PMID- 31625766
OWN - NLM
STAT- MEDLINE
DCOM- 20201015
LR  - 20201015
IS  - 1473-4877 (Electronic)
IS  - 0300-7995 (Linking)
VI  - 36
IP  - 2
DP  - 2020 Feb
TI  - Development of risk models for major adverse chronic renal outcomes among 
      patients with type 2 diabetes mellitus using insurance claims: a retrospective 
      observational study.
PG  - 219-227
LID - 10.1080/03007995.2019.1682981 [doi]
AB  - Objective: To develop and validate models allowing the prediction of major 
      adverse chronic renal outcomes (MACRO) in patients with type 2 diabetes mellitus 
      (T2DM) using insurance claims data.Methods: The Optum Integrated Real World 
      Evidence Electronic Health Records and Claims de-identified database 
      (10/01/2006-09/30/2016) was used to identify T2DM patients >/=50 years old. Risk 
      factors were assessed over a 12-month baseline period, and MACRO were 
      subsequently assessed until the end of data availability, continuous enrollment, 
      or death. Separate models were built for moderate-to-severe diabetic kidney 
      disease (DKD), end-stage renal disease (ESRD), and renal death. A random 
      split-sample approach was employed, where 70% of the sample served for model 
      development (training set) and the remaining 30% served for validation (testing 
      set). C-statistics were used to assess model performance.Results: A total of 
      160,031 patients were included. Risk factors associated with MACRO for all models 
      included adapted diabetes complications severity index, heart failure, anemia, 
      diabetic nephropathy, and CKD. C-statistics ranged between 0.70 
      (moderate-to-severe DKD) and 0.84 (renal death) in the testing set. A substantial 
      proportion (e.g. 88.7% for moderate-to-severe DKD) of patients predicted to be at 
      high-risk of MACRO did not have diabetic nephropathy, proteinuria, or CKD at 
      baseline.Conclusions: The models developed using insurance claims data could 
      reliably predict the risk of MACRO in patients with T2DM and enabled patients at 
      higher-risk of DKD to be identified in the absence of baseline diabetic 
      nephropathy, CKD, or proteinuria. These models could help establish strategies to 
      reduce the risk of MACRO in T2DM patients.
FAU - Wysham, Carol H
AU  - Wysham CH
AD  - Rockwood Clinic, Spokane, WA, USA.
FAU - Gauthier-Loiselle, Marjolaine
AU  - Gauthier-Loiselle M
AD  - Analysis Group, Inc., Montreal, Canada.
FAU - Bailey, Robert A
AU  - Bailey RA
AD  - Janssen Scientific Affairs, LLC., Raritan, NJ, USA.
FAU - Manceur, Ameur M
AU  - Manceur AM
AD  - Analysis Group, Inc., Montreal, Canada.
FAU - Lefebvre, Patrick
AU  - Lefebvre P
AD  - Analysis Group, Inc., Montreal, Canada.
FAU - Greenberg, Morris
AU  - Greenberg M
AD  - Analysis Group, Inc., Boston, MA, USA.
FAU - Duh, Mei Sheng
AU  - Duh MS
AD  - Analysis Group, Inc., Boston, MA, USA.
FAU - Young, James B
AU  - Young JB
AD  - Cleveland Clinic Foundation Lerner College of Medicine of Case Western Reserve 
      University, Cleveland, OH, USA.
LA  - eng
PT  - Journal Article
PT  - Observational Study
PT  - Research Support, Non-U.S. Gov't
DEP - 20191106
PL  - England
TA  - Curr Med Res Opin
JT  - Current medical research and opinion
JID - 0351014
SB  - IM
MH  - Aged
MH  - Aged, 80 and over
MH  - Diabetes Mellitus, Type 2/*complications
MH  - Diabetic Nephropathies/*etiology
MH  - Female
MH  - Humans
MH  - Insurance, Health
MH  - Male
MH  - Middle Aged
MH  - Renal Insufficiency, Chronic/*etiology
MH  - Retrospective Studies
MH  - Risk Factors
OTO - NOTNLM
OT  - Insurance claims review
OT  - Renal insufficiency, chronic
OT  - diabetes mellitus, type 2
OT  - risk prediction
EDAT- 2019/10/19 06:00
MHDA- 2020/10/21 06:00
CRDT- 2019/10/19 06:00
PHST- 2019/10/19 06:00 [pubmed]
PHST- 2020/10/21 06:00 [medline]
PHST- 2019/10/19 06:00 [entrez]
AID - 10.1080/03007995.2019.1682981 [doi]
PST - ppublish
SO  - Curr Med Res Opin. 2020 Feb;36(2):219-227. doi: 10.1080/03007995.2019.1682981. 
      Epub 2019 Nov 6.