目的：本研究旨在回顧2018年1月1日至2024年9月30日期間，收錄於PubMed上的、使用TriNetX數據庫進行次級數據分析的文章。通過分析這些文章的標題和摘要，本研究希望識別常見的研究主題，包括常研究的疾病、高引用的文章，以及受到研究學者高度關注的研究。<p>方法：在本研究中，數據取自PubMed資料庫平台，該平台提供免費檢索生物醫學期刊的文獻與摘要，其文章主要由Medline資料庫所收錄。研究中使用了TriNetX平台的數據庫，並利用R軟件4.2.3版本進行文本探勘。<p>結果：研究共從PubMed平台檢索到1,005篇文章。在這些文章中，最常報告的診斷為COVID-19感染（234篇），其次是糖尿病（156篇）和癌症（138篇）。文章發表趨勢分析顯示，自2020年起，利用TriNetX數據庫的研究顯著增加，同時美國在發表量上處於領先地位。發表量最高的期刊為Cureus，其次是International Journal of Impotence Research和Journal of Medical Virology。這些期刊的平均影響因子為5.2±6.4（範圍：0-96.2），每篇文章的平均被引用次數為15.5±100.2（範圍：0-2,189）。共有24篇文章的被引用次數超過100次，其中21篇與COVID-19相關。被引用次數最多的一篇文章（2,189次）同樣與COVID-19相關。在138篇癌症相關文章中，研究最常見的癌症類別是前列腺癌（16篇，11.6%）和乳腺癌（16篇，11.6%），其次是肺癌（14篇，10.1%）。<p>結論：利用TriNetX數據庫發表的文章數量顯著增長，自2020年以來呈現出顯著激增之趨勢。TriNetX建立了一個臨床研究協作平台，促進了真實世界證據的生成。該平台通過提供全面且可靠的數據，支持高品質、數據驅動的研究。

Background/Purpose: TriNetX collaborates with leading contract research organizations, including Syneos and ICON, and partners with 220 healthcare organizations across 30 countries. Since 2018, an increasing number of articles using TriNetX data have been published in various journals. This study aims to review PubMed articles published between 2018 and September 30, 2024, that utilize secondary data from the TriNetX database, identifying prevalent research topics, including common diseases, highly cited articles, and areas of significant interest.

Methods: Data were retrieved from PubMed, a platform that provides access to biomedical citations and abstracts. The research used the TriNetX database, and text mining was performed using R software version 4.2.3. The citation count of the retrieved articles was based on the Journal Citation Reports 2023 and publication dates up to September 30, 2024.

Results: A total of 1,005 articles were identified. The most common research topics were COVID-19 (n=234), diabetes (n=156), and cancer (n=138). Publications surged after 2020, with the U.S. leading in volume. Cureus published the most articles, followed by the International Journal of Impotence Research and the Journal of Medical Virology. The average journal impact factor was 5.2±6.4 (range: 0-96.2), and the average citation count was 15.5±100.2 (range: 0-2,189). Of the 1,005 articles, 24 had over 100 citations, 21 of which focused on COVID-19. The most-cited article (2,189 citations) was COVID-19-related. Among cancer studies, prostate and breast cancer were the most frequent (n=16 each, 11.6%), followed by lung cancer (n=14, 10.1%).

Conclusion: The number of articles using the TriNetX database has increased since 2020. The platform has become a key resource for generating real-world evidence, supporting high-quality, data-driven or hypothesis-driven research across various clinical areas.