title: Automatic identification of methotrexate-induced liver toxicity in patients with rheumatoid arthritis from the electronic medical record.
abstract: OBJECTIVE
  To improve the accuracy of mining structured and unstructured components of the electronic medical record (EMR) by adding temporal features to automatically identify patients with rheumatoid arthritis (RA) with methotrexate-induced liver transaminase abnormalities.
  
  
  METHODS
  Codified information and a string-matching algorithm were applied to a RA cohort of 5903 patients from Partners HealthCare to select 1130 patients with potential liver toxicity. Supervised machine learning was applied as our key method. For features, Apache clinical Text Analysis and Knowledge Extraction System (cTAKES) was used to extract standard vocabulary from relevant sections of the unstructured clinical narrative. Temporal features were further extracted to assess the temporal relevance of event mentions with regard to the date of transaminase abnormality. All features were encapsulated in a 3-month-long episode for classification. Results were summarized at patient level in a training set (N=480 patients) and evaluated against a test set (N=120 patients).
  
  
  RESULTS
  The system achieved positive predictive value (PPV) 0.756, sensitivity 0.919, F1 score 0.829 on the test set, which was significantly better than the best baseline system (PPV 0.590, sensitivity 0.703, F1 score 0.642). Our innovations, which included framing the phenotype problem as an episode-level classification task, and adding temporal information, all proved highly effective.
  
  
  CONCLUSIONS
  Automated methotrexate-induced liver toxicity phenotype discovery for patients with RA based on structured and unstructured information in the EMR shows accurate results. Our work demonstrates that adding temporal features significantly improved classification results.
authors.affiliation: Boston Children's Hospital, Informatics Program, Boston, Massachusetts, USA *CL, EWK and DD are co-first authors.
authors.forename: Chen
authors.initials: C
authors.lastname: Lin
authors.affiliation: Division of Rheumatology, Immunology and Allergy, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA Harvard Medical School, Boston, Massachusetts, USA *CL, EWK and DD are co-first authors.
authors.forename: Elizabeth W
authors.initials: EW
authors.lastname: Karlson
authors.affiliation: Boston Children's Hospital, Informatics Program, Boston, Massachusetts, USA Harvard Medical School, Boston, Massachusetts, USA *CL, EWK and DD are co-first authors.
authors.forename: Dmitriy
authors.initials: D
authors.lastname: Dligach
authors.affiliation: Division of Rheumatology, Immunology and Allergy, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA.
authors.forename: Monica P
authors.initials: MP
authors.lastname: Ramirez
authors.affiliation: Boston Children's Hospital, Informatics Program, Boston, Massachusetts, USA Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: Timothy A
authors.initials: TA
authors.lastname: Miller
authors.affiliation: Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA.
authors.forename: Huan
authors.initials: H
authors.lastname: Mo
authors.affiliation: Department of Medicine, Vanderbilt University, Nashville, Tennessee, USA.
authors.forename: Natalie S
authors.initials: NS
authors.lastname: Braggs
authors.affiliation: Research Computing, Partners HealthCare, Boston, Massachusetts, USA.
authors.forename: Andrew
authors.initials: A
authors.lastname: Cagan
authors.affiliation: Research Computing, Partners HealthCare, Boston, Massachusetts, USA.
authors.forename: Vivian
authors.initials: V
authors.lastname: Gainer
authors.affiliation: Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA Department of Medicine, Vanderbilt University, Nashville, Tennessee, USA.
authors.forename: Joshua C
authors.initials: JC
authors.lastname: Denny
authors.affiliation: Boston Children's Hospital, Informatics Program, Boston, Massachusetts, USA Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: Guergana K
authors.initials: GK
authors.lastname: Savova
mesh_terms: D000465:Algorithms; D001172:Arthritis, Rheumatoid / Q000188:drug therapy*; D056486:Chemical and Drug Induced Liver Injury / Q000175:diagnosis*; D057286:Electronic Health Records; D006801:Humans; D007166:Immunosuppressive Agents / Q000009:adverse effects*; D008099:Liver / Q000187:drug effects; D008727:Methotrexate / Q000009:adverse effects*
chemical_list: D007166:Immunosuppressive Agents; D008727:Methotrexate
keywords: electronic medical record; liver toxicity; methotrexate; natural language processing; pharmacogenetic; rheumatoid arthritis