Validation of a pre-endoscopy risk score for predicting the presence of gastric intestinal metaplasia in a U.S. population
Surveillance of gastric intestinal metaplasia (GIM) may lead to early gastric cancer detection. Our purpose was to externally validate a predictive model for endoscopic GIM previously developed in a veteran population in a second U.S. population. We previously developed a pre-endoscopy risk model fo...
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Published in | Gastrointestinal endoscopy Vol. 98; no. 4; pp. 569 - 576.e1 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
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Elsevier Inc
01.10.2023
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Abstract | Surveillance of gastric intestinal metaplasia (GIM) may lead to early gastric cancer detection. Our purpose was to externally validate a predictive model for endoscopic GIM previously developed in a veteran population in a second U.S. population.
We previously developed a pre-endoscopy risk model for detection of GIM using 423 GIM cases and 1796 control subjects from the Houston Veterans Affairs Hospital. The model included sex, age, race/ethnicity, smoking, and Helicobacter pylori infection with an area under the receiver-operating characteristic curve (AUROC) of .73 for GIM and .82 for extensive GIM. We validated this model in a second cohort of patients from 6 Catholic Health Initiative (CHI)-St Luke’s hospitals (Houston, Tex, USA) from January to December 2017. Cases were defined as having GIM on any gastric biopsy sample and extensive GIM as involving both the antrum and corpus. We further optimized the model by pooling both cohorts and assessing discrimination using AUROC.
The risk model was validated in 215 GIM cases (55 with extensive GIM) and 2469 control subjects. Cases were older than control subjects (59.8 vs 54.7 years) with more nonwhites (59.1% vs 42.0%) and H pylori infections (23.7% vs 10.9%). The model applied to the CHI-St Luke’s cohort had an AUROC of .62 (95% confidence interval [CI], .57-.66) for predicting GIM and of .71 (95% CI, .63-.79) for predicting extensive GIM. When the Veterans Affairs and CHI-St Luke’s cohorts were pooled, discrimination of both models improved (GIM vs extensive GIM AUROC: .74 vs .82).
A pre-endoscopy risk prediction model was validated and updated using a second U.S. cohort with robust discrimination for endoscopic GIM. This model should be evaluated in other U.S. populations to risk-stratify patients for endoscopic GIM screening.
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AbstractList | Surveillance of gastric intestinal metaplasia (GIM) may lead to early gastric cancer detection. Our purpose was to externally validate a predictive model for endoscopic GIM previously developed in a veteran population in a second U.S.
We previously developed a pre-endoscopy risk model for detection of GIM using 423 GIM cases and 1796 control subjects from the Houston Veterans Affairs Hospital. The model included sex, age, race/ethnicity, smoking, and Helicobacter pylori infection with an area under the receiver-operating characteristic curve (AUROC) of .73 for GIM and .82 for extensive GIM. We validated this model in a second cohort of patients from 6 Catholic Health Initiative (CHI)-St Luke's hospitals (Houston, Tex, USA) from January to December 2017. Cases were defined as having GIM on any gastric biopsy sample and extensive GIM as involving both the antrum and corpus. We further optimized the model by pooling both cohorts and assessing discrimination using AUROC.
The risk model was validated in 215 GIM cases (55 with extensive GIM) and 2469 control subjects. Cases were older than control subjects (59.8 vs 54.7 years) with more nonwhites (59.1% vs 42.0%) and H pylori infections (23.7% vs 10.9%). The model applied to the CHI-St Luke's cohort had an AUROC of .62 (95% confidence interval [CI], .57-.66) for predicting GIM and of .71 (95% CI, .63-.79) for predicting extensive GIM. When the Veterans Affairs and CHI-St Luke's cohorts were pooled, discrimination of both models improved (GIM vs extensive GIM AUROC: .74 vs .82).
