Abstract:
OBJECTIVE:Bleeding 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. DESIGN:This 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. RESULTS:A 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). CONCLUSIONS:In 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.
journal_name
Gutjournal_title
Gutauthors
Hatta W,Tsuji Y,Yoshio T,Kakushima N,Hoteya S,Doyama H,Nagami Y,Hikichi T,Kobayashi M,Morita Y,Sumiyoshi T,Iguchi M,Tomida H,Inoue T,Koike T,Mikami T,Hasatani K,Nishikawa J,Matsumura T,Nebiki H,Nakamatsu D,Ohnitdoi
10.1136/gutjnl-2019-319926subject
Has Abstractpub_date
2020-06-04 00:00:00eissn
0017-5749issn
1468-3288pii
gutjnl-2019-319926pub_type
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