ArticleJournal of the American Medical Informatics Association : JAMIA2023
Systematic replication of smoking disease associations using survey responses and EHR data in the All of Us Research Program.
Article in Journal of the American Medical Informatics Association : JAMIA, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed.
- A phenome-wide association study of rurality in theJAMIA open · 2026Article
- Assessing the generalizability of prevalence estimates from the All of Us Research Program.American journal of epidemiology · 2026Article
- Exploring beyond diagnoses in electronic health records to improve discovery: a review of the phenome-wide association study.JAMIA open · 2025Review
- Hyponatremia Associated with the Use of Common Antidepressants in the All of Us Research Program.Clinical pharmacology and therapeutics · 2025Observational
- PheWAS analysis on large-scale biobank data with PheTK.Bioinformatics (Oxford, England) · 2024Article
- Characterizing apparent treatment resistant hypertension in the United States: insights from the All of Us Research Program.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Returning value to communities from the All of Us Research Program through innovative approaches for data use, analysis, dissemination, and research capacity building.Journal of the American Medical Informatics Association : JAMIA · 2024Article
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
objectiveThe All of Us Research Program (All of Us) aims to recruit over a million participants to further precision medicine. Essential to the verification of biobanks is a replication of known associations to establish validity. Here, we evaluated how well All of Us data replicated known cigarette smoking associations. MATERIALS AND
methodsWe defined smoking exposure as follows: (1) an EHR Smoking exposure that used International Classification of Disease codes; (2) participant provided information (PPI) Ever Smoking; and, (3) PPI Current Smoking, both from the lifestyle survey. We performed a phenome-wide association study (PheWAS) for each smoking exposure measurement type. For each, we compared the effect sizes derived from the PheWAS to published meta-analyses that studied cigarette smoking from PubMed. We defined two levels of replication of meta-analyses: (1) nominally replicated: which required agreement of direction of effect size, and (2) fully replicated: which required overlap of confidence intervals.
resultsPheWASes with EHR Smoking, PPI Ever Smoking, and PPI Current Smoking revealed 736, 492, and 639 phenome-wide significant associations, respectively. We identified 165 meta-analyses representing 99 distinct phenotypes that could be matched to EHR phenotypes. At P < .05, 74 were nominally replicated and 55 were fully replicated. At P < 2.68 × 10-5 (Bonferroni threshold), 58 were nominally replicated and 40 were fully replicated. DISCUSSION: Most phenotypes found in published meta-analyses associated with smoking were nominally replicated in All of Us. Both survey and EHR definitions for smoking produced similar results.
conclusionThis study demonstrated the feasibility of studying common exposures using All of Us data.
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