Different roles of protein biomarkers predicting estimated glomerular filtration rate (eGFR) trajectories in people with chronic kidney disease and diabetes mellitus: a nationwide retrospective cohort study
Authors' conclusion
Protein biomarkers only modestly improve predictive accuracy compared to clinical predictors alone. The different protein markers serve different roles for the prediction of longitudinal eGFR trajectories potentially reflecting their role in the disease pathway.
Study context
- Population
- People with DM and moderately advanced chronic kidney disease (CKD), nationwide German Chronic Kidney Disease study
- Participants
- 838 people
- Exposure
- Clinical + protein predictors model vs clinical only model
- Outcome
- Prediction of eGFR trajectories (predictive accuracy)
Methodological detailsnationwide, Bayesian linear mixed models, repeated cross-validation
- Nationwide
- Bayesian linear mixed models
- Repeated cross-validation
Main finding
As reported in the abstract
Predictive performance for eGFR trajectories
Combined model [Formula] before updating by baseline eGFR
0.44
95% CrI 0.37–0.50
Combined model [Formula] after updating by baseline eGFR
0.59
95% CrI 0.51–0.65
Observational data: associations, not effects.
Further findings
Roles of individual predictors
- Few predictors sufficient for performance comparable to main model
- TNF Receptor 1 and Receptor for Advanced Glycation Endproducts associated with baseline eGFR
- Kidney Injury Molecule 1 and urine albumin-creatinine-ratio predictive for future eGFR decline
Original publication
Different roles of protein biomarkers predicting eGFR trajectories in people with chronic kidney disease and diabetes mellitus: a nationwide retrospective cohort study. Cardiovasc Diabetol. Published 29 March 2023. doi:10.
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