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Xu Y, Li GD, Wu CH, Zhong XQ. Nomogram prediction model for gastric cancer risk in chronic atrophic gastritis: Role of blood cell ratios. Shijie Huaren Xiaohua Zazhi 2024; 32:811-820. [DOI: 10.11569/wcjd.v32.i11.811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2024] [Revised: 10/20/2024] [Accepted: 11/21/2024] [Indexed: 11/28/2024] Open
Abstract
BACKGROUND Chronic atrophic gastritis (CAG) is a precancerous condition for gastric cancer. Although endoscopy is the standard method for monitoring CAG, its invasive nature and high cost limit its use.
AIM To identify risk factors for gastric cancer in the CAG population, focusing on blood cell ratios, and develop a personalized prediction model using a nomogram.
METHODS A retrospective analysis was conducted on 314 GAG patients admitted to Hangzhou Normal University Affiliated Hospital from January 2018 to January 2024. Data collected included demographic, serological, and blood cell parameters. Independent risk factors were identified using multivariate logistic regression and a nomogram model was constructed with R. Model performance was assessed using the area under the ROC curve (AUC), the Hosmer-Lemeshow test, and decision curve analysis (DCA).
RESULTS Significant predictive factors for gastric cancer in the CAG population included male gender (odds ratio [OR] = 2.214, P < 0.05), Helicobacter pylori (H. pylori) infection (OR = 2.686, P < 0.05), gastrin 17 (G-17) (OR = 1.037, P < 0.05), hemoglobin-to-red blood cell distribution width ratio (HRR) (OR = 0.648, P < 0.05), and lymphocyte-to-monocyte ratio (LMR) (OR = 0.645, P < 0.05). The prediction model, with an AUC of 0.854, demonstrated good fit (Hosmer-Lemeshow test: χ2 = 6.062, P = 0.640). DCA indicated the potential generalizability of the model.
CONCLUSION The nomogram provides a noninvasive, convenient, and cost-effective tool for screening gastric cancer in CAG patients, showing excellent discrimination and calibration. Further large-scale, multicenter studies are necessary to validate its efficacy across diverse populations.
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Affiliation(s)
- Yang Xu
- Department of Gastroenterology and Hepatology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou 310015, Zhejiang Province, China
- Department of Gastroenterology and Hepatology, Hospital of Zhejiang People's Armed Police, Hangzhou 310051, Zhejiang Province, China
| | - Guo-Dong Li
- Department of Gastroenterology and Hepatology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou 310015, Zhejiang Province, China
| | - Chen-Han Wu
- Department of Gastroenterology and Hepatology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou 310015, Zhejiang Province, China
| | - Xue-Qing Zhong
- Department of Gastroenterology and Hepatology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou 310015, Zhejiang Province, China
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Huang Z, Chen S, Yin S, Shi Z, Gu L, Li L, Yin H, Huang Z, Li B, Chen X, Yang Y, Wang Z, Li H, Zhang C, He Y. Development and validation of a nomogram for predicting the risk of developing gastric cancer based on a questionnaire: a cross-sectional study. Front Oncol 2024; 14:1351967. [PMID: 39588309 PMCID: PMC11586234 DOI: 10.3389/fonc.2024.1351967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 10/21/2024] [Indexed: 11/27/2024] Open
Abstract
Background Detection of gastric cancer (GC) at early stages is an effective strategy for decreasing mortality. This study aimed to construct a prediction nomogram based on a questionnaire to assess the risk of developing GC. Methods Our study comprised a total of 4379 participants (2326 participants from outpatient at Fengqing People's Hospital were considered for model development and internal validation, and 2053 participants from outpatients at the endoscopy center at the Seventh Affiliated Hospital of Sun Yat-Sen University were considered for independent external validation) and gastric mucosa status was determined by endoscopy and biopsies. The eligible participants in development cohort from Fengqing people's Hospital were randomly separated into a training cohort (n=1629, 70.0%) and an internal validation cohort (n=697, 30.0%). The relevant features were selected by a least absolute shrinkage and selection operator (LASSO), and the ensuing features were evaluated through multivariable logistic regression analysis. Subsequently, the variables were selected to construct a prediction nomogram. The discriminative ability and predictive accuracy of the nomogram were evaluated by the C-index and calibration plot, respectively. Decision curve analysis (DCA) curves were used for the assessment of clinical benefit of the model. This model was developed to estimate the risk of developing neoplastic lesions according to the "transparent reporting of a multivariable prediction model for individual prognosis or diagnosis" (TRIPOD) statement. Results Six variables, including age, sex, alcohol consumption, cigarette smoking, education level, and Hp infection status, were independent risk factors for the development of neoplastic lesions. Thus, these variables were incorporated into the final nomogram. The AUC of the nomogram were 0.701, 0.657 and 0.699 in the training, internal validation, and external validation cohorts, respectively. The calibration curve showed that the nomogram was in good agreement with the observed outcomes. Compared to treatment of all patients or none, our nomogram showed a notably higher clinical benefit. Conclusion This nomogram proved to be a convenient, cost-effective tool to effectively predict an individual's risk of developing neoplastic lesions, and it can act as a prescreening tool before gastroscopy.
