OpenMed/multicare-articles huggingface dataset:
Enhancing the power of genetic association studies through the use of silver standard cases derived from electronic medical records
Authors: Andrew McDavid, Paul K Crane, Katherine M Newton, David R Crosslin, Wayne McCormick, Noah Weston, Kelly Ehrlich, Eugene Hart, Robert Harrison, Walter A Kukull, Carla Rottscheit, Peggy Peissig, Elisha Stefanski, Catherine A McCarty, Rebecca Lynn Zuvich, Marylyn D Ritchie, Jonathan L Haines, Joshua C Denny, Gerard D Schellenberg, Mariza de Andrade, Iftikhar Kullo, Rongling Li, Daniel Mirel, Andrew Crenshaw, James D Bowen, Ge Li, Debby Tsuang, Susan McCurry, Linda Teri, Eric B Larson, Gail P Jarvik, Chris S Carlson
Journal: PLoS One (2013)
MeSH terms: Biomarkers / metabolism, Dementia / genetics, Electronic Health Records / statistics & numerical data, Genome-Wide Association Study, Genomics, Polymorphism, Single Nucleotide / genetics, Comparative Study, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't, Aged, Case-Control Studies, Chi-Square Distribution, Computer Simulation, Dementia / epidemiology, Humans, Models, Statistical, Phenotype, Risk Factors, Biomarkers

The feasibility of using imperfectly phenotyped "silver standard" samples identified from electronic medical record diagnoses is considered in genetic association studies when these samples might be combined with an existing set of samples phenotyped with a gold standard technique. An analytic expression is derived for the power of a chi-square test of independence using either research-quality case/control samples alone, or augmented with silver standard data. The subset of the parameter space where inclusion of silver standard samples increases statistical power is identified. A case study of dementia subjects identified from electronic medical records from the Electronic Medical Records and Genomics (eMERGE) network, combined with subjects from two studies specifically targeting dementia, verifies these results.