Temporal validation of the CT-PIRP prognostic model for mortality and renal replacement therapy initiation in chronic kidney disease patients

BMC Nephrology

Giorgia Russo¹  Mattia Corradini²  Dino Gibertoni³  Paola Rucci³  Davide Martelli⁴  Marcora Mandreoli⁵  Elena Mancini⁶  Antonio Santoro⁶ 

[1] 0000 0000 8897 2840, grid.416317.6, Nephrology and Dialysis Unit, Ospedale S.Anna, Ferrara, Italy;0000 0004 1756 8364, grid.415217.4, Nephrology and Dialysis Unit, Ospedale S.Maria Nuova, Reggio Emilia, Italy;0000 0004 1757 1758, grid.6292.f, Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy;0000 0004 1760 3756, grid.415207.5, Nephrology and Dialysis Unit, Ospedale S.Maria delle Croci, Ravenna, Italy;Nephrology and Dialysis Unit, Ospedale S. Maria della Scaletta, Via Montericco, 4, 40026, Imola, Italy;grid.412311.4, Nephrology, Dialysis and Hypertension Unit, Policlinico S.Orsola-Malpighi, Bologna, Italy;

关键词: Chronic kidney disease;    CKD;    Prognostic models;    Classification trees;    Renal outcomes;    Renal disease;    RRT inception;    Temporal validation;   

DOI  :  10.1186/s12882-019-1345-7

来源: publisher

【 摘 要 】

BackgroundA classification tree model (CT-PIRP) was developed in 2013 to predict the annual renal function decline of patients with chronic kidney disease (CKD) participating in the PIRP (Progetto Insufficienza Renale Progressiva) project, which involves thirteen Nephrology Hospital Units in Emilia-Romagna (Italy). This model identified seven subgroups with specific combinations of baseline characteristics that were associated with a differential estimated glomerular filtration rate (eGFR) annual decline, but the model’s ability to predict mortality and renal replacement therapy (RRT) has not been established yet.MethodsSurvival analysis was used to determine whether CT-PIRP subgroups identified in the derivation cohort (n = 2265) had different mortality and RRT risks. Temporal validation was performed in a matched cohort (n = 2051) of subsequently enrolled PIRP patients, in which discrimination and calibration were assessed using Kaplan-Meier survival curves, Cox regression and Fine & Gray competing risk modeling.ResultsIn both cohorts mortality risk was higher for subgroups 3 (proteinuric, low eGFR, high serum phosphate) and lower for subgroups 1 (proteinuric, high eGFR), 4 (non-proteinuric, younger, non-diabetic) and 5 (non-proteinuric, younger, diabetic). Risk of RRT was higher for subgroups 3 and 2 (proteinuric, low eGFR, low serum phosphate), while subgroups 1, 6 (non-proteinuric, old females) and 7 (non-proteinuric, old males) showed lower risk. Calibration was excellent for mortality in all subgroups while for RRT it was overall good except in subgroups 4 and 5.ConclusionsThe CT-PIRP model is a temporally validated prediction tool for mortality and RRT, based on variables routinely collected, that could assist decision-making regarding the treatment of incident CKD patients. External validation in other CKD populations is needed to determine its generalizability.

【 授权许可】

CC BY