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Affiliation(s)
- Zhangsen Huang
- Digestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Songyao Chen
- Digestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Songcheng Yin
- Digestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
- Guangdong Provincial Key Laboratory of Digestive Cancer Research, Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong, China
| | - Zhaowen Shi
- General Surgery, Fengqing People’s Hospital, Lincang, China
| | - Liang Gu
- Digestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Liang Li
- Digestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Haofan Yin
- Digestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Zhijian Huang
- Digestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Bo Li
- Digestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
- Guangdong Provincial Key Laboratory of Digestive Cancer Research, Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong, China
| | - Xin Chen
- General Surgery, Fengqing People’s Hospital, Lincang, China
| | - Yilin Yang
- General Surgery, Fengqing People’s Hospital, Lincang, China
| | - Zhengli Wang
- General Surgery, Fengqing People’s Hospital, Lincang, China
| | - Hai Li
- General Surgery, Fengqing People’s Hospital, Lincang, China
| | - Changhua Zhang
- Digestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
- Guangdong Provincial Key Laboratory of Digestive Cancer Research, Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong, China
| | - Yulong He
- Digestive Medicine Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
- Guangdong Provincial Key Laboratory of Digestive Cancer Research, Digestive Diseases Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong, China
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Sun X, Zhang L, Luo Q, Zhou Y, Du J, Fu D, Wang Z, Lei Y, Wang Q, Zhao L. Application of Machine Learning in the Diagnosis of Early Gastric Cancer Using the Kyoto Classification Score and Clinical Features Collected from Medical Consultations. Bioengineering (Basel) 2024; 11:973. [PMID: 39451349 PMCID: PMC11504958 DOI: 10.3390/bioengineering11100973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2024] [Revised: 09/10/2024] [Accepted: 09/23/2024] [Indexed: 10/26/2024] Open
Abstract
The early detection accuracy of early gastric cancer (EGC) determines the choice of the optimal treatment strategy and the related medical expenses. We aimed to develop a simple, affordable, and time-saving diagnostic model using six machine learning (ML) algorithms for the diagnosis of EGC. It is based on the endoscopy-based Kyoto classification score obtained after the completion of endoscopy and other clinical features obtained after medical consultation. We retrospectively evaluated 1999 patients who underwent gastrointestinal endoscopy at the China Beijing Hospital. Of these, 203 subjects were diagnosed with EGC. The data were randomly divided into training and test sets (ratio 4:1). We constructed six ML models, and the developed models were evaluated on the testing set. This procedure was repeated five times. The Kolmogorov-Arnold Networks (KANs) model achieved the best performance (mean AUC value: 0.76; mean balanced accuracy: 70.96%; mean precision: 58.91%; mean recall: 70.96%; mean false positive rate: 26.11%; mean false negative rate: 31.96%; and mean F1 score value: 58.46). The endoscopy-based Kyoto classification score was the most important feature with the highest feature importance score. The results suggest that the KAN model, the optimal ML model in this study, has the potential to identify EGC patients, which may result in a reduction in both the time cost and medical expenses in clinical practice.
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Affiliation(s)
- Xue Sun
- Department of General Practice, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China; (X.S.); (Y.Z.)
| | - Liping Zhang
- Pharmacovigilance Research Center for Information Technology and Data Science, Cross-Strait Tsinghua Research Institute, Xiamen 361015, China;
| | - Qingfeng Luo
- Department of Gastroenterology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China; (Q.L.); (D.F.)
| | - Yan Zhou
- Department of General Practice, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China; (X.S.); (Y.Z.)
| | - Jun Du
- Department of Pathology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China;
| | - Dongmei Fu
- Department of Gastroenterology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China; (Q.L.); (D.F.)
| | - Ziyu Wang
- Digestive Endoscopy Center, Beijing Majiapu Community Health Service Center, Beijing 100068, China;
| | - Yi Lei
- Pharmacovigilance Research Center for Information Technology and Data Science, Cross-Strait Tsinghua Research Institute, Xiamen 361015, China;
| | - Qing Wang
- Pharmacovigilance Research Center for Information Technology and Data Science, Cross-Strait Tsinghua Research Institute, Xiamen 361015, China;
| | - Li Zhao
- Department of Gastroenterology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing 100730, China; (Q.L.); (D.F.)
