title: Identifying subgroups of renal function trajectories.
abstract: Renal function in patients with chronic kidney disease (CKD) may follow different trajectory profiles. The aim of this study was to evaluate and illustrate the ability of the latent class linear mixed model (LCMM) to identify clinically relevant subgroups of renal function trajectories within a multicenter hospital-based cohort of CKD patients.
  
  
  
  We analysed data from the NephroTest cohort including 1967 patients with all-stage CKD at baseline who had glomerular filtration rate (GFR) both measured by 51 Cr-EDTA renal clearance (mGFR) and estimated by the CKD-EPI equation (eGFR); 1103 patients had at least two measurements. The LCMM was used to identify subgroups of GFR trajectories, and patients' characteristics at baseline were compared between the subgroups identified.
  
  
  
  Five classes of mGFR trajectories were identified. Three had a slow linear decline of mGFR over time at different levels. In the two others, patients had a high level of mGFR at baseline with either a strong nonlinear decline over time ( n  = 11) or a nonlinear improvement ( n  = 94) of mGFR. Higher levels of proteinuria and blood pressure at baseline were observed in classes with either severely decreased mGFR or strong mGFR decline over time. Using eGFR provided similar findings.
  
  
  
  The LCMM allowed us to identify in our cohort five clinically relevant subgroups of renal function trajectories. It could be used in other CKD cohorts to better characterize their different profiles of disease progression, as well as to investigate specific risk factors associated with each profile.
authors.affiliation: Univ. Bordeaux, ISPED, Centre INSERM U1219-Bordeaux Population Health Research, Bordeaux, France.
authors.forename: Julie
authors.initials: J
authors.lastname: Boucquemont
authors.affiliation: Univ. Bordeaux, ISPED, Centre INSERM U1219-Bordeaux Population Health Research, Bordeaux, France.
authors.forename: Lucie
authors.initials: L
authors.lastname: Loubère
authors.affiliation: CESP, Inserm, Univ Paris-Sud, UVSQ, Univ Paris-Saclay, Villejuif, France.
authors.forename: Marie
authors.initials: M
authors.lastname: Metzger
authors.affiliation: Centre Hospitalier Universitaire de Bordeaux, Service de Néphrologie Transplantation Dialyse, Bordeaux, France.|Unité INSERM 1026, University of Bordeaux, Bordeaux, France.
authors.forename: Christian
authors.initials: C
authors.lastname: Combe
authors.affiliation: CESP, Inserm, Univ Paris-Sud, UVSQ, Univ Paris-Saclay, Villejuif, France.
authors.forename: Bénédicte
authors.initials: B
authors.lastname: Stengel
authors.affiliation: Univ. Bordeaux, ISPED, Centre INSERM U1219-Bordeaux Population Health Research, Bordeaux, France.
authors.forename: Karen
authors.initials: K
authors.lastname: Leffondre
mesh_terms: D015331:Cohort Studies; D003404:Creatinine; D005919:Glomerular Filtration Rate; D006801:Humans; D007472:Iohexol; D012042:Registries; D051436:Renal Insufficiency, Chronic; D013548:Sweden
chemical_list: D007472:Iohexol; D003404:Creatinine
keywords: chronic kidney disease progression; growth mixture modelling; latent class linear mixed model; measured glomerular filtration rate; trajectories