title: A pathological scoring system to predict renal outcome in diabetic nephropathy.
abstract: BACKGROUND
  With the association between diabetic nephropathy (DN) and renal outcome being increasingly clear, we aimed at creating a new DN pathological scoring system that could predict the renal outcome.
  
  
  METHODS
  We studied 205 patients with DN confirmed by renal biopsy, sometime between March 1985 and January 2010, who met the inclusion criteria. Renal biopsy included clinical parameters and Tervaert classifications. Hazard ratios (HRs) for death-censored end-stage renal disease (ESRD) were estimated by adjusted Cox proportional-hazards regression. The overall pathological risk score (D-score) was calculated by summing the products of beta coefficient and bootstrap-inclusion fractions, its predictive utility evaluated by Kaplan-Meier methods and c-statistics for a 10-year risk of ESRD.
  
  
  RESULTS
  The D-scores of glomerular classes 1, 2A, 2B, 3, and 4 were, respectively, 0, 3, 4, 6, and 6. Those of interstitial fibrosis and tubular atrophy classes 0, 1, 2, and 3 were 0, 7, 9, and 11, and those of interstitial inflammation classes 0, 1, and 2 were 0, 3, and 4, respectively. The D-score of hyalinosis class 2 was 3 and that of arteriosclerosis class 2 was 1. So, a patient's D-score could be 0-25. HRs for ESRD in patients with D-score ≤14, 15-18, 19-21, and 22-25 were, respectively, 1.00 (reference) 16.21 (95% confidence interval (CI), 1.86-140.90), 19.78 (95% CI, 2.15-182.40), and 45.46 (95% CI, 4.63-446.68) after adjusting for clinical factors. The c-statistics suggested a better predictive ability for a 10-year renal death with models that included the D-score.
  
  
  CONCLUSIONS
  Prediction of DN patients' renal outcome was better with the D-score than without it. Patients with a D-score ≤14 had excellent renal prognosis.
authors.affiliation: Nephrology Center, Toranomon Hospital Kajigaya, Kanagawa, Japan.
authors.forename: Junichi
authors.initials: J
authors.lastname: Hoshino
authors.forename: Koki
authors.initials: K
authors.lastname: Mise
authors.forename: Toshiharu
authors.initials: T
authors.lastname: Ueno
authors.forename: Aya
authors.initials: A
authors.lastname: Imafuku
authors.forename: Masahiro
authors.initials: M
authors.lastname: Kawada
authors.forename: Keiichi
authors.initials: K
authors.lastname: Sumida
authors.forename: Rikako
authors.initials: R
authors.lastname: Hiramatsu
authors.forename: Eiko
authors.initials: E
authors.lastname: Hasegawa
authors.forename: Masayuki
authors.initials: M
authors.lastname: Yamanouchi
authors.forename: Noriko
authors.initials: N
authors.lastname: Hayami
authors.forename: Tatsuya
authors.initials: T
authors.lastname: Suwabe
authors.forename: Naoki
authors.initials: N
authors.lastname: Sawa
authors.forename: Shigeko
authors.initials: S
authors.lastname: Hara
authors.forename: Takeshi
authors.initials: T
authors.lastname: Fujii
authors.forename: Kenichi
authors.initials: K
authors.lastname: Ohashi
authors.forename: Yoshifumi
authors.initials: Y
authors.lastname: Ubara
authors.forename: Kenmei
authors.initials: K
authors.lastname: Takaichi
mesh_terms: D000328:Adult; D000368:Aged; D001161:Arteriosclerosis / Q000473:pathology*; D001284:Atrophy; D001706:Biopsy; D015331:Cohort Studies; D003928:Diabetic Nephropathies / Q000378:metabolism / Q000473:pathology*; D018450:Disease Progression; D005260:Female; D005355:Fibrosis; D005919:Glomerular Filtration Rate; D006801:Humans; D007249:Inflammation; D007668:Kidney / Q000378:metabolism / Q000473:pathology*; D007676:Kidney Failure, Chronic / Q000378:metabolism / Q000473:pathology*; D007684:Kidney Tubules / Q000473:pathology; D008297:Male; D008875:Middle Aged; D016016:Proportional Hazards Models; D011507:Proteinuria / Q000473:pathology*; D051436:Renal Insufficiency, Chronic / Q000378:metabolism / Q000473:pathology; D012189:Retrospective Studies; D018570:Risk Assessment