Development and validation of a relatively accurate gastric cancer high-risk group screening scoring system in urban residents.

IF 2.8 3区 医学 Q2 ONCOLOGY Clinical & Translational Oncology Pub Date : 2024-10-08 DOI:10.1007/s12094-024-03748-2
Weipeng Zhao, Tian Li, Ping Wang, Rui Zhang, Fan Gao, Zongfeng Ma, Siqi Zhen, Feng Liu, Yanliu Chu
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Abstract

Purpose: Our study aimed to develop a relatively accurate gastric cancer (GC) screening score system for urban residents and to validate the screening efficacy.

Methods: The present study included a derivation cohort (n = 3406) and a validation cohort (n = 868) of urban residents. Applying the full-stack engineering intelligent system platform of Hualian Health Big Data of Shandong University, the clinical physical examination data of subjects were collected. Univariate and multivariate analyses were used to identify risk factors for GC, and subsequently, an optimal prediction rule was established to create three distinct scoring systems.

Results: In the GC-risk scoring system I, age, plateletocrit (PCT), carcinoembryonic antigen (CEA), glucose, albumin, creatinine were independent risk factors of GC, with scores ranging from 0 to 28 and optimal cut-off was 15.5. The second scoring system consisted of age, PCT, RDW-CV, CEA, glucose, albumin, and creatinine, with scores ranging from 0 to 31. The optimal cut-off point was determined to be 15.5. The scoring system III comprise of age, sex, PCT, RDW CV, CEA, glucose, with scores ranging from 0 to 21 and optimal cut-off was 10.5. All three scoring systems demonstrated excellent discrimination for GC, achieving an AUC of 0.884, 0.89, and 0.876, respectively. In external validation, the AUC values were 0.654, 0.658, and 0.714. Notably, the GC-risk scoring system III exhibited the highest screening efficiency.

Conclusions: Urban residents benefited from the effective and verified GC-risk scoring systems, which demonstrated excellent performance in identifying individuals with an elevated risk of GC.

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在城市居民中开发和验证相对准确的胃癌高危人群筛查评分系统。
目的:我们的研究旨在为城市居民开发一个相对准确的胃癌(GC)筛查评分系统,并验证其筛查效果:方法:本研究包括城市居民衍生队列(3406 人)和验证队列(868 人)。应用山东大学华联健康大数据全栈工程智能系统平台,收集受试者的临床体检数据。采用单变量和多变量分析确定 GC 的风险因素,并建立最佳预测规则,形成三个不同的评分系统:在 GC 风险评分系统 I 中,年龄、血小板比容 (PCT)、癌胚抗原 (CEA)、血糖、白蛋白、肌酐是 GC 的独立风险因素,评分范围为 0 至 28 分,最佳临界值为 15.5。第二个评分系统由年龄、PCT、RDW-CV、CEA、葡萄糖、白蛋白和肌酐组成,评分范围为 0 至 31 分。最佳截断点被确定为 15.5。评分系统 III 包括年龄、性别、PCT、RDW-CV、CEA、葡萄糖,评分范围为 0 至 21 分,最佳临界点为 10.5。这三种评分系统对 GC 都有很好的区分度,AUC 分别为 0.884、0.89 和 0.876。在外部验证中,AUC 值分别为 0.654、0.658 和 0.714。值得注意的是,GC-风险评分系统 III 的筛查效率最高:城市居民受益于有效且经过验证的 GC 风险评分系统,该系统在识别 GC 风险升高的个体方面表现出色。
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来源期刊
CiteScore
6.20
自引率
2.90%
发文量
240
审稿时长
1 months
期刊介绍: Clinical and Translational Oncology is an international journal devoted to fostering interaction between experimental and clinical oncology. It covers all aspects of research on cancer, from the more basic discoveries dealing with both cell and molecular biology of tumour cells, to the most advanced clinical assays of conventional and new drugs. In addition, the journal has a strong commitment to facilitating the transfer of knowledge from the basic laboratory to the clinical practice, with the publication of educational series devoted to closing the gap between molecular and clinical oncologists. Molecular biology of tumours, identification of new targets for cancer therapy, and new technologies for research and treatment of cancer are the major themes covered by the educational series. Full research articles on a broad spectrum of subjects, including the molecular and cellular bases of disease, aetiology, pathophysiology, pathology, epidemiology, clinical features, and the diagnosis, prognosis and treatment of cancer, will be considered for publication.
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