ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2015
Contrasting Association Results between Existing PheWAS Phenotype Definition Methods and Five Validated Electronic Phenotypes.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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.
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Who cites it
12 citing papers in PubMed, 14 citations in OpenAlex.
- A deep learning model to dynamically predict cancer-associated thromboembolism in large-scale healthcare systems.NPJ digital medicine · 2026Article
- A probabilistic approach for building disease phenotypes across electronic health records.BioData mining · 2025Article
- SepsisJournal of medical microbiology · 2025Review
- Using Phecodes for Research with the Electronic Health Record: From PheWAS to PheRS.Annual review of biomedical data science · 2021Review
- Using Electronic Health Records To Generate Phenotypes For Research.Current protocols in human genetics · 2019Article
- AUDIT-C and ICD codes as phenotypes for harmful alcohol use: association with ADH1B polymorphisms in two US populations.Addiction (Abingdon, England) · 2018Article
- PheProb: probabilistic phenotyping using diagnosis codes to improve power for genetic association studies.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- SUSTain: Scalable Unsupervised Scoring for Tensors and its Application to Phenotyping.KDD : proceedings. International Conference on Knowledge Discovery & Data Mining · 2018Article
- Defining Phenotypes from Clinical Data to Drive Genomic Research.Annual review of biomedical data science · 2018Article
- Genome-wide and Phenome-wide Approaches to Understand Variable Drug Actions in Electronic Health Records.Clinical and translational science · 2018Review
- Article
- The Impact of Diagnostic Code Misclassification on Optimizing the Experimental Design of Genetic Association Studies.Journal of healthcare engineering · 2017Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Phenome-Wide Association Studies (PheWAS) comprehensively investigate the association between genetic variation and a wide array of outcome traits. Electronic health record (EHR) based PheWAS uses various abstractions of International Classification of Diseases, Ninth Revision (ICD-9) codes to identify case/control status for diagnoses that are used as the phenotypic variables. However, there have not been comparisons within a PheWAS between results from high quality derived phenotypes and high-throughput but potentially inaccurate use of ICD-9 codes for case/control definition. For this study we first developed a group of high quality algorithms for five phenotypes. Next we evaluated the association of these "gold standard" phenotypes and 4,636,178 genetic variants with minor allele frequency > 0.01 and compared the results from high-throughput associations at the 3 digit, 5 digit, and PheWAS codes for defining case/control status. We found that certain diseases contained similar patient populations across phenotyping methods but had differences in PheWAS.
Indexed as
Identifiers
26958218PMC4765620W2432355112What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.