A clinical stratification tool for chronic kidney disease progression rate based on classification tree analysis

Paola Rucci, Marcora Mandreoli, Dino Gibertoni, Alessandro Zuccalà, Maria Pia Fantini, Jacopo Lenzi, Antonio Santoro, Roberto Scarpioni, Sara De Amicis, Carlo Buzio, Salvatore David, Sonia Pasquali, Mattia Corradini, Gianni Cappelli, Fabio Olmeda, Alberto Baraldi, Francesco Caruso, Sergio Stefoni, Claudio Orsi, Cecilia CannarilePierpaolo Di Nicolò, Alda Storari, Giorgia Russo, Andrea Buscaroli, Mattia Monti, Giovanni Mosconi, Stefania Cristino, Carlo Feletti, Leopoldo Baldrati, Angelo Rigotti, Marta Flachi

Research output: Contribution to journalArticle

Abstract

BackgroundRegistry-based studies have identified risk factors for chronic kidney disease (CKD) and for progression to end-stage renal disease. However, usually, these studies do not incorporate sequential measurements of kidney function and provide little information on the prognosis of individual patients. The aim of this study is to identify which combinations of demographic and clinical characteristics are useful to discriminate patients with a differential annual decline in glomerular filtration rate (GFR).MethodsThis observational retrospective study includes patients enlisted in the registry of the Prevention of Progressive Renal Insufficiency Project of Emilia-Romagna region (Italy) from July 2004 to June 2010, with at least four serum creatinine measurements. Classification tree analysis (CTA) was used to identify subgroups of patients with a different annual GFR decline using demographic and laboratory data collected at study entry.ResultsThe CTA procedure generated seven mutually exclusive groups. Among patients with proteinuria, those with a baseline estimated GFR (eGFR) of >33 mL/min/1.73 m2 exhibited the fastest illness progression in the study population (-3.655 mL/min/1.73 m2), followed by patients with a baseline eGFR of 2 and a baseline serum phosphorus of >4.3 mg/dL (-2.833 mL/min/1.73 m 2). Among patients without proteinuria, those aged 67 years, females had on average a stable eGFR over time, with a large variability.ConclusionsIt is possible to rely on a few variables typically accessible in routine clinical practice to stratify patients with a different CKD progression rate. Stratification can be used to guide decisions about the follow-up schedule, treatments to slow progression of kidney disease, prevent its complications and to begin planning for dialysis and transplantation.

Original languageEnglish
Pages (from-to)603-610
Number of pages8
JournalNephrology Dialysis Transplantation
Volume29
Issue number3
DOIs
Publication statusPublished - 2014

Keywords

  • CKD progression
  • Decision tree
  • Prediction models

ASJC Scopus subject areas

  • Nephrology
  • Transplantation
  • Medicine(all)

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    Rucci, P., Mandreoli, M., Gibertoni, D., Zuccalà, A., Fantini, M. P., Lenzi, J., Santoro, A., Scarpioni, R., De Amicis, S., Buzio, C., David, S., Pasquali, S., Corradini, M., Cappelli, G., Olmeda, F., Baraldi, A., Caruso, F., Stefoni, S., Orsi, C., ... Flachi, M. (2014). A clinical stratification tool for chronic kidney disease progression rate based on classification tree analysis. Nephrology Dialysis Transplantation, 29(3), 603-610. https://doi.org/10.1093/ndt/gft444