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Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the
Wei-Qi Wei1, Lisa A Bastarache1, Robert J Carroll1
1Departments of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, United States of America.
Insights
Phecodes, a novel EHR coding system, better represent clinical phenotypes and replicate genetic associations compared to ICD-9-CM and CCS. This approach enhances phenome-wide association studies (PheWAS) for genomic research.
Area of Science:
- Genomic Medicine
- Biomedical Informatics
- Computational Biology
Background:
- Electronic Health Records (EHRs) contain valuable clinical data for genetic research.
- Accurate representation of clinical phenotypes from EHR billing codes is crucial for genetic association studies.
- Existing coding systems like ICD-9-CM and CCS have limitations in capturing clinically meaningful phenotypes.
Purpose of the Study:
- To compare the efficacy of three EHR coding systems: ICD-9-CM, CCS, and phecodes.
- To evaluate their ability to represent clinically meaningful phenotypes and replicate known genetic associations.
- To assess their utility in phenome-wide association studies (PheWAS).
Main Methods:
- Selected 100 disease phenotypes, including 25 from prior genome-wide association studies (GWAS) and 75 common diseases from problem lists.
- Compared the exact match rates of ICD-9-CM, CCS, and phecodes for these phenotypes.
- Evaluated the replication of 440 known single nucleotide polymorphism (SNP)-phenotype associations using each coding system.
Main Results:
- Phecodes demonstrated superior performance, exactly matching 83% of phenotypes compared to 53% for ICD-9-CM and 32% for CCS.
- Phecodes successfully replicated more SNP-phenotype associations (153 pairs) than ICD-9-CM (143) and CCS (139).
- Phecodes generally yielded stronger odds ratios and lower p-values, and identified novel genetic signals in PheWAS.
Conclusions:
- Phecode groupings provide a more accurate and clinically relevant representation of diseases in EHRs for genomic studies.
- While all tested systems can be used for PheWAS, phecodes offer superior performance and discovery potential.
- The phecode approach enhances the utility of EHR data for large-scale genetic association research.
Objective:
To compare three groupings of Electronic Health Record (EHR) billing codes for their ability to represent clinically meaningful phenotypes and to replicate known genetic associations. The three tested coding systems were the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes, the Agency for Healthcare Research and Quality Clinical Classification Software for ICD-9-CM (CCS), and manually curated "phecodes" designed to facilitate phenome-wide association studies (PheWAS) in EHRs.
Methods And Materials:
We selected 100 disease phenotypes and compared the ability of each coding system to accurately represent them without performing additional groupings. The 100 phenotypes included 25 randomly-chosen clinical phenotypes pursued in prior genome-wide association studies (GWAS) and another 75 common disease phenotypes mentioned across free-text problem lists from 189,289 individuals. We then evaluated the performance of each coding system to replicate known associations for 440 SNP-phenotype pairs.
Results:
Out of the 100 tested clinical phenotypes, phecodes exactly matched 83, compared to 53 for ICD-9-CM and 32 for CCS. ICD-9-CM codes were typically too detailed (requiring custom groupings) while CCS codes were often not granular enough. Among 440 tested known SNP-phenotype associations, use of phecodes replicated 153 SNP-phenotype pairs compared to 143 for ICD-9-CM and 139 for CCS. Phecodes also generally produced stronger odds ratios and lower p-values for known associations than ICD-9-CM and CCS. Finally, evaluation of several SNPs via PheWAS identified novel potential signals, some seen in only using the phecode approach. Among them, rs7318369 in PEPD was associated with gastrointestinal hemorrhage.
Conclusion:
Our results suggest that the phecode groupings better align with clinical diseases mentioned in clinical practice or for genomic studies. ICD-9-CM, CCS, and phecode groupings all worked for PheWAS-type studies, though the phecode groupings produced superior results.
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