Prognostic models for chronic kidney disease: a systematic review and external validation

Abstract

Background Accurate risk prediction is needed in order to provide personalized healthcare for chronic kidney disease (CKD) patients. An overload of prognosis studies is being published, ranging from individual biomarker studies to full prediction studies. We aim to systematically appraise published prognosis studies investigating multiple biomarkers and their role in risk predictions. Our primary objective was to investigate if the prognostic models that are reported in the literature were of sufficient quality and to externally validate them. Methods We undertook a systematic review and appraised the quality of studies reporting multivariable prognosis models for end-stage renal disease (ESRD), cardiovascular (CV) events and mortality in CKD patients. We subsequently externally validated these models in a randomized trial that included patients from a broad CKD population. Results We identified 91 papers describing 36 multivariable models for prognosis of ESRD, 50 for CV events, 46 for mortality and 17 for a composite outcome. Most studies were deemed of moderate quality. Moreover, they often adopted different definitions for the primary outcome and rarely reported full model equations (21% of the included studies). External validation was performed in the Multifactorial Approach and Superior Treatment Efficacy in Renal Patients with the Aid of Nurse Practitioners trial (n = 788, with 160 events for ESRD, 79 for CV and 102 for mortality). The 24 models that reported full model equations showed a great variability in their performance, although calibration remained fairly adequate for most models, except when predicting mortality (calibration slope >1.5). Conclusions This review shows that there is an abundance of multivariable prognosis models for the CKD population. Most studies were considered of moderate quality, and they were reported and analysed in such a manner that their results cannot directly be used in follow-up research or in clinical practice.

Performance of prediction models for nephropathy in people with type 2 diabetes: systematic review and external validation study

“…Several systematic reviews on prognostic models for nephropathy have been performed,232425 although several years ago232526 or focusing only on the general population 24. Also, although some external validation of the models has been done, it was either limited to the general population242627 or only included a small number of (other) models as part of a model development paper 28. Given that people with type 2 diabetes have an increased risk of developing nephropathy, it is important to assess the performance of prognostic models in a head-to-head comparison in a large scale population of those with type 2 diabetes.…”

“…22 More recently, identified risk factors include oxidative stress, inflammation, genetic background, ethnicity, and glomerular hyperfiltration. 22 Several systematic reviews on prognostic models for nephropathy have been performed, [23][24][25] although several years ago 23 25 26 or focusing only on the general population. 24 Also, although some external validation of the models has been done, it was either limited to the general population 24 26 27 or only included a small number of (other) models as part of a model development paper.…”

Impacts of Interaction of Mental Condition and Quality of Life between Donors and Recipients at Decision-Making of Preemptive and Post-Dialysis Living-Donor Kidney Transplantation

“…However, the majority of patients with chronic kidney disease remain at risk of progressing to kidney failure (previously end-stage renal disease: ESRD). Indeed, the prevalence of ESRD has increased in recent years [ 4 , 5 ]. There are two types of major therapeutic modalities for ESRD: Dialyses (haemodialysis and peritoneal dialysis) and kidney transplantation [ 5 ].…”

Validation of a Novel Predictive Algorithm for Kidney Failure in Patients Suffering from Chronic Kidney Disease: The Prognostic Reasoning System for Chronic Kidney Disease (PROGRES-CKD)

“…To further characterize PROGRES-CKD accuracy, we compared its discrimination performance against KFREs which were extensively validated in different CKD patient populations [ 11 , 17 , 18 ] and are routinely used in clinical practice. PROGRES-CKD was as accurate as KFREs for 24-month prediction in both validation cohorts and more accurate for 6-month forecasting in the GCKD study.…”

“…Indeed, the majority of published risk scores lack external validation [ 11 , 13 , 14 ], leading to suboptimal discrimination in external populations [ 12 ] and limited generalizability to clinical settings [ 11 ]. One prominent exception is represented by the Kidney Failure Risk Equations (KFREs) developed by Tangri and colleagues [ 15 ], which showed stable discrimination in different validation studies [ 16 , 17 , 18 ]. However, KFREs do not provide short-term forecasts, are not calculable for patients with incomplete data, and need re-calibration when applied to CKD populations with risk factor distributions departing from those of the original derivation dataset.…”