoneal metastasis in gastric cancer patients.
WORLD JOURNAL OF SURGICAL ONCOLOGY
(2023)
Article
Oncology
Shuxiang Chen, Huijuan Zhang, Hong Wei, Yongxiu Tong, Xiaofang Chen
Summary: This study aimed to develop a practical nomogram based on comprehensive CT texture analysis and conventional CT signs to predict occult peritoneal metastasis (PM) in patients with gastric cancer (GC). The study found that specific CT signs and texture features of the primary tumor and peritoneum could be used as independent predictors for occult PM. A nomogram was constructed, and different prediction models were developed. The joint model, including CT signs and texture parameters, showed the best predictive performance. The nomogram demonstrated good consistency between the predicted and observed PM.
FRONTIERS IN ONCOLOGY
(2022)
Article
Oncology
Jia Yang, Hongtao Su, Tao Chen, Xinhua Chen, Hao Chen, Guoxin Li, Jiang Yu
Summary: This study aimed to develop a clinical radiomics nomogram to better predict peritoneal metastases in patients with gastric cancer. The results showed that the clinical predictive models combined with clinical risk factors and radiomics features had good performance in predicting peritoneal metastasis in gastric cancer.
Article
Oncology
Annamaria Agnes, Alberto Biondi, Roberto Persiani, Antonio Laurino, Rossella Reddavid, Maurizio De Giuli, Federico Sicoli, Ferdinando Cananzi, Stefano De Pascale, Uberto Fumagalli, Federica Galli, Stefano Rausei, Laura Lorenzon, Domenico D'Ugo
Summary: Two risk models (PERI-Gastric 1 and 2) were developed to assess the risk of peritoneal recurrence after curative-aim gastrectomy, based on multivariable logistic regression results and discrimination evaluation using the area under the receiver operating curve. These models could guide the use of prophylactic treatments.
Article
Oncology
Xian-qing Song, Zhi-xian Liu, Qing-yuan Kong, Zhen-hua He, Sen Zhang
Summary: This study successfully developed and validated a nomogram for effectively predicting the risk of peritoneal metastasis in colorectal cancer, providing a basis for early diagnosis. Through a retrospective analysis of 1284 patients with colorectal cancer, independent risk factors influencing peritoneal metastasis risk were identified. Internal validation showed that the nomogram has high predictive accuracy.
FRONTIERS IN ONCOLOGY
(2022)
Article
Oncology
Xianhe Shen, Huilan Liu, Haihua Zhou, Zhiyi Cheng, Guiyuan Liu, Chuanjiang Huang, Rongrong Dou, Fuxing Liu, Xiaolan You
Summary: This study revealed the regulatory role of Galectin-1 in gastric cancer (GC) cell peritoneal metastasis. Galectin-1 enhanced the adhesion ability of GC cells to peritoneal mesothelial cells and promoted the expression of collagen, leading to the occurrence of peritoneal metastasis.
Article
Oncology
Zifeng Yang, Yong Li, Xiusen Qin, Zejian Lv, Huaiming Wang, Deqing Wu, Zixu Yuan, Hui Wang
Summary: A predictive nomogram was developed using multicenter data to predict the overall survival in CRC patients with S-PM, showing good discriminative ability and high accuracy.
FRONTIERS IN ONCOLOGY
(2021)
Article
Oncology
Fawaz Jade, Pocard Marc, Liberale Gabriel, Eveno Clarisse, Malgras Brice, Sideris Lucas, Huebner Martin, Sabbagh Charles, Sgarbura Olivia, Taibi Abdelkader, Hobeika Christian
Summary: A tool was created to refine the timing of early second-look laparoscopic exploration in patients at high risk of peritoneal metastasis recurrence after colon cancer surgery. The study found that synchronous limited peritoneal metastasis and/or ovarian metastasis were associated with very high-risk patients requiring early second-look laparoscopic exploration.
JOURNAL OF SURGICAL ONCOLOGY
(2023)
Article
Oncology
Yue Jiang, Fangfang Chen, Xunshan Ren, Yu Yang, Jiajun Luo, Jingwen Yuan, Jingping Yuan, Qiang Tong
Summary: This study demonstrates that a signature consisting of four RNA-binding proteins (RBP) can predict the possibility of peritoneal metastasis (PM) in gastric cancer (GC) patients, with a similar predictive accuracy compared to the TNM staging system. Additionally, the combination of the classifier and TNM staging enhances the predictive capability.
FRONTIERS IN ONCOLOGY
(2022)
Article
Cell Biology
Yu Mei, Shuo Wang, Tienan Feng, Min Yan, Fei Yuan, Zhenggang Zhu, Tian Li, Zhenglun Zhu
Summary: The study established a nomogram for predicting lymph node metastasis in early gastric cancer, with age, tumor size, submucosal invasion, histological subtype, and HER2 positivity identified as independent risk factors. The model showed good performance in both internal and external validation, with the prediction model providing a higher net benefit for guiding treatment.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2021)
Article
Medicine, General & Internal
Yuming Jiang, Xiaokun Liang, Wei Wang, Chuanli Chen, Qingyu Yuan, Xiaodong Zhang, Na Li, Hao Chen, Jiang Yu, Yaoqin Xie, Yikai Xu, Zhiwei Zhou, Guoxin Li, Ruijiang Li
Summary: The study showed that the deep learning model PMetNet based on preoperative CT images can reliably predict occult peritoneal metastasis, aiding in individualized preoperative treatment decisions and avoiding unnecessary surgeries and complications.
Article
Oncology
Xueer Zheng, Kaibo Guo, Harpreet S. Wasan, Shanming Ruan
Summary: In this study, risk factors for lymph node metastasis and distant metastasis in T1 gastric cancer patients were identified through retrospective analysis. Nomograms were established to predict these outcomes and overall survival, showing high efficiency of discrimination and accuracy. These user-friendly tools may have advantageous clinical utility in guiding individual therapeutic strategies for high-risk T1 gastric cancer patients.
AMERICAN JOURNAL OF CANCER RESEARCH
(2021)
Article
Biochemistry & Molecular Biology
Xiao-Jiang Chen, Cheng-Zhi Wei, Jun Lin, Ruo-Peng Zhang, Guo-Ming Chen, Yuan-Fang Li, Run-Cong Nie, Yong-Ming Chen
Summary: This study analyzed the relationship between PD-L1 expression and prognosis in gastric cancer patients with peritoneal metastasis, and found that high PD-L1 expression was associated with better prognosis.
Article
Medicine, General & Internal
Fang Huang, Meihua Fang
Summary: This study aimed to establish a prediction model for liver metastasis in patients with gastric cancer (GC). Through a retrospective cohort study, clinical data was collected and a prediction model was constructed. The results showed that the model had good predictive ability and could assist clinicians in making personalized predictions and adjusting treatment strategies in a timely manner.
Article
Oncology
Norihito Kubo, Hyunsoon Cho, Dahhay Lee, Hannah Yang, Youngsook Kim, Harbi Khalayleh, Hong Man Yoon, Keun Won Ryu, George B. Hanna, Daniel G. Coit, Kenichi Hakamada, Young -Woo Kim
Summary: This study identified clinicopathologic factors associated with the risk of peritoneal seeding in advanced gastric cancer and constructed a clinically useful tool for selective diagnostic laparoscopy in high-risk patients.