title: Utility of the CKD273 peptide classifier in predicting chronic kidney disease progression.
abstract: BACKGROUND
  Chronic kidney disease (CKD) is a growing public health concern, afflicting approximately one-tenth of adults in developed countries. However, the clinical need for an accurate test, such as a biomarker and/or peptide classifier, for predicting CKD progression and related adverse outcomes remains unaddressed. Recently, a proteomics approach based on capillary electrophoresis-mass spectrometry was employed to develop a urinary peptide-based high-dimensional classifier, namely CKD273, for predicting CKD progression.
  
  
  OBJECTIVE
  The study aims to critically appraise the evidence level of the CKD273 classifier's utility in predicting CKD progression, according to the Oxford Evidence-Based Medicine (EBM) and Strength of Recommendation Taxonomy (SORT) guidelines.
  
  
  METHODS
  Eligible studies were identified by a literature search of MEDLINE and Web of Science Expanded Core Collection databases. Limitations were set to prospective cohort studies evaluating the classifier's accuracy in predicting CKD progression. Data extraction was undertaken according to a predefined protocol by two independent reviewers. The EBM and SORT guidelines were applied to appraise the CKD273 classifier's utility for predicting CKD progression.
  
  
  RESULTS
  The query search results rendered four prospective cohort studies. The classifier performed independently of age, gender and the type of urine storage containers used. The classifier predicted the development of micro- or macroalbuminuria and rapid decline (i.e. >-5% annual decrease) in the estimated glomerular filtration rate. One study assessed the association of the classifier with end-stage renal disease and death but did not take confounding factors into account. The CKD273 classifier attained high evidence levels according to the EBM (score range 1b), supporting its utility for predicting CKD progression. However, lower scores were attained when the studies were scored according the SORT guidelines (score ranges 1-4).
  
  
  CONCLUSIONS
  Initial promising evidence supports the CKD273 classifier's utility in predicting CKD progression. The classifier's applicability should be corroborated with additional evidence arising from inception cohort studies assessing patient-oriented outcomes, which demonstrate its added value beyond currently available clinical risk predictors, as well as its cost-effectiveness in clinical practice.
authors: Center for Basic Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
authors: Elena
authors: E
authors: Critselis
authors: Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
authors: Hiddo
authors: H
authors: Lambers Heerspink
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000652:urine; D016000:Cluster Analysis; D018450:Disease Progression; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D010455:Peptides / Q000652:urine*; D011379:Prognosis; D011446:Prospective Studies; D040901:Proteomics / Q000379:methods*; D051436:Renal Insufficiency, Chronic / Q000175:diagnosis / Q000652:urine*; D015203:Reproducibility of Results
chemical_list: D015415:Biomarkers; D010455:Peptides
keywords: CKD273 peptide classifier; chronic kidney disease; evidence-based medicine; proteomics; urinary biomarker