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本文引用的文献

1
The Research Program: Data quality, utility, and diversity.研究计划:数据质量、效用和多样性。
Patterns (N Y). 2022 Aug 12;3(8):100570. doi: 10.1016/j.patter.2022.100570.
2
The American Cancer Society's Facts & Figures: 2020 Edition.美国癌症协会《2020年事实与数据》版
J Adv Pract Oncol. 2020 Mar;11(2):135-136. doi: 10.6004/jadpro.2020.11.2.1. Epub 2020 Mar 1.
3
Diversity and inclusion for the All of Us research program: A scoping review.《全民研究计划的多样性和包容性:范围综述》。
PLoS One. 2020 Jul 1;15(7):e0234962. doi: 10.1371/journal.pone.0234962. eCollection 2020.
4
The "All of Us" Research Program. Reply.“我们所有人”研究项目。回复。
N Engl J Med. 2019 Nov 7;381(19):1884-1885. doi: 10.1056/NEJMc1912496.
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The "All of Us" Research Program.“All of Us”研究计划。
N Engl J Med. 2019 Aug 15;381(7):668-676. doi: 10.1056/NEJMsr1809937.
6
Annual Report to the Nation on the Status of Cancer, Featuring Cancer in Men and Women Age 20-49 Years.《国家癌症报告:20-49 岁男性和女性癌症现状》
J Natl Cancer Inst. 2019 Dec 1;111(12):1279-1297. doi: 10.1093/jnci/djz106.
7
Surveillance for Certain Health Behaviors and Conditions Among States and Selected Local Areas - Behavioral Risk Factor Surveillance System, United States, 2015.国家和部分选定地区特定健康行为和状况监测 - 美国 2015 年行为危险因素监测系统。
MMWR Surveill Summ. 2018 Jun 29;67(9):1-90. doi: 10.15585/mmwr.ss6709a1.
8
Epigenetics and Precision Oncology.表观遗传学与精准肿瘤学
Cancer J. 2017 Sep/Oct;23(5):262-269. doi: 10.1097/PPO.0000000000000281.
9
Personalized and Cancer Models to Guide Precision Medicine.用于指导精准医学的个性化癌症模型。
Cancer Discov. 2017 May;7(5):462-477. doi: 10.1158/2159-8290.CD-16-1154. Epub 2017 Mar 22.
10
The Eighth Edition AJCC Cancer Staging Manual: Continuing to build a bridge from a population-based to a more "personalized" approach to cancer staging.第八版 AJCC 癌症分期手册:继续从基于人群的方法向更“个体化”的癌症分期方法构建桥梁。
CA Cancer J Clin. 2017 Mar;67(2):93-99. doi: 10.3322/caac.21388. Epub 2017 Jan 17.

《在所有 31.5 万名“我们所有人”参与者中癌症概述》。

An Overview of Cancer in the First 315,000 All of Us Participants.

机构信息

Department of Public Health Sciences, University of Chicago, Chicago, Illinois, United States of America.

Institute for Population and Precision Health, University of Chicago, Chicago, Illinois, United States of America.

出版信息

PLoS One. 2022 Sep 1;17(9):e0272522. doi: 10.1371/journal.pone.0272522. eCollection 2022.

DOI:10.1371/journal.pone.0272522
PMID:36048778
原文链接:
https://pmc.ncbi.nlm.nih.gov/articles/PMC9436122/
Abstract

INTRODUCTION

The NIH All of Us Research Program will have the scale and scope to enable research for a wide range of diseases, including cancer. The program's focus on diversity and inclusion promises a better understanding of the unequal burden of cancer. Preliminary cancer ascertainment in the All of Us cohort from two data sources (self-reported versus electronic health records (EHR)) is considered.

MATERIALS AND METHODS

This work was performed on data collected from the All of Us Research Program's 315,297 enrolled participants to date using the Researcher Workbench, where approved researchers can access and analyze All of Us data on cancer and other diseases. Cancer case ascertainment was performed using data from EHR and self-reported surveys across key factors. Distribution of cancer types and concordance of data sources by cancer site and demographics is analyzed.

RESULTS AND DISCUSSION

Data collected from 315,297 participants resulted in 13,298 cancer cases detected in the survey (in 89,261 participants), 23,520 cancer cases detected in the EHR (in 203,813 participants), and 7,123 cancer cases detected across both sources (in 62,497 participants). Key differences in survey completion by race/ethnicity impacted the makeup of cohorts when compared to cancer in the EHR and national NCI SEER data.

CONCLUSIONS

This study provides key insight into cancer detection in the All of Us Research Program and points to the existing strengths and limitations of All of Us as a platform for cancer research now and in the future.

摘要

简介

NIH 所有美国人研究计划将具有规模和范围,能够针对包括癌症在内的各种疾病进行研究。该计划专注于多样性和包容性,有望更好地了解癌症负担的不平等。本研究考虑了从两个数据源(自我报告与电子健康记录(EHR))对所有美国人队列中的初步癌症确定。

材料和方法

这项工作是使用 Researcher Workbench 对迄今为止从所有美国人研究计划的 315297 名已注册参与者中收集的数据进行的,经过批准的研究人员可以在该工作台上访问和分析所有与癌症和其他疾病相关的美国人数据。通过 EHR 和自我报告的调查,针对关键因素确定癌症病例。分析了癌症类型的分布和按癌症部位和人口统计学数据来源的一致性。

结果与讨论

从 315297 名参与者中收集的数据导致在调查中检测到 13298 例癌症病例(在 89261 名参与者中),在 EHR 中检测到 23520 例癌症病例(在 203813 名参与者中),以及在两个来源中检测到 7123 例癌症病例(在 62497 名参与者中)。与 EHR 和全国 NCI SEER 数据中的癌症相比,种族/族裔的调查完成情况的关键差异影响了队列的构成。

结论

本研究提供了在所有美国人研究计划中进行癌症检测的关键见解,并指出了作为癌症研究平台的所有美国人现有的优势和局限性,无论是现在还是未来。