title: Clinical decision support system for end-stage kidney disease risk estimation in IgA nephropathy patients.
abstract: BACKGROUND
  The progression of IgA nephropathy (IgAN) to end-stage kidney disease (ESKD) depends on several factors that are not quite clear and tangle the risk assessment. We aimed at developing a clinical decision support system (CDSS) for a quantitative risk assessment of ESKD and its timing using available clinical data at the time of renal biopsy.
  
  
  METHODS
  We included a total of 1040 biopsy-proven IgAN patients with long-term follow-up from Italy (N = 546), Norway (N = 441) and Japan (N = 53). Of these, 241 patients reached ESKD: 104 Italian [median time to ESKD = 5 (3-9) years], 134 Norwegian [median time to ESKD = 6 (2-11) years] and 3 Japanese [median time to ESKD = 3 (2-12) years]. We independently trained and validated two cooperating artificial neural networks (ANNs) for predicting first the ESKD status and then the time to ESKD (defined as three categories: ≤ 3 years, between > 3 and 8 years and over 8 years). As inputs we used gender, age, histological grading, serum creatinine, 24-h proteinuria and hypertension at the time of renal biopsy.
  
  
  RESULTS
  The ANNs demonstrated high performance for both the prediction of ESKD (with an AUC of 89.9, 93.3 and 100% in the Italian, Norwegian and Japanese IgAN population, respectively) and its timing (f-measure of 90.7% in the cohort from Italy and 70.8% in the one from Norway). We embedded the two ANNs in a CDSS available online (www.igan.net). Entering the clinical parameters at the time of renal biopsy, the CDSS returns as output the estimated risk and timing of ESKD for the patient.
  
  
  CONCLUSIONS
  This CDSS provides useful additional information for identifying 'high-risk' IgAN patients and may help stratify them in the context of a personalized medicine approach.
authors.affiliation: Cardiovascular Genetics and Genomics, National Heart and Lung Institute, Royal Brompton Hospital, Imperial College London, London, UK Department of Emergency and Organ Transplantation, University of Bari, Bari, Italy.
authors.forename: Francesco
authors.initials: F
authors.lastname: Pesce
authors.affiliation: Department of Electrical and Information Engineering, Politecnico of Bari, Bari, Italy.
authors.forename: Mattea
authors.initials: M
authors.lastname: Diciolla
authors.affiliation: Department of Electrical and Information Engineering, Politecnico of Bari, Bari, Italy.
authors.forename: Giulio
authors.initials: G
authors.lastname: Binetti
authors.affiliation: Department of Electrical and Information Engineering, Politecnico of Bari, Bari, Italy.
authors.forename: David
authors.initials: D
authors.lastname: Naso
authors.affiliation: Department of Electrical and Information Engineering, Politecnico of Bari, Bari, Italy.
authors.forename: Vito Claudio
authors.initials: VC
authors.lastname: Ostuni
authors.affiliation: Department of Electrical and Information Engineering, Politecnico of Bari, Bari, Italy.
authors.forename: Tommaso
authors.initials: T
authors.lastname: Di Noia
authors.affiliation: Department of Clinical Medicine, Renal Research Group, University of Bergen, Bergen, Norway Department of Medicine, Haukeland University Hospital, Bergen, Norway.
authors.forename: Ann Merethe
authors.initials: AM
authors.lastname: Vågane
authors.affiliation: Department of Clinical Medicine, Renal Research Group, University of Bergen, Bergen, Norway Department of Medicine, Haukeland University Hospital, Bergen, Norway.
authors.forename: Rune
authors.initials: R
authors.lastname: Bjørneklett
authors.affiliation: Division of Nephrology, Department of Internal Medicine, Faculty of Medicine, Juntendo University, Tokyo, Japan.
authors.forename: Hitoshi
authors.initials: H
authors.lastname: Suzuki
authors.affiliation: Division of Nephrology, Department of Internal Medicine, Faculty of Medicine, Juntendo University, Tokyo, Japan.
authors.forename: Yasuhiko
authors.initials: Y
authors.lastname: Tomino
authors.affiliation: Department of Electrical and Information Engineering, Politecnico of Bari, Bari, Italy.
authors.forename: Eugenio
authors.initials: E
authors.lastname: Di Sciascio
authors.affiliation: C.A.R.S.O. Consortium, University of Bari, Bari, Italy Schena Foundation, European Research Centre of Kidney Diseases, Bari, Italy.
authors.forename: Francesco Paolo
authors.initials: FP
authors.lastname: Schena
mesh_terms: D000328:Adult; D001706:Biopsy; D020000:Decision Support Systems, Clinical; D018450:Disease Progression; D005260:Female; D005500:Follow-Up Studies; D005922:Glomerulonephritis, IGA / Q000175:diagnosis* / Q000628:therapy; D006801:Humans; D006973:Hypertension; D020407:Internet; D007676:Kidney Failure, Chronic / Q000175:diagnosis* / Q000628:therapy; D007677:Kidney Function Tests; D008297:Male; D008875:Middle Aged; D057285:Precision Medicine; D012372:ROC Curve; D012044:Regression Analysis; D018570:Risk Assessment; D055815:Young Adult
keywords: IgA nephropathy; artificial neural networks; clinical decision support system; end-stage kidney disease; risk stratification