Sa1639 - Kyoto Classification of Gastritis is Useful for Detect the Patients with High Risk for Early Gastric Cancer in Japan

2018 ◽  
Vol 154 (6) ◽  
pp. S-338
Author(s):  
Tomoari Kamada ◽  
Ken Haruma ◽  
Kazuhiko Inoue ◽  
Noriaki Manabe ◽  
Jiro Hata ◽  
...  
JGH Open ◽  
2020 ◽  
Author(s):  
Yo Fujimoto ◽  
Yasumi Katayama ◽  
Yoshinori Gyotoku ◽  
Ryosuke Oura ◽  
Ikuhiro Kobori ◽  
...  

1998 ◽  
Author(s):  
L Saragoni ◽  
M Gaudio ◽  
A Vio ◽  
S Folli ◽  
O Nanni ◽  
...  

2017 ◽  
Vol 56 (6) ◽  
pp. 579-586 ◽  
Author(s):  
Mitsushige Sugimoto ◽  
Hiromitsu Ban ◽  
Hitomi Ichikawa ◽  
Shu Sahara ◽  
Taketo Otsuka ◽  
...  
Keyword(s):  

Gut ◽  
2020 ◽  
pp. gutjnl-2019-319926 ◽  
Author(s):  
Waku Hatta ◽  
Yosuke Tsuji ◽  
Toshiyuki Yoshio ◽  
Naomi Kakushima ◽  
Shu Hoteya ◽  
...  

ObjectiveBleeding after endoscopic submucosal dissection (ESD) for early gastric cancer (EGC) is a frequent adverse event after ESD. We aimed to develop and externally validate a clinically useful prediction model (BEST-J score: Bleeding after ESD Trend from Japan) for bleeding after ESD for EGC.DesignThis retrospective study enrolled patients who underwent ESD for EGC. Patients in the derivation cohort (n=8291) were recruited from 25 institutions, and patients in the external validation cohort (n=2029) were recruited from eight institutions in other areas. In the derivation cohort, weighted points were assigned to predictors of bleeding determined in the multivariate logistic regression analysis and a prediction model was established. External validation of the model was conducted to analyse discrimination and calibration.ResultsA prediction model comprised 10 variables (warfarin, direct oral anticoagulant, chronic kidney disease with haemodialysis, P2Y12 receptor antagonist, aspirin, cilostazol, tumour size >30 mm, lower-third in tumour location, presence of multiple tumours and interruption of each kind of antithrombotic agents). The rates of bleeding after ESD at low-risk (0 to 1 points), intermediate-risk (2 points), high-risk (3 to 4 points) and very high-risk (≥5 points) were 2.8%, 6.1%, 11.4% and 29.7%, respectively. In the external validation cohort, the model showed moderately good discrimination, with a c-statistic of 0.70 (95% CI, 0.64 to 0.76), and good calibration (calibration-in-the-large, 0.05; calibration slope, 1.01).ConclusionsIn this nationwide multicentre study, we derived and externally validated a prediction model for bleeding after ESD. This model may be a good clinical decision-making support tool for ESD in patients with EGC.


2019 ◽  
Vol 8 (9) ◽  
pp. 1310 ◽  
Author(s):  
Hong Jin Yoon ◽  
Seunghyup Kim ◽  
Jie-Hyun Kim ◽  
Ji-Soo Keum ◽  
Sang-Il Oh ◽  
...  

In early gastric cancer (EGC), tumor invasion depth is an important factor for determining the treatment method. However, as endoscopic ultrasonography has limitations when measuring the exact depth in a clinical setting as endoscopists often depend on gross findings and personal experience. The present study aimed to develop a model optimized for EGC detection and depth prediction, and we investigated factors affecting artificial intelligence (AI) diagnosis. We employed a visual geometry group(VGG)-16 model for the classification of endoscopic images as EGC (T1a or T1b) or non-EGC. To induce the model to activate EGC regions during training, we proposed a novel loss function that simultaneously measured classification and localization errors. We experimented with 11,539 endoscopic images (896 T1a-EGC, 809 T1b-EGC, and 9834 non-EGC). The areas under the curves of receiver operating characteristic curves for EGC detection and depth prediction were 0.981 and 0.851, respectively. Among the factors affecting AI prediction of tumor depth, only histologic differentiation was significantly associated, where undifferentiated-type histology exhibited a lower AI accuracy. Thus, the lesion-based model is an appropriate training method for AI in EGC. However, further improvements and validation are required, especially for undifferentiated-type histology.


Endoscopy ◽  
1974 ◽  
Vol 6 (04) ◽  
pp. 209-213 ◽  
Author(s):  
K. Murakami ◽  
F. Misaki ◽  
K. Shimamoto ◽  
K. Kawai

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