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Toyoshima O, Nishizawa T, Yoshida S, Matsuno T, Fujisawa G, Toyoshima A, Ebinuma H, Fujishiro M, Saito Y, Suzuki H. Gastric cancer incidence based on endoscopic Kyoto classification of gastritis. World J Gastroenterol 2023; 29:4763-4773. [PMID: 37664152 PMCID: PMC10473921 DOI: 10.3748/wjg.v29.i31.4763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 07/20/2023] [Accepted: 07/28/2023] [Indexed: 08/18/2023] Open
Abstract
BACKGROUND Gastric cancer (GC) incidence based on the endoscopic Kyoto classification of gastritis has not been systematically investigated using time-to-event analysis. AIM To examine GC incidence in an endoscopic surveillance cohort. METHODS This study was retrospectively conducted at the Toyoshima Endoscopy Clinic. Patients who underwent two or more esophagogastroduodenoscopies were enrolled. GC incidence was based on Kyoto classification scores, such as atrophy, intestinal metaplasia (IM), enlarged folds (EFs), nodularity, diffuse redness (DR), and total Kyoto scores. Hazard ratios (HRs) adjusted for age and sex were calculated using a Cox hazard model. RESULTS A total of 6718 patients were enrolled (median age 54.0 years; men 44.2%). During the follow-up period (max 5.02 years; median 2.56 years), GC developed in 34 patients. The average frequency of GCs per year was 0.19%. Kyoto atrophy scores 1 [HR with score 0 as reference: 3.66, 95% confidence interval (CI): 1.06 to 12.61], 2 (11.60, 3.82-35.27), IM score 2 (9.92, 4.37-22.54), EF score 1 (4.03, 1.63-9.96), DR scores 1 (6.22, 2.65-14.56), and 2 (10.01, 3.73-26.86) were associated with GC incidence, whereas nodularity scores were not. The total Kyoto scores of 4 (HR with total Kyoto scores 0-1 as reference: 6.23, 95%CI: 1.93 to 20.13, P = 0.002) and 5-8 (16.45, 6.29-43.03, P < 0.001) were more likely to develop GC, whereas the total Kyoto scores 2-3 were not. The HR of the total Kyoto score for developing GC per 1 rank was 1.75 (95%CI: 1.46 to 2.09, P < 0.001). CONCLUSION A high total Kyoto score (≥ 4) was associated with GC incidence. The endoscopy-based diagnosis of gastritis can stratify GC risk.
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Affiliation(s)
- Osamu Toyoshima
- Department of Gastroenterology, Toyoshima Endoscopy Clinic, Tokyo 157-0066, Japan
| | - Toshihiro Nishizawa
- Department of Gastroenterology and Hepatology, International University of Health and Welfare, Narita Hospital, Narita 286-8520, Japan
| | - Shuntaro Yoshida
- Department of Gastroenterology, Toyoshima Endoscopy Clinic, Tokyo 157-0066, Japan
| | - Tatsuya Matsuno
- Department of Gastroenterology, Toyoshima Endoscopy Clinic, Tokyo 157-0066, Japan
| | - Gota Fujisawa
- Department of Gastroenterology, Toyoshima Endoscopy Clinic, Tokyo 157-0066, Japan
| | - Akira Toyoshima
- Department of Colorectal Surgery, Japanese Red Cross Medical Center, Tokyo 150-8935, Japan
| | - Hirotoshi Ebinuma
- Department of Gastroenterology and Hepatology, International University of Health and Welfare, Narita Hospital, Narita 286-8520, Japan
| | - Mitsuhiro Fujishiro
- Department of Gastroenterology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan
| | - Yutaka Saito
- Division of Endoscopy, National Cancer Center Hospital, Tokyo 104-0045, Japan
| | - Hidekazu Suzuki
- Division of Gastroenterology and Hepatology, Department of Internal Medicine, Tokai University School of Medicine, Isehara 259-1193, Japan
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Toyoshima O, Nishizawa T. Kyoto classification of gastritis: Advances and future perspectives in endoscopic diagnosis of gastritis. World J Gastroenterol 2022; 28:6078-6089. [PMID: 36483157 PMCID: PMC9724483 DOI: 10.3748/wjg.v28.i43.6078] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 10/06/2022] [Accepted: 11/04/2022] [Indexed: 11/16/2022] Open
Abstract
This editorial provides an update of the recent evidence on the endoscopy-based Kyoto classification of gastritis, clarifying the shortcomings of the Kyoto classification, and providing prospects for future research, with particular focus on the histological subtypes of gastric cancer (GC) and Helicobacter pylori (H. pylori) infection status. The total Kyoto score is designed to express GC risk on a score ranging from 0 to 8, based on the following five endoscopic findings: Atrophy, intestinal metaplasia (IM), enlarged folds (EF), nodularity, and diffuse redness (DR). The total Kyoto score reflects H. pylori status as follows: 0, ≥ 2, and ≥ 4 indicate a normal stomach, H. pylori-infected gastritis, and gastritis at risk for GC, respectively. Regular arrangement of collecting venules (RAC) predicts non-infection; EF, nodularity, and DR predict current infection; map-like redness (MLR) predicts past infection; and atrophy and IM predict current or past infection. Atrophy, IM, and EF all increase the incidence of H. pylori-infected GC. MLR is a specific risk factor for H. pylori-eradicated GC, while RAC results in less GC. Diffuse-type GC can be induced by active inflammation, which presents as EF, nodularity, and atrophy on endoscopy, as well as neutrophil and mononuclear cell infiltration on histology. In contrast, intestinal-type GC develops via atrophy and IM, and is consistent between endoscopy and histology. However, this GC risk-scoring design needs to be improved.
