Epidemiologic Questionnaire (EPI-Q) – a scalable, app-based health survey linked to electronic health record and genotype data
0
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
The Epidemiologic Questionnaire (EPI-Q) was established to collect broad, uniform, self-reported health data to supplement electronic health record (EHR) and genotype information from participants in the University of Michigan (UM) Precision Health cohorts. Recruitment of EPI-Q participants, who were already enrolled in 1 of 3 ongoing UM Precision Health cohorts—the Michigan Genomics Initiative, Mental Health Biobank, and Metabolism, Endocrinology, and Diabetes cohorts—began in March 2020. Of 54,043 retrospective invitations, 5,577 individuals enrolled, representing a 10.3% response rate. Of these, 3,502 (63.7%) were female, and the average age was 56.1 years (standard deviation, 15.4). The baseline survey comprises 11 modules on topics including personal and family health history, lifestyle, and cancer screening and history. Additionally, 11 optional modules cover topics including financial toxicity, occupational exposure, and life meaning. The questions are based on standardized and validated instruments used in other cohorts, and we share resources to expedite development of similar surveys. Data are collected via the MyDataHelps platform, which enables current and future participants to share non-Michigan Medicine EHR data. Recruitment is ongoing. Cohort data are available to those with institutional review board approval; for details, contact the Data Office for Clinical and Translational Research (DataOffice@umich.edu).
Abstract
The Epidemiologic Questionnaire (EPI-Q) was established to collect broad, uniform, self-reported health data to supplement electronic health record (EHR) and genotype information from participants in the University of Michigan (UM) Precision Health cohorts. Recruitment of EPI-Q participants, who were already enrolled in 1 of 3 ongoing UM Precision Health cohorts—the Michigan Genomics Initiative, Mental Health Biobank, and Metabolism, Endocrinology, and Diabetes cohorts—began in March 2020. Of 54,043 retrospective invitations, 5,577 individuals enrolled, representing a 10.3% response rate. Of these, 3,502 (63.7%) were female, and the average age was 56.1 years (standard deviation, 15.4). The baseline survey comprises 11 modules on topics including personal and family health history, lifestyle, and cancer screening and history. Additionally, 11 optional modules cover topics including financial toxicity, occupational exposure, and life meaning. The questions are based on standardized and validated instruments used in other cohorts, and we share resources to expedite development of similar surveys. Data are collected via the MyDataHelps platform, which enables current and future participants to share non-Michigan Medicine EHR data. Recruitment is ongoing. Cohort data are available to those with institutional review board approval; for details, contact the Data Office for Clinical and Translational Research (DataOffice@umich.edu).
참고문헌 (26)
- Zawistowski M, "The Michigan Genomics Initiative : a biobank linking genotypes and electronic clinical records in Michigan Medicine patients", Cell Genom, 3, pp.100257~ (2023)
- Beesley LJ, "The emerging landscape of health research based on biobanks linked to electronic health records : existing resources, statistical challenges, and potential opportunities", Stat Med, 39, pp.773~800 (2020)
- Fritsche LG, "Cancer PRSweb : an online repository with polygenic risk scores for major cancer traits and their evaluation in two independent biobanks", Am J Hum Genet, 107, pp.815~836 (2020)
- Singh K, "Predicting persistent opioid use after surgery using electronic health record and patient-reported data", Surgery, 172, pp.241~248 (2022)
- Fritsche LG, "On cross-ancestry cancer polygenic risk scores", PLoS Genet, 17, pp.e1009670~ (2021)
- "UK biobank"[URL]
- Sudlow C, "UK biobank : an open access resource for identifying the causes of a wide range of complex diseases of middle and old age", PLoS Med, 12, pp.e1001779~ (2015)
- "Quickfacts: Grand Rapids city, Michigan; Flint city, Michigan; Detroit city, Michigan; Michigan"[URL]
- "DP02: selected social characteristics in the United Status - 2021: ACS 5-year estimates data profiles, Dearborn city, Michigan"[URL]
- "National Arab American demographics"[URL]
- All of Us Research Program Investigators, "The"All of Us"research program", N Engl J Med, 381, pp.668~676 (2019)
- "Million Veteran Program (MVP)"[URL]
- Brieger K, "Genes for good : engaging the public in genetics research via social media", Am J Hum Genet, 105, pp.65~77 (2019)
- "Cohort profile: epidemiological questionnaire (EPI-Q) - a broad, health-based, scalable survey linked with electronic health record and genotype data" (2022)[URL]
- Alimujiang A, "Association between life purpose and mortality among US adults older than 50 years", JAMA Netw Open, 2, pp.e194270~ (2019)
- Nakamura JS, "Associations between satisfaction with aging and health and well-being outcomes among older US adults", JAMA Netw Open, 5, pp.e2147797~ (2022)
- Røysamb E, "Genetics, personality and wellbeing. A twin study of traits, facets and life satisfaction", Sci Rep, 8, pp.12298~ (2018)
- "A genome-wide association analysis of happiness: consistent genetic effects across the lifespan and across genetic ancestries in multiple cohorts" (2022)[URL]
- Zhou W, "Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies", Nat Genet, 50, pp.1335~1341 (2018)
- Kroenke K, "The PHQ-9 : validity of a brief depression severity measure", J Gen Intern Med, 16, pp.606~613 (2001)
- Awad GH, "Lack of Arab or Middle Eastern and North African health data undermines assessment of health disparities", Am J Public Health, 112, pp.209~212 (2022)
- Fatumo S, "A roadmap to increase diversity in genomic studies", Nat Med, 28, pp.243~250 (2022)
- de Souza JA, "Measuring financial toxicity as a clinically relevant patient-reported outcome : the validation of the COmprehensive Score for financial Toxicity(COST)", Cancer, 123, pp.476~484 (2017)
- Witte J, "Methods for measuring financial toxicity after cancer diagnosis and treatment : a systematic review and its implications", Ann Oncol, 30, pp.1061~1070 (2019)
- Patel MR, "Measurement and validation of the comprehensive score for financial toxicity(COST)in a population with diabetes", Diabetes Care, 45, pp.2535~2543 (2022)
- Pavela G, "Re-validation of the COmprehensive Score for Financial Toxicity(COST) : assessing the scale’s utility in chronic disease populations", Health Serv Insights, 14, pp.11786329211057352~ (2021)
