Investigating the Relationship Between Age and Kidney Failure in Adults With Category 4 Chronic Kidney Disease

In people with severe chronic kidney disease (CKD), there is an inverse relationship between age and kidney failure. If this relationship is the same at any age (linear), one effect (hazard ratio) will be sufficient for accurate risk prediction; if it is nonlinear, the effect will vary with age.

To investigate the relationship between age and kidney failure in adults with category G4 chronic kidney disease (G4 CKD).

We performed a population-based study using linked administrative databases in Alberta, Canada, to study adults with G4 CKD (estimated glomerular filtration rate [eGFR] = 15-30 mL/min/1.73 m²) and without previously documented eGFR <15 mL/min/1.73 m² or renal replacement. We used cause-specific Cox regression to model the relationship between age and the hazard of kidney failure (the earlier of eGFR <10 mL/min/1.73 m² or receipt of renal replacement) and death, incorporating spline terms to capture any nonlinear effect of age. We included sex, diabetes mellitus, cardiovascular disease, albuminuria