دورية أكاديمية

Establishment and Validation of a Pathologic Upgrade Prediction Nomogram Model for Gastric Low-Grade Intraepithelial Neoplasia Patients After the Eradication of

التفاصيل البيبلوغرافية
العنوان: Establishment and Validation of a Pathologic Upgrade Prediction Nomogram Model for Gastric Low-Grade Intraepithelial Neoplasia Patients After the Eradication of
المؤلفون: Yejiao Ruan MD, Guangrong Lu MD, Yuesheng Zhu MD, Xianhui Ma BSc, Yuning Shi BSc, Xuchao Zhang BSc, Zheng Zhu BSc, Zhenzhai Cai MD, Xuanping Xia MD
المصدر: Cancer Control, Vol 29 (2022)
بيانات النشر: SAGE Publishing, 2022.
سنة النشر: 2022
المجموعة: LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
مصطلحات موضوعية: Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
الوصف: Background As yet, there is no unified method of treatment for the evaluation and management of gastric low-grade intraepithelial neoplasia (LGIN) worldwide. Methods Patients with gastric LGIN who had been treated with Helicobacter pylori eradication were gathered retrospectively. Based on several relevant characteristics described and analyzed by LASSO regression analysis and multivariable logistic regression, a prediction nomogram model was established. C-index, the area under the receiver operating characteristic curve (AUC), calibration plot, and decision curve analysis (DCA) were adopted to evaluate the accuracy and reliability of the model. Results A total of 309 patients with LGIN were randomly divided into the training groups and the validation groups. LASSO regression analysis and multivariable logistic regression identified that 6 variables including gender, size, location, borderline, number, and erosion were independent risk factors. The nomogram model displayed good discrimination with a C-index of .765 (95% confidence interval: .702-.828). The accuracy and reliability of the model were also verified by an AUC of .764 in the training group and .757 in the validation group. Meanwhile, the calibration curve and the DCA suggested that the predictive nomogram had promising accuracy and clinical utility. Conclusions A predictive nomogram model was constructed and proved to be clinically applicable to identify high-risk groups with possible pathologic upgrade in patients with gastric LGIN. Since it is regarded that strengthening follow-up or endoscopic treatment of high-risk patients may contribute to improving the detection rate or reducing the incidence of gastric cancer, the predictive nomogram model provides a reliable basis for the treatment of LGIN.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1526-2359
10732748
Relation: https://doaj.org/toc/1526-2359
DOI: 10.1177/10732748221143390
URL الوصول: https://doaj.org/article/84a17e0b5f6a4602adf477dc1c5d0509
رقم الأكسشن: edsdoj.84a17e0b5f6a4602adf477dc1c5d0509
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:15262359
10732748
DOI:10.1177/10732748221143390