PMID- 28097680
OWN - NLM
STAT- MEDLINE
DCOM- 20170801
LR  - 20221207
IS  - 1365-2710 (Electronic)
IS  - 0269-4727 (Linking)
VI  - 42
IP  - 2
DP  - 2017 Apr
TI  - Development of a novel algorithm for detecting glucocorticoid-induced diabetes 
      mellitus using a medical information database.
PG  - 215-220
LID - 10.1111/jcpt.12499 [doi]
AB  - WHAT IS KNOWN AND 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. WHAT IS NEW AND 
      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.
CI  - (c) 2017 John Wiley & Sons Ltd.
FAU - Imatoh, T
AU  - Imatoh T
AUID- ORCID: 0000-0002-8160-7335
AD  - Division of Medicinal Safety Science, National Institute of Health Sciences, 
      Tokyo, Japan.
FAU - Sai, K
AU  - Sai K
AD  - Division of Medicinal Safety Science, National Institute of Health Sciences, 
      Tokyo, Japan.
FAU - Hori, K
AU  - Hori K
AD  - Department of Hospital Pharmacy, Hamamatsu University School of Medicine, 
      Hamamatsu, Japan.
FAU - Segawa, K
AU  - Segawa K
AD  - Division of Medicinal Safety Science, National Institute of Health Sciences, 
      Tokyo, Japan.
FAU - Kawakami, J
AU  - Kawakami J
AD  - Department of Hospital Pharmacy, Hamamatsu University School of Medicine, 
      Hamamatsu, Japan.
FAU - Kimura, M
AU  - Kimura M
AD  - Department of Medical Informatics, Hamamatsu University School of Medicine, 
      Hamamatsu, Japan.
FAU - Saito, Y
AU  - Saito Y
AD  - Division of Medicinal Safety Science, National Institute of Health Sciences, 
      Tokyo, Japan.
LA  - eng
PT  - Journal Article
DEP - 20170118
PL  - England
TA  - J Clin Pharm Ther
JT  - Journal of clinical pharmacy and therapeutics
JID - 8704308
RN  - 0 (Glycated Hemoglobin A)
RN  - 0 (hemoglobin A1c protein, human)
RN  - 9PHQ9Y1OLM (Prednisolone)
SB  - IM
MH  - Adult
MH  - Aged
MH  - Algorithms
MH  - *Databases, Factual
MH  - Diabetes Mellitus/*chemically induced/diagnosis
MH  - Female
MH  - Glycated Hemoglobin/analysis
MH  - Humans
MH  - Male
MH  - Middle Aged
MH  - Pharmacoepidemiology
MH  - Prednisolone/*adverse effects
OTO - NOTNLM
OT  - Japanese patients
OT  - glucocorticoid-induced diabetes mellitus
OT  - medical information database
OT  - pharmacoepidemiology
EDAT- 2017/01/18 06:00
MHDA- 2017/08/02 06:00
CRDT- 2017/01/19 06:00
PHST- 2016/09/15 00:00 [received]
PHST- 2016/12/05 00:00 [accepted]
PHST- 2017/01/18 06:00 [pubmed]
PHST- 2017/08/02 06:00 [medline]
PHST- 2017/01/19 06:00 [entrez]
AID - 10.1111/jcpt.12499 [doi]
PST - ppublish
SO  - J Clin Pharm Ther. 2017 Apr;42(2):215-220. doi: 10.1111/jcpt.12499. Epub 2017 Jan 
      18.