韩国健康成年人 5 年内罹患胃癌的风险预测模型。

IF 6 1区 医学 Q1 GASTROENTEROLOGY & HEPATOLOGY Gastric Cancer Pub Date : 2024-07-01 Epub Date: 2024-04-01 DOI:10.1007/s10120-024-01488-4
Hyungseok Oh, Sunwoo Cho, Jung Ah Lee, Seungho Ryu, Yoosoo Chang
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引用次数: 0

摘要

背景:虽然内镜检查在韩国被普遍用于胃癌筛查,但整合内镜检查结果的预测模型却很少见。我们的目的是利用内镜检查结果作为预测指标,建立一个 5 年胃癌风险预测模型:我们利用 2011 年至 2019 年江北三星健康研究的队列数据开发了一个预测模型。在260 407名年龄≥20岁、既往无癌症病史的参与者中,共观察到435例胃癌病例。该研究采用 Cox 比例危险回归模型来评估胃癌的预测因素,并计算胃癌的 5 年风险。Harrell's C统计量和Nam-D'Agostino χ2检验分别用于测量判别质量和校准能力:我们将年龄、性别、吸烟状况、饮酒量、癌症家族史和既往内镜检查结果纳入风险预测模型。该模型显示出足够的辨别能力[发展队列:C-统计量为 0.800,95% 置信区间为 0.5%]:0.800,95% 置信区间(CI)0.770-0.829;验证队列:C-统计量:0.799,95% 置信区间(CI)0.770-0.829:0.799,95% 置信区间 0.743-0.856]。该模型在进行有效校准时也表现良好(开发队列:χ2 = 13.65,P = 0.135;验证队列:χ2 = 15.57,P = 0.056):我们的预测模型(包括青壮年)显示出良好的区分度和校准性。此外,该模型考虑到内镜检查结果,以 5 年的固定时间间隔来预测罹患胃癌的风险。因此,它在临床上是有用的,尤其是对于有内镜检查结果的成年人。
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Risk prediction model for gastric cancer within 5 years in healthy Korean adults.

Background: Although endoscopy is commonly used for gastric cancer screening in South Korea, predictive models that integrate endoscopy results are scarce. We aimed to develop a 5-year gastric cancer risk prediction model using endoscopy results as a predictor.

Methods: We developed a predictive model using the cohort data of the Kangbuk Samsung Health Study from 2011 to 2019. Among the 260,407 participants aged ≥20 years who did not have any previous history of cancer, 435 cases of gastric cancer were observed. A Cox proportional hazard regression model was used to evaluate the predictors and calculate the 5-year risk of gastric cancer. Harrell's C-statistics and Nam-D'Agostino χ2 test were used to measure the quality of discrimination and calibration ability, respectively.

Results: We included age, sex, smoking status, alcohol consumption, family history of cancer, and previous results for endoscopy in the risk prediction model. This model showed sufficient discrimination ability [development cohort: C-Statistics: 0.800, 95% confidence interval (CI) 0.770-0.829; validation cohort: C-Statistics: 0.799, 95% CI 0.743-0.856]. It also performed well with effective calibration (development cohort: χ2 = 13.65, P = 0.135; validation cohort: χ2 = 15.57, P = 0.056).

Conclusion: Our prediction model, including young adults, showed good discrimination and calibration. Furthermore, this model considered a fixed time interval of 5 years to predict the risk of developing gastric cancer, considering endoscopic results. Thus, it could be clinically useful, especially for adults with endoscopic results.

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来源期刊
Gastric Cancer
Gastric Cancer 医学-胃肠肝病学
CiteScore
14.70
自引率
2.70%
发文量
80
审稿时长
6-12 weeks
期刊介绍: Gastric Cancer is an esteemed global forum that focuses on various aspects of gastric cancer research, treatment, and biology worldwide. The journal promotes a diverse range of content, including original articles, case reports, short communications, and technical notes. It also welcomes Letters to the Editor discussing published articles or sharing viewpoints on gastric cancer topics. Review articles are predominantly sought after by the Editor, ensuring comprehensive coverage of the field. With a dedicated and knowledgeable editorial team, the journal is committed to providing exceptional support and ensuring high levels of author satisfaction. In fact, over 90% of published authors have expressed their intent to publish again in our esteemed journal.
期刊最新文献
Failure of evaluation on ABC classification for gastric cancer screening. Correction: An artificial intelligence system for comprehensive pathologic outcome prediction in early gastric cancer through endoscopic image analysis (with video). Survival among patients cured from gastric adenocarcinoma compared to the background population. SMARCA4-deficient undifferentiated gastric carcinoma: a case series and literature review. A machine learning model for predicting the lymph node metastasis of early gastric cancer not meeting the endoscopic curability criteria.
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