A pre-endoscopy risk prediction model was validated and updated using a second U.S. cohort with robust discrimination for endoscopic GIM. This model should be evaluated in other U.S. populations to risk-stratify patients for endoscopic GIM screening. Surveillance of gastric intestinal metaplasia (GIM) may lead to early gastric cancer detection. Our purpose was to externally validate a predictive model for endoscopic GIM previously developed in a veteran population in a second U.S. population. We previously developed a pre-endoscopy risk model for detection of GIM using 423 GIM cases and 1796 control subjects from the Houston Veterans Affairs Hospital. The model included sex, age, race/ethnicity, smoking, and Helicobacter pylori infection with an area under the receiver-operating characteristic curve (AUROC) of .73 for GIM and .82 for extensive GIM. We validated this model in a second cohort of patients from 6 Catholic Health Initiative (CHI)-St Luke’s hospitals (Houston, Tex, USA) from January to December 2017. Cases were defined as having GIM on any gastric biopsy sample and extensive GIM as involving both the antrum and corpus. We further optimized the model by pooling both cohorts and assessing discrimination using AUROC. The risk model was validated in 215 GIM cases (55 with extensive GIM) and 2469 control subjects. Cases were older than control subjects (59.8 vs 54.7 years) with more nonwhites (59.1% vs 42.0%) and H pylori infections (23.7% vs 10.9%). The model applied to the CHI-St Luke’s cohort had an AUROC of .62 (95% confidence interval [CI], .57-.66) for predicting GIM and of .71 (95% CI, .63-.79) for predicting extensive GIM. When the Veterans Affairs and CHI-St Luke’s cohorts were pooled, discrimination of both models improved (GIM vs extensive GIM AUROC: .74 vs .82). A pre-endoscopy risk prediction model was validated and updated using a second U.S. cohort with robust discrimination for endoscopic GIM. This model should be evaluated in other U.S. populations to risk-stratify patients for endoscopic GIM screening. [Display omitted] Surveillance of gastric intestinal metaplasia (GIM) may lead to early gastric cancer detection. Our purpose was to externally validate a predictive model for endoscopic GIM previously developed in a veteran population in a second U.S.BACKGROUND AND AIMSSurveillance of gastric intestinal metaplasia (GIM) may lead to early gastric cancer detection. Our purpose was to externally validate a predictive model for endoscopic GIM previously developed in a veteran population in a second U.S.We previously developed a pre-endoscopy risk model for detection of GIM using 423 GIM cases and 1796 control subjects from the Houston Veterans Affairs Hospital. The model included sex, age, race/ethnicity, smoking, and Helicobacter pylori infection with an area under the receiver-operating characteristic curve (AUROC) of .73 for GIM and .82 for extensive GIM. We validated this model in a second cohort of patients from 6 Catholic Health Initiative (CHI)-St Luke's hospitals (Houston, Tex, USA) from January to December 2017. Cases were defined as having GIM on any gastric biopsy sample and extensive GIM as involving both the antrum and corpus. We further optimized the model by pooling both cohorts and assessing discrimination using AUROC.METHODSWe previously developed a pre-endoscopy risk model for detection of GIM using 423 GIM cases and 1796 control subjects from the Houston Veterans Affairs Hospital. The model included sex, age, race/ethnicity, smoking, and Helicobacter pylori infection with an area under the receiver-operating characteristic curve (AUROC) of .73 for GIM and .82 for extensive GIM. We validated this model in a second cohort of patients from 6 Catholic Health Initiative (CHI)-St Luke's hospitals (Houston, Tex, USA) from January to December 2017. Cases were defined as having GIM on any gastric biopsy sample and extensive GIM as involving both the antrum and corpus. We further optimized the model by pooling both cohorts and assessing discrimination using AUROC.The risk model was validated in 215 GIM cases (55 with extensive GIM) and 2469 control subjects. Cases were older than control subjects (59.8 vs 54.7 years) with more nonwhites (59.1% vs 42.0%) and H pylori infections (23.7% vs 10.9%). The model applied to the CHI-St Luke's cohort had an AUROC of .62 (95% confidence interval [CI], .57-.66) for predicting GIM and of .71 (95% CI, .63-.79) for predicting extensive