Diagnostic or prognostic study
Proteomic cardiovascular risk assessment in chronic kidney disease
- Prognostic model development and validation study
- elastic net regression
- internal and external validation
Authors' conclusion
In two sizeable populations with CKD, a proteomic risk model for incident cardiovascular disease surpassed clinical risk models recommended in clinical practice, even after including estimated glomerular filtration rate.
Study context
- Population
- Participants with chronic kidney disease (CKD) and no history of CVD at baseline, Chronic Renal Insufficiency Cohort (derivation) and Atherosclerosis Risk in Communities cohort (validation)2,182 derivation
- Comparison
- Proteomic risk model vs clinical risk models
- Outcome
- Incident CV risk (annualized ROC AUC)
- Follow-up
- 1 to 10 years
Performance
As reported in the abstract
Annualized ROC AUC, CRIC internal validation set
Protein model
0.84 and 0.89
range
Clinical models
0.70 and 0.73
range
Further findings
ARIC validation cohort
- Similar findings observed
Mendelian randomization
- For nearly half of the individual proteins independently associated with CV risk, a causal link to CV events or risk factors suggested
Pathway analyses
- Enrichment of proteins in immunologic function, vascular and neuronal development, and hepatic fibrosis
Original publication
Proteomic cardiovascular risk assessment in chronic kidney disease. Eur Heart J. Published 4 April 2023. doi:10.1093/eurheartj/ehad115
Summarised from the published abstract; every number is checked against it