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Affiliation(s)
- Osamu Toyoshima
- Department of Gastroenterology, Toyoshima Endoscopy Clinic, Tokyo 157-0066, Japan
| | - Toshihiro Nishizawa
- Department of Gastroenterology, Toyoshima Endoscopy Clinic, Tokyo 157-0066, Japan
- Department of Gastroenterology and Hepatology, International University of Medicine and Welfare, Narita 286-8520, Japan
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Peng C, Zhao G, Pei B, Wang K, Li H, Fei S, Song L, Wang C, Xiong S, Xue Y, He Q, Zheng M. A Novel Plasma-Based Methylation Panel for Upper Gastrointestinal Cancer Early Detection. Cancers (Basel) 2022; 14:5282. [PMID: 36358701 PMCID: PMC9656240 DOI: 10.3390/cancers14215282] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 10/13/2022] [Accepted: 10/25/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Upper gastrointestinal cancer (UGC) is an important cause of cancer death in China, with low five-year survival rates due to the majority of UGC patients being diagnosed at an advanced stage. Therefore, there is an urgent need to develop cost-effective, reliable and non-invasive methods for the early detection of UGC. METHODS A novel plasma-based methylation panel combining simultaneous detection of three methylated biomarkers (ELMO1, ZNF582 and TFPI2) and an internal control gene were developed and used to examine plasma samples from 186 UGC patients and 190 control subjects. RESULTS The results indicated excellent PCR amplification efficiency and reproducibility of ELMO1, ZNF582 and TFPI2 in the range of 10-100,000 copies per PCR reaction of fully methylated genomic DNA. The methylation levels of ELMO1, ZNF582 and TFPI2 were significantly higher in UGC samples than those in control subjects. The sensitivities of ELMO1, ZNF582 and TFPI2 alone for UGC detection were 32.3%, 61.3% and 30.6%, respectively; when three markers were combined, the sensitivity was improved to 71.0%, with a specificity of 90.0%, and the area under the curve (AUC) was 0.870 (95% CI: 0.832-0.902). CONCLUSION Methylated ELMO1, ZNF582 and TFPI2 were specific for UGC and the three-methylated gene panel provided an alternative non-invasive choice for UGC early detection.
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Affiliation(s)
- Cheng Peng
- Department of Gastroenterology, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing 211100, China
| | - Guodong Zhao
- Zhejiang University Kunshan Biotechnology Laboratory, Zhejiang University Kunshan Innovation Institute, Kunshan 215300, China
- Department of R&D, Suzhou VersaBio Technologies Co. Ltd., Kunshan 215300, China
| | - Bing Pei
- Department of Clinical Laboratory, The Affiliated Suqian First People’s Hospital of Nanjing Medical University, Suqian 223800, China
| | - Kai Wang
- Department of R&D, Suzhou VersaBio Technologies Co. Ltd., Kunshan 215300, China
| | - Hui Li
- Department of Gastroenterology, Affiliated Hospital of Xuzhou Medical University, Xuzhou 221002, China
- Department of Gastroenterology, First People’s Hospital of Xuzhou, Xuzhou 221002, China
| | - Sujuan Fei
- Department of Gastroenterology, Affiliated Hospital of Xuzhou Medical University, Xuzhou 221002, China
| | - Lishuang Song
- Department of R&D, Suzhou VersaBio Technologies Co. Ltd., Kunshan 215300, China
| | - Chunkai Wang
- Department of R&D, Suzhou VersaBio Technologies Co. Ltd., Kunshan 215300, China
| | - Shangmin Xiong
- Zhejiang University Kunshan Biotechnology Laboratory, Zhejiang University Kunshan Innovation Institute, Kunshan 215300, China
- Department of R&D, Suzhou VersaBio Technologies Co. Ltd., Kunshan 215300, China
| | - Ying Xue
- Center for Reproduction and Genetics, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou 215000, China
| | - Qibin He
- Department of Gastroenterology, The Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing 211100, China
| | - Minxue Zheng
- Zhejiang University Kunshan Biotechnology Laboratory, Zhejiang University Kunshan Innovation Institute, Kunshan 215300, China
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
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