title: Development of a novel algorithm for detecting glucocorticoid-induced diabetes mellitus using a medical information database.
abstract: OBJECTIVE
  Glucocorticoid-induced diabetes mellitus (GIDM) increases the risk of diabetes mellitus (DM)-related complications but is generally difficult to detect in clinical settings. The criteria for diagnosing GIDM have not been established. Recently, medical information databases (MIDs) have been used in post-marketing surveillance (PMS) studies. We conducted a pharmacoepidemiological study to develop an algorithm for detecting GIDM using MID.
  
  
  METHODS
  We selected 1214 inpatients who were newly prescribed with a typical glucocorticoid, prednisolone, during hospitalization from 2008 to 2014 from an MID of Hamamatsu University Hospital in Japan. GIDM was screened based on fasting blood glucose (FBG) and haemoglobin A1c (HbA1c) levels according to the current Japan Diabetes Society (JDS) DM criteria, and its predictability was evaluated by an expert's review of medical records. We investigated further candidate screening factors using receiver operating characteristics analysis.
  
  
  RESULTS
  Sixty-three inpatients were identified by the JDS DM criteria. Of these, 33 patients were definitely diagnosed as having GIDM by expert's review (positive predictive value = 52·4%). To develop a highly predictive algorithm, we compared the characteristics of inpatients diagnosed with definite GIDM and those diagnosed as non-GIDM. The maximum levels of HbA1c in patients with GIDM were significantly higher than those of patients with non-GIDM (66·9 mmol/mol vs. 58·7 mmol/mol, P < 0·001). The patients with GIDM had significantly higher relative increase in maximum level of HbA1c (RIM-HbA1c) than those with non-GIDM (0·3 vs. 0·03, P < 0·001). However, we did not observe a significant difference in those of fasting blood glucose (FBG) levels. We applied the RIM-HbA1c as a second screening factor to improve the detection of GIDM. It showed that a 13% increase in RIM-HbA1c separated patients with from patients without GIDM.
  
  
  CONCLUSIONS
  Patients with GIDM had significantly higher RIM-HbA1c than patients with non-GIDM. There was a 13% increase in RIM-HbA1c in patients with GIDM compared to the others. Our detection algorithm for GIDM using an MID achieved high sensitivity and specificity, and was superior to one based only on the current JDS DM criteria. Our results suggest that monitoring changes in HbA1c levels is important for detecting GIDM and adds to current diagnostic criteria for type 2 DM.
authors.affiliation: Division of Medicinal Safety Science, National Institute of Health Sciences, Tokyo, Japan.
authors.forename: T
authors.identifier: http://orcid.org/0000-0002-8160-7335
authors.initials: T
authors.lastname: Imatoh
authors.affiliation: Division of Medicinal Safety Science, National Institute of Health Sciences, Tokyo, Japan.
authors.forename: K
authors.initials: K
authors.lastname: Sai
authors.affiliation: Department of Hospital Pharmacy, Hamamatsu University School of Medicine, Hamamatsu, Japan.
authors.forename: K
authors.initials: K
authors.lastname: Hori
authors.affiliation: Division of Medicinal Safety Science, National Institute of Health Sciences, Tokyo, Japan.
authors.forename: K
authors.initials: K
authors.lastname: Segawa
authors.affiliation: Department of Hospital Pharmacy, Hamamatsu University School of Medicine, Hamamatsu, Japan.
authors.forename: J
authors.initials: J
authors.lastname: Kawakami
authors.affiliation: Department of Medical Informatics, Hamamatsu University School of Medicine, Hamamatsu, Japan.
authors.forename: M
authors.initials: M
authors.lastname: Kimura
authors.affiliation: Division of Medicinal Safety Science, National Institute of Health Sciences, Tokyo, Japan.
authors.forename: Y
authors.initials: Y
authors.lastname: Saito
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D016208:Databases, Factual; D003920:Diabetes Mellitus / Q000139:chemically induced* / Q000175:diagnosis; D005260:Female; D006442:Glycated Hemoglobin / Q000032:analysis; D006801:Humans; D008297:Male; D008875:Middle Aged; D017891:Pharmacoepidemiology; D011239:Prednisolone / Q000009:adverse effects*
chemical_list: D006442:Glycated Hemoglobin; D011239:Prednisolone; C517652:hemoglobin A1c protein, human
keywords: Japanese patients; glucocorticoid-induced diabetes mellitus; medical information database; pharmacoepidemiology