Suppr超能文献

基于索赔数据开发并验证一种算法,用于识别日本胃癌病例的发病情况并确定其进展阶段。

Development and validation of a claims-based algorithm to identify incidents and determine the progression phases of gastric cancer cases in Japan.

作者信息

Inoue Takahiro, Agatsuma Nobukazu, Utsumi Takahiro, Tanaka Yukari, Nishikawa Yoshitaka, Horimatsu Takahiro, Shimizu Takahiro, Nikaido Mitsuhiro, Nakanishi Yuki, Hoshino Nobuaki, Takahashi Yoshimitsu, Nakayama Takeo, Seno Hiroshi

机构信息

Department of Gastroenterology and Hepatology, Kyoto University Graduate School of Medicine, 54 Kawaharacho, Shogoin, Sakyo-Ku, Kyoto, 606-8507, Japan.

Department of Gastroenterology and Hepatology, Japanese Red Cross Wakayama Medical Center, Wakayama, Japan.

出版信息

J Gastroenterol. 2025 Feb;60(2):141-151. doi: 10.1007/s00535-024-02167-y. Epub 2024 Nov 26.

Abstract

BACKGROUND

Although health insurance claims data can address questions that clinical trials cannot answer, the uncertainty of disease names and the absence of stage information hinder their use in gastric cancer (GC) research. This study aimed to develop and validate a claims-based algorithm to identify and determine the progression phases of incident GC cases in Japan.

METHODS

The gold standard for validation in this retrospective observational study was medical records of patients with incident GC who underwent specific treatments, defined by the claim codes associated with GC treatment. The algorithm was developed and refined using a cohort from two large tertiary care medical centers (April-September 2017 and April-September 2019) and subsequently validated using two independent cohorts: one from different periods (October 2017-March 2019 and October 2019-March 2021) and the other from a different institution (a community hospital). The algorithm identified incident cases based on a combination of the International Classification of Diseases, 10th Revision diagnosis codes for GC (C160-169), and claim codes for specific treatments, classifying them into endoscopic, surgical, and palliative groups. Positive predictive value (PPV), sensitivity of incident case identification, and diagnostic accuracy of progression phase determination were evaluated.

RESULTS

The developed algorithm achieved PPVs of 90.0% (1119/1244) and 95.9% (94/98), sensitivities of 98.0% (1119/1142) and 98.9% (94/95) for incident case identification, with diagnostic accuracies of 94.1% (1053/1119) and 93.6% (88/94) for progression phase determination in the two validation cohorts, respectively.

CONCLUSIONS

This validated claims-based algorithm could advance real-world GC research and assist in decision-making regarding GC treatment.

摘要

背景

尽管医疗保险理赔数据能够解决一些临床试验无法回答的问题,但疾病名称的不确定性以及分期信息的缺失阻碍了其在胃癌(GC)研究中的应用。本研究旨在开发并验证一种基于理赔数据的算法,以识别并确定日本新发病例的胃癌进展阶段。

方法

在这项回顾性观察研究中,验证的金标准是接受特定治疗的新发病例的病历记录,这些治疗由与胃癌治疗相关的理赔编码定义。该算法使用来自两个大型三级医疗中心的队列(2017年4月至9月和2019年4月至9月)进行开发和完善,随后使用两个独立队列进行验证:一个来自不同时期(2017年10月至2019年3月和2019年10月至2021年3月),另一个来自不同机构(一家社区医院)。该算法基于国际疾病分类第10版胃癌诊断编码(C160-169)和特定治疗的理赔编码组合来识别新发病例,并将其分为内镜组、手术组和姑息治疗组。评估了阳性预测值(PPV)、新发病例识别的敏感性以及进展阶段确定的诊断准确性。

结果

在两个验证队列中,所开发的算法在新发病例识别方面的PPV分别为90.0%(1119/1244)和95.9%(94/98),敏感性分别为98.0%(1119/1142)和98.9%(94/95),在进展阶段确定方面的诊断准确性分别为94.1%(1053/1119)和93.6%(88/94)。

结论

这种经过验证的基于理赔数据的算法可以推动胃癌的真实世界研究,并有助于胃癌治疗的决策制定。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44b2/11794417/01d1c0e6ef94/535_2024_2167_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验