PMID- 32233158
OWN - NLM
STAT- MEDLINE
DCOM- 20200402
LR  - 20200407
IS  - 1598-6357 (Electronic)
IS  - 1011-8934 (Print)
IS  - 1011-8934 (Linking)
VI  - 35
IP  - 12
DP  - 2020 Mar 30
TI  - Extracting Structured Genotype Information from Free-Text HLA Reports Using a 
      Rule-Based Approach.
PG  - e78
LID - 10.3346/jkms.2020.35.e78 [doi]
LID - e78
AB  - BACKGROUND: Human leukocyte antigen (HLA) typing is important for transplant 
      patients to prevent a severe mismatch reaction, and the result can also support 
      the diagnosis of various disease or prediction of drug side effects. However, 
      such secondary applications of HLA typing results are limited because they are 
      typically provided in free-text format or PDFs on electronic medical records. We 
      here propose a method to convert HLA genotype information stored in an 
      unstructured format into a reusable structured format by extracting 
      serotype/allele information. METHODS: We queried HLA typing reports from the 
      clinical data warehouse of Seoul National University Hospital (SUPPREME) from 
      2000 to 2018 as a rule-development data set (64,024 reports) and from the most 
      recent year (6,181 reports) as a test set. We used a rule-based natural language 
      approach using a Python regex function to extract the 1) number of patients in 
      the report, 2) clinical characteristics such as indication of the HLA testing, 
      and 3) precise HLA genotypes. The performance of the rules and codes was 
      evaluated by comparison between the extracted results from the test set and a 
      validation set generated by manual curation. RESULTS: Among 11,287 reports for 
      development set and 1,107 for the test set describing HLA typing for a single 
      patient, iterative rule generation developed 124 extracting rules and 8 cleaning 
      rules for HLA genotypes. Application of these rules extracted HLA genotypes with 
      0.892-0.999 precision and 0.795-0.998 recall for the five HLA genes. The 
      precision and recall of the extracting rules for the number of patients in a 
      report were 0.997 and 0.994 and those for the clinical variable extraction were 
      0.997 and 0.992, respectively. All extracted HLA alleles and serotypes were 
      transformed according to formal HLA nomenclature by the cleaning rules. 
      CONCLUSION: The rule-based HLA genotype extraction method shows reliable 
      accuracy. We believe that there are significant number of patients who takes 
      profit when this under-used genetic information will be return to them.
CI  - (c) 2020 The Korean Academy of Medical Sciences.
FAU - Lee, Kye Hwa
AU  - Lee KH
AUID- ORCID: 0000-0002-7593-7020
AD  - Center for Precision Medicine, Seoul National University Hospital, Seoul, Korea. 
      geffa@snu.as.kr.
FAU - Kim, Hyo Jung
AU  - Kim HJ
AUID- ORCID: 0000-0001-9555-0926
AD  - Division of Biomedical Informatics, Seoul National University Biomedical 
      Informatics and Systems Biomedical Informatics Research Center, Seoul National 
      University College of Medicine, Seoul, Korea.
FAU - Kim, Yi Jun
AU  - Kim YJ
AUID- ORCID: 0000-0002-1763-4267
AD  - Center for Precision Medicine, Seoul National University Hospital, Seoul, Korea.
FAU - Kim, Ju Han
AU  - Kim JH
AUID- ORCID: 0000-0003-1522-9038
AD  - Division of Biomedical Informatics, Seoul National University Biomedical 
      Informatics and Systems Biomedical Informatics Research Center, Seoul National 
      University College of Medicine, Seoul, Korea.
FAU - Song, Eun Young
AU  - Song EY
AUID- ORCID: 0000-0003-1286-9611
AD  - Department of Laboratory Medicine, Seoul National University College of Medicine, 
      Seoul, Korea. eysong1@snu.ac.kr.
LA  - eng
GR  - NRF-2018R1D1A1A02086109/NRF/National Research Foundation of Korea/Korea
PT  - Journal Article
DEP - 20200330
PL  - Korea (South)
TA  - J Korean Med Sci
JT  - Journal of Korean medical science
JID - 8703518
RN  - 0 (HLA Antigens)
SB  - IM
MH  - Algorithms
MH  - Data Warehousing
MH  - Electronic Health Records
MH  - Genotype
MH  - HLA Antigens/*genetics
MH  - *Histocompatibility Testing
MH  - Humans
MH  - *Information Storage and Retrieval
MH  - *Natural Language Processing
MH  - Seoul
PMC - PMC7105511
OTO - NOTNLM
OT  - Data Sets as Topic
OT  - Electronic Medical Record
OT  - Genetic Testing
OT  - HLA Test
OT  - Major Histocompatibility Complex
COIS- The authors have no potential conflicts of interest to disclose.
EDAT- 2020/04/02 06:00
MHDA- 2020/04/03 06:00
PMCR- 2020/03/30
CRDT- 2020/04/02 06:00
PHST- 2019/05/16 00:00 [received]
PHST- 2020/01/29 00:00 [accepted]
PHST- 2020/04/02 06:00 [entrez]
PHST- 2020/04/02 06:00 [pubmed]
PHST- 2020/04/03 06:00 [medline]
PHST- 2020/03/30 00:00 [pmc-release]
AID - 35.e78 [pii]
AID - 10.3346/jkms.2020.35.e78 [doi]
PST - epublish
SO  - J Korean Med Sci. 2020 Mar 30;35(12):e78. doi: 10.3346/jkms.2020.35.e78.