- ICH GCP
- 미국 임상 시험 레지스트리
- 임상시험 NCT01491724
The Learning Curve of Probe-based Confocal Laser Endomicroscopy (pCLE) Images Interpretation in Gastric Intestinal Metaplasia (GIM)
The Learning Curve of Probe-based Confocal Laser Endomicroscopy (pCLE) Images Interpretation in Gastric Intestinal Metaplasia(GIM)
The Learning Curve of Probe-based Confocal Laser Endomicroscopy (pCLE) images interpretation in Gastric Intestinal Metaplasia (GIM)
Objective:
The aim of this study is to evaluate the learning curve of pCLE images interpretation in GIM.
Research design:
Blinded review of pCLE images for the diagnosis of GIM
Sample size:
Five beginner endoscopists will be assigned in this study to read approximately 80 videoclips
Data analysis:
ROC curve is analyzed by SPSS version 16.
Expected Benefit and Clinical Application Information on the learning curve for GIM interpretation from pCLE images in order to develop early gastric cancer detection
연구 개요
상태
정황
상세 설명
Background and Rationale:
Gastric cancer remains the second leading cause of cancer related death in the world. The incidence and mortality rate is predominant in East Asia[1]. Usually, gastric cancer is asymptomatic in early stage; therefore, most patients are in the advanced stage and incurable at diagnosis. The pathogenesis of intestinal type gastric cancer is sequential and multistep pathway. Gastric intestinal metaplasia (GIM) is the precancerous lesion for intestinal type gastric cancer[2]. The strategies which can detect precancerous and/or early cancerous transformation are very beneficial because only early gastric cancer can potentially be cured by endoscopic treatment. Probe-based confocal laser endomicroscope or pCLE is useful for GIM detection with 94% in sensitivity[3]. However, this perfect sensitivity in pCLE interpretation is provided in only expertise. We still do not know how to be an expert in GIM interpretation. No study about learning curve in GIM interpretation by pCLE published
Observation and Measurement:
Collect the accuracy in GIM interpretation from pCLE reported in ROC curve
Methodology:
- Six inexperienced pCLE readers were recruited.
- All inexperienced pCLE readers must attend the learning session.
- Self-review from CD is recommended for all inexperienced pCLE readers
- Two-week interval for examination in GIM interpretation from 20 new histology-proved pCLE images (GIM and normal mucosa) for 5 sessions are on schedule after training session.
- All Inexperienced pCLE readers need to review the training CD at least a day before each examination.
- The accuracy rate in each examination will be recorded individually for each inexperienced pCLE reader.
- ROC curve is reported for learning curve in GIM interpretation from pCLE images.
Data collection:
All data will be processed and recorded by one physician.
연구 유형
등록 (예상)
연락처 및 위치
연구 장소
-
-
-
Bangkok, 태국, 10330
- 모병
- Rapat Pittayanon
-
연락하다:
- Rapat Pittayanon, MD
- 전화번호: 66813132112
- 이메일: rapat125@gmail.com
-
연락하다:
- Nuttapaht Namjud, M.Sc
- 전화번호: 66894971957
- 이메일: ampere_nut@hotmail.com
-
부수사관:
- Rungsun Rerknimitr, Professor
-
수석 연구원:
- Rapat Pittayanon, MD
-
-
참여기준
자격 기준
공부할 수 있는 나이
- 어린이
- 성인
- 고령자
건강한 자원 봉사자를 받아들입니다
연구 대상 성별
샘플링 방법
연구 인구
설명
Inclusion Criteria:
- First year fellow of gastroenterologist who never have the experienced in pCLE interpretation.
공부 계획
연구는 어떻게 설계됩니까?
디자인 세부사항
코호트 및 개입
그룹/코호트 |
|---|
|
pCLE images
|
연구는 무엇을 측정합니까?
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
|
The change of accuracy of pCLE images interpretation in GIM after each examination
기간: Baseline and every 2 weeks for 4 sessions
|
Percentage of accuracy changing in each examination
|
Baseline and every 2 weeks for 4 sessions
|
공동 작업자 및 조사자
수사관
- 연구 책임자: Rungsun Rerknimitr, Professor, King Chulalongkorn Memorial Hospital
- 수석 연구원: Rapat Pittayanon, MD, King Chulalongkron Memorial Hospital
간행물 및 유용한 링크
유용한 링크
연구 기록 날짜
연구 주요 날짜
연구 시작
기본 완료 (예상)
연구 완료 (예상)
연구 등록 날짜
최초 제출
QC 기준을 충족하는 최초 제출
처음 게시됨 (추정)
연구 기록 업데이트
마지막 업데이트 게시됨 (추정)
QC 기준을 충족하는 마지막 업데이트 제출
마지막으로 확인됨
추가 정보
이 정보는 변경 없이 clinicaltrials.gov 웹사이트에서 직접 가져온 것입니다. 귀하의 연구 세부 정보를 변경, 제거 또는 업데이트하도록 요청하는 경우 register@clinicaltrials.gov. 문의하십시오. 변경 사항이 clinicaltrials.gov에 구현되는 즉시 저희 웹사이트에도 자동으로 업데이트됩니다. .