GIM. When the Veterans Affairs and CHI-St Luke's cohorts were pooled, discrimination of both models improved (GIM vs extensive GIM AUROC: .74 vs .82).RESULTSThe risk model was validated in 215 GIM cases (55 with extensive GIM) and 2469 control subjects. Cases were older than control subjects (59.8 vs 54.7 years) with more nonwhites (59.1% vs 42.0%) and H pylori infections (23.7% vs 10.9%). The model applied to the CHI-St Luke's cohort had an AUROC of .62 (95% confidence interval [CI], .57-.66) for predicting GIM and of .71 (95% CI, .63-.79) for predicting extensive GIM. When the Veterans Affairs and CHI-St Luke's cohorts were pooled, discrimination of both models improved (GIM vs extensive GIM AUROC: .74 vs .82).A pre-endoscopy risk prediction model was validated and updated using a second U.S. cohort with robust discrimination for endoscopic GIM. This model should be evaluated in other U.S. populations to risk-stratify patients for endoscopic GIM screening.CONCLUSIONSA pre-endoscopy risk prediction model was validated and updated using a second U.S. cohort with robust discrimination for endoscopic GIM. This model should be evaluated in other U.S. populations to risk-stratify patients for endoscopic GIM screening. |
Author | Liu, Yan Othman, Mohamed O. Kligman, Eugene El-Serag, Hashem B. Tan, Mimi C. Thrift, Aaron P. Sen, Ahana |
AuthorAffiliation | 5 Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA 2 Madison Medical Affiliates, Milwaukee, Wisconsin, USA 3 Houston VA HSR&D Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas, USA 1 Section of Gastroenterology and Hepatology, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA 4 Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA |
AuthorAffiliation_xml | – name: 2 Madison Medical Affiliates, Milwaukee, Wisconsin, USA – name: 3 Houston VA HSR&D Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey Veterans Affairs Medical Center, Houston, Texas, USA – name: 1 Section of Gastroenterology and Hepatology, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA – name: 4 Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas, USA – name: 5 Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA |
Author_xml | – sequence: 1 givenname: Mimi C. orcidid: 0000-0001-6113-4780 surname: Tan fullname: Tan, Mimi C. organization: Section of Gastroenterology and Hepatology, Baylor College of Medicine, Houston, Texas, USA – sequence: 2 givenname: Ahana surname: Sen fullname: Sen, Ahana organization: Section of Gastroenterology and Hepatology, Baylor College of Medicine, Houston, Texas, USA – sequence: 3 givenname: Eugene surname: Kligman fullname: Kligman, Eugene organization: Madison Medical Affiliates, Milwaukee, Wisconsin, USA – sequence: 4 givenname: Mohamed O. surname: Othman fullname: Othman, Mohamed O. organization: Section of Gastroenterology and Hepatology, Baylor College of Medicine, Houston, Texas, USA – sequence: 5 givenname: Yan surname: Liu fullname: Liu, Yan organization: Section of Gastroenterology and Hepatology, Baylor College of Medicine, Houston, Texas, USA – sequence: 6 givenname: Hashem B. surname: El-Serag fullname: El-Serag, Hashem B. organization: Section of Gastroenterology and Hepatology, Baylor College of Medicine, Houston, Texas, USA – sequence: 7 givenname: Aaron P. surname: Thrift fullname: Thrift, Aaron P. organization: Section of Epidemiology and Population Sciences, Baylor College of Medicine, Houston, Texas, USA |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 (iii) All authors have approved the final version of the manuscript. (iv) All work was independent of the funding source. Authorship Statement YL: analyzed the data and contributed to the design of the study MCT, HBE, APT: analysed the data, designed the research study, and wrote the paper MO: designed the research study and contributed to the design of the study EK: collected the data, contributed to the design of the study (ii) Specific author contributions (i) Guarantor of the article: Mimi C. Tan, MD, MPH AS: wrote the paper |
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SubjectTerms | Endoscopy, Gastrointestinal Helicobacter Infections - diagnosis Helicobacter Infections - epidemiology Helicobacter pylori Humans Precancerous Conditions Risk Factors Smoking |
Title | Validation of a pre-endoscopy risk score for predicting the presence of gastric intestinal metaplasia in a U.S. population |
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