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Utility of the CKD273 peptide classifier in predicting chronic kidney disease progression
Elena Critselis1, Hiddo Lambers Heerspink2
1Center for Basic Research, Biomedical Research Foundation of the Academy of Athens, Athens, Greece.
Insights
The CKD273 urinary peptide classifier shows promise for predicting chronic kidney disease progression. Further research is needed to confirm its clinical utility and cost-effectiveness.
Area of Science:
- Nephrology
- Proteomics
- Biomarker Discovery
Background:
- Chronic kidney disease (CKD) affects approximately 10% of adults globally.
- Accurate prediction of CKD progression and adverse outcomes remains a clinical challenge.
- A urinary peptide classifier, CKD273, has been developed using proteomics.
Purpose of the Study:
- To critically appraise the evidence level for the CKD273 classifier's utility in predicting CKD progression.
- To evaluate the classifier's predictive accuracy based on Evidence-Based Medicine (EBM) and Strength of Recommendation Taxonomy (SORT) guidelines.
Main Methods:
- Literature search of MEDLINE and Web of Science databases for prospective cohort studies.
- Data extraction by two independent reviewers following a predefined protocol.
- Application of EBM and SORT guidelines to assess the CKD273 classifier's predictive performance.
Main Results:
- Four prospective cohort studies met the inclusion criteria.
- The CKD273 classifier accurately predicted micro/macroalbuminuria and rapid estimated glomerular filtration rate decline.
- High evidence levels (EBM score 1b) support the classifier's utility, though SORT scores were lower.
Conclusions:
- Promising evidence supports the CKD273 classifier for predicting CKD progression.
- Further validation in inception cohort studies is recommended to assess patient-oriented outcomes and added value.
- Cost-effectiveness in clinical practice requires further investigation.
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.
Objectives:
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.
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