title: Residual proteinuria and eGFR predict progression of renal impairment within 2 years in type 2 diabetic patients with nephropathy who are receiving optimal treatment with angiotensin receptor blockers.
abstract: OBJECTIVE
  Proteinuria and estimated glomerular filtration rate (eGFR) predict progression of renal impairment in type 2 diabetic nephropathy (DN) but are they still predictive when these patients are treated with angiotensin receptor blockers (ARB)? We investigated whether residual (after ≥3 months of ARB treatment) urinary protein/creatinine ratio (rPCR) or urinary albumin/creatinine ratio (rACR) and residual eGFR (reGFR), predict subsequent progression.
  
  
  METHODS
  One thousand, two hundred and forty-five patients with type 2 DN from two international multi-center studies were analysed. Cross classification of rPCR, rACR with reGFR (rPCR: <1000, 1000-<2000 and ≥2000 mg/g; rACR: <666.7, 666.7-<1333.3 and ≥1333.3 mg/g; reGFR: 15-29, 30-44 and 45-59 mL/min per 1.73 m2). Progression of renal disease exhibited as: end stage renal failure, doubling of serum creatinine, or serum creatinine ≥6 mg/dL.
  
  
  RESULTS
  Increasing rPCR or rACR, and decreasing reGFR were strongly associated with increasing risk of renal disease progression, with no evidence of interaction between rPCR and reGFR, or rACR and reGFR. The estimated 24-month risk was low (<8%) for patients with rPCR <1000 mg/g regardless of reGFR, for patients with reGFR ≥45 mL/min per 1.73 m2 regardless of rPCR, or with rPCR between 1000-<2000 mg/g and reGFR ≥30 mL/min per 1.73 m2 . However, the risk rose steeply (to 39.4%) for reGFR <30 mL/min per 1.73 m2 and rPCR ≥2000 mg/g.
  
  
  CONCLUSIONS
  Despite DN patients being treated with ARB, renal disease progression risk over 2 years increases with increasing proteinuria, albuminuria and decreasing eGFR. Recognition of these risk factors' impact is important in patient management and future clinical trial design.
authors.affiliation: Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia. sara.ivory@monash.edu
authors.forename: Sara E
authors.initials: SE
authors.lastname: Ivory
authors.forename: David K
authors.initials: DK
authors.lastname: Packham
authors.forename: Anne T
authors.initials: AT
authors.lastname: Reutens
authors.forename: Rory
authors.initials: R
authors.lastname: Wolfe
authors.forename: Richard D
authors.initials: RD
authors.lastname: Rohde
authors.forename: Julia
authors.initials: J
authors.lastname: Lewis
authors.forename: Robert C
authors.initials: RC
authors.lastname: Atkins
mesh_terms: D000328:Adult; D000368:Aged; D000419:Albuminuria / Q000175:diagnosis / Q000188:drug therapy* / Q000209:etiology / Q000503:physiopathology; D047228:Angiotensin II Type 1 Receptor Blockers / Q000627:therapeutic use*; D015415:Biomarkers / Q000097:blood / Q000652:urine; D003404:Creatinine / Q000097:blood / Q000652:urine; D003924:Diabetes Mellitus, Type 2 / Q000150:complications*; D003928:Diabetic Nephropathies / Q000175:diagnosis / Q000188:drug therapy* / Q000209:etiology / Q000503:physiopathology; D018450:Disease Progression; D004311:Double-Blind Method; D005260:Female; D005919:Glomerular Filtration Rate / Q000187:drug effects*; D006801:Humans; D053208:Kaplan-Meier Estimate; D007668:Kidney / Q000187:drug effects* / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D016016:Proportional Hazards Models; D018570:Risk Assessment; D012307:Risk Factors; D012709:Serum Albumin / Q000378:metabolism; D000075462:Serum Albumin, Human; D013997:Time Factors; D016896:Treatment Outcome
chemical_list: C422455:ALB protein, human; D047228:Angiotensin II Type 1 Receptor Blockers; D015415:Biomarkers; D012709:Serum Albumin; D003404:Creatinine; D000075462:Serum Albumin, Human