Prediction model for non-curative resection of endoscopic submucosal dissection in patients with early gastric cancer

Eun Hye Kim, Jun Chul Park, In Ji Song, Yeong Jin Kim, Dong Hoo Joh, Kyu Yeon Hahn, Yong Kang Lee, Ha Yan Kim, Hyunsoo Chung, Sung Kwan Shin, SangKil Lee, Yongchan Lee

Research output: Contribution to journalArticle

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Abstract

Background and Aims Endoscopic submucosal dissection (ESD) is a useful method for complete resection of early gastric cancer (EGC). However, there are still some patients who undergo additional gastrectomy after ESD because of non-curative resection. There is no model that can accurately predict non-curative resection of ESD. We aimed to create a model for predicting non-curative resection of ESD in patients with EGC. Patients and methods We reviewed the medical records, including all gross findings of EGC, of patients who underwent ESD for EGCs. We divided the patients into a non-curative resection group and a curative resection group. The clinicopathologic characteristics were compared between the groups to identify the risk factors for non-curative resection of ESD. We created a scoring system based on logistic regression modeling and bootstrap validation. Results Of 1639 patients who had undergone ESD for EGCs, 272 were identified as being treated non-curatively with ESD. A large tumor size (≥20 mm), tumor location in the upper body of the stomach, the presence of ulcer, fusion of gastric folds, the absence of mucosal nodularity, spontaneous bleeding, and undifferentiated tumor histology were associated with non-curative resection of ESD. Points of risk scores were assigned for these variables based on the β coefficient as follows: tumor size (≥20 mm), 2 points; tumor location in the upper body of the stomach, 1 point; ulcer, 2 points; fusion of gastric folds, 2 points; absence of mucosal nodularity, 1 point; spontaneous bleeding, 1 point; and undifferentiated histology, 2 points. Our risk scoring model showed good discriminatory performance on internal validation (bootstrap-corrected area under the receiver operating characteristic curve, 0.7004; 95% confidence interval, 0.6655-0.7353). Conclusions We developed a validated prediction model that can be used to identify patients who will undergo non-curative resection of ESD. Our prediction model can provide useful information for making decisions about the treatment of EGC before performing ESD.

Original languageEnglish
Pages (from-to)976-983
Number of pages8
JournalGastrointestinal Endoscopy
Volume85
Issue number5
DOIs
Publication statusPublished - 2017 May 1

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Stomach Neoplasms
Stomach
Neoplasms
Histology
Endoscopic Mucosal Resection
Hemorrhage
Stomach Ulcer
Gastrectomy
ROC Curve
Ulcer
Medical Records
Decision Making
Logistic Models
Confidence Intervals

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging
  • Gastroenterology

Cite this

Kim, Eun Hye ; Park, Jun Chul ; Song, In Ji ; Kim, Yeong Jin ; Joh, Dong Hoo ; Hahn, Kyu Yeon ; Lee, Yong Kang ; Kim, Ha Yan ; Chung, Hyunsoo ; Shin, Sung Kwan ; Lee, SangKil ; Lee, Yongchan. / Prediction model for non-curative resection of endoscopic submucosal dissection in patients with early gastric cancer. In: Gastrointestinal Endoscopy. 2017 ; Vol. 85, No. 5. pp. 976-983.
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title = "Prediction model for non-curative resection of endoscopic submucosal dissection in patients with early gastric cancer",
abstract = "Background and Aims Endoscopic submucosal dissection (ESD) is a useful method for complete resection of early gastric cancer (EGC). However, there are still some patients who undergo additional gastrectomy after ESD because of non-curative resection. There is no model that can accurately predict non-curative resection of ESD. We aimed to create a model for predicting non-curative resection of ESD in patients with EGC. Patients and methods We reviewed the medical records, including all gross findings of EGC, of patients who underwent ESD for EGCs. We divided the patients into a non-curative resection group and a curative resection group. The clinicopathologic characteristics were compared between the groups to identify the risk factors for non-curative resection of ESD. We created a scoring system based on logistic regression modeling and bootstrap validation. Results Of 1639 patients who had undergone ESD for EGCs, 272 were identified as being treated non-curatively with ESD. A large tumor size (≥20 mm), tumor location in the upper body of the stomach, the presence of ulcer, fusion of gastric folds, the absence of mucosal nodularity, spontaneous bleeding, and undifferentiated tumor histology were associated with non-curative resection of ESD. Points of risk scores were assigned for these variables based on the β coefficient as follows: tumor size (≥20 mm), 2 points; tumor location in the upper body of the stomach, 1 point; ulcer, 2 points; fusion of gastric folds, 2 points; absence of mucosal nodularity, 1 point; spontaneous bleeding, 1 point; and undifferentiated histology, 2 points. Our risk scoring model showed good discriminatory performance on internal validation (bootstrap-corrected area under the receiver operating characteristic curve, 0.7004; 95{\%} confidence interval, 0.6655-0.7353). Conclusions We developed a validated prediction model that can be used to identify patients who will undergo non-curative resection of ESD. Our prediction model can provide useful information for making decisions about the treatment of EGC before performing ESD.",
author = "Kim, {Eun Hye} and Park, {Jun Chul} and Song, {In Ji} and Kim, {Yeong Jin} and Joh, {Dong Hoo} and Hahn, {Kyu Yeon} and Lee, {Yong Kang} and Kim, {Ha Yan} and Hyunsoo Chung and Shin, {Sung Kwan} and SangKil Lee and Yongchan Lee",
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Kim, EH, Park, JC, Song, IJ, Kim, YJ, Joh, DH, Hahn, KY, Lee, YK, Kim, HY, Chung, H, Shin, SK, Lee, S & Lee, Y 2017, 'Prediction model for non-curative resection of endoscopic submucosal dissection in patients with early gastric cancer', Gastrointestinal Endoscopy, vol. 85, no. 5, pp. 976-983. https://doi.org/10.1016/j.gie.2016.10.018

Prediction model for non-curative resection of endoscopic submucosal dissection in patients with early gastric cancer. / Kim, Eun Hye; Park, Jun Chul; Song, In Ji; Kim, Yeong Jin; Joh, Dong Hoo; Hahn, Kyu Yeon; Lee, Yong Kang; Kim, Ha Yan; Chung, Hyunsoo; Shin, Sung Kwan; Lee, SangKil; Lee, Yongchan.

In: Gastrointestinal Endoscopy, Vol. 85, No. 5, 01.05.2017, p. 976-983.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Prediction model for non-curative resection of endoscopic submucosal dissection in patients with early gastric cancer

AU - Kim, Eun Hye

AU - Park, Jun Chul

AU - Song, In Ji

AU - Kim, Yeong Jin

AU - Joh, Dong Hoo

AU - Hahn, Kyu Yeon

AU - Lee, Yong Kang

AU - Kim, Ha Yan

AU - Chung, Hyunsoo

AU - Shin, Sung Kwan

AU - Lee, SangKil

AU - Lee, Yongchan

PY - 2017/5/1

Y1 - 2017/5/1

N2 - Background and Aims Endoscopic submucosal dissection (ESD) is a useful method for complete resection of early gastric cancer (EGC). However, there are still some patients who undergo additional gastrectomy after ESD because of non-curative resection. There is no model that can accurately predict non-curative resection of ESD. We aimed to create a model for predicting non-curative resection of ESD in patients with EGC. Patients and methods We reviewed the medical records, including all gross findings of EGC, of patients who underwent ESD for EGCs. We divided the patients into a non-curative resection group and a curative resection group. The clinicopathologic characteristics were compared between the groups to identify the risk factors for non-curative resection of ESD. We created a scoring system based on logistic regression modeling and bootstrap validation. Results Of 1639 patients who had undergone ESD for EGCs, 272 were identified as being treated non-curatively with ESD. A large tumor size (≥20 mm), tumor location in the upper body of the stomach, the presence of ulcer, fusion of gastric folds, the absence of mucosal nodularity, spontaneous bleeding, and undifferentiated tumor histology were associated with non-curative resection of ESD. Points of risk scores were assigned for these variables based on the β coefficient as follows: tumor size (≥20 mm), 2 points; tumor location in the upper body of the stomach, 1 point; ulcer, 2 points; fusion of gastric folds, 2 points; absence of mucosal nodularity, 1 point; spontaneous bleeding, 1 point; and undifferentiated histology, 2 points. Our risk scoring model showed good discriminatory performance on internal validation (bootstrap-corrected area under the receiver operating characteristic curve, 0.7004; 95% confidence interval, 0.6655-0.7353). Conclusions We developed a validated prediction model that can be used to identify patients who will undergo non-curative resection of ESD. Our prediction model can provide useful information for making decisions about the treatment of EGC before performing ESD.

AB - Background and Aims Endoscopic submucosal dissection (ESD) is a useful method for complete resection of early gastric cancer (EGC). However, there are still some patients who undergo additional gastrectomy after ESD because of non-curative resection. There is no model that can accurately predict non-curative resection of ESD. We aimed to create a model for predicting non-curative resection of ESD in patients with EGC. Patients and methods We reviewed the medical records, including all gross findings of EGC, of patients who underwent ESD for EGCs. We divided the patients into a non-curative resection group and a curative resection group. The clinicopathologic characteristics were compared between the groups to identify the risk factors for non-curative resection of ESD. We created a scoring system based on logistic regression modeling and bootstrap validation. Results Of 1639 patients who had undergone ESD for EGCs, 272 were identified as being treated non-curatively with ESD. A large tumor size (≥20 mm), tumor location in the upper body of the stomach, the presence of ulcer, fusion of gastric folds, the absence of mucosal nodularity, spontaneous bleeding, and undifferentiated tumor histology were associated with non-curative resection of ESD. Points of risk scores were assigned for these variables based on the β coefficient as follows: tumor size (≥20 mm), 2 points; tumor location in the upper body of the stomach, 1 point; ulcer, 2 points; fusion of gastric folds, 2 points; absence of mucosal nodularity, 1 point; spontaneous bleeding, 1 point; and undifferentiated histology, 2 points. Our risk scoring model showed good discriminatory performance on internal validation (bootstrap-corrected area under the receiver operating characteristic curve, 0.7004; 95% confidence interval, 0.6655-0.7353). Conclusions We developed a validated prediction model that can be used to identify patients who will undergo non-curative resection of ESD. Our prediction model can provide useful information for making decisions about the treatment of EGC before performing ESD.

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