PDF(Pubmed)
Abstract：
This technical report serves as a comprehensive guide for conducting a phenome-wide association study (PheWAS) utilizing data extracted from the Nationwide Inpatient Sample 2020. Specifically tailored to individuals diagnosed with pancreatic cysts and lung cancer, the report establishes a step-by-step workflow designed to assist researchers in uncovering potential associations within this specific cohort. The methodology outlined in the report ensures clarity and reproducibility by employing a curated cohort sourced from the GitHub repository and executed using R for robust data analysis. The code encompasses pivotal steps, including the utilization of a QQ plot as a crucial diagnostic tool aimed at identifying systematic biases or associations. Additionally, the report incorporates the creation of a Manhattan plot, delving into essential mathematical considerations to enhance the interpretability of the results. Notably, the report elucidates the handling of the International Classification of Disease version 10 (ICD-10) codes, providing a sample approach for their segmentation to analyze associations by diagnostic categories. The segmentation aligns with the guidelines outlined in the American Medical Association\'s ICD-10-CM 2022, the Complete Official Codebook with Guidelines (American Medical Association Press, 2021), ensuring a standardized and rigorous analytical process. This comprehensive guide equips researchers with the tools and insights needed to navigate the complexities of PheWAS within the context of pancreatic cysts and lung cancer, fostering transparency, reproducibility, and meaningful scientific exploration.
摘要：
本技术报告是利用从2020年全国住院患者样本中提取的数据进行表型全关联研究（PheWAS）的综合指南。专门针对诊断为胰腺囊肿和肺癌的个体，该报告建立了一个循序渐进的工作流程,旨在帮助研究人员发现这一特定队列中的潜在关联.报告中概述的方法通过采用源自GitHub存储库并使用R执行的精选队列来进行可靠的数据分析，从而确保了清晰度和可重复性。代码包含关键步骤，包括利用QQ图作为旨在识别系统偏见或关联的关键诊断工具。此外,该报告包含了曼哈顿地块的创建，深入研究基本的数学考虑因素，以增强结果的可解释性。值得注意的是,该报告阐明了国际疾病分类第10版（ICD-10）代码的处理，为他们的细分提供了一个样本方法，以按诊断类别分析关联。分割与美国医学协会的ICD-10-CM2022中概述的指南一致，该指南是带有指南的完整官方代码手册（美国医学协会出版社，2021),确保标准化和严格的分析过程。这份全面的指南为研究人员提供了在胰腺囊肿和肺癌背景下导航PheWAS复杂性所需的工具和见解。促进透明度，再现性，有意义的科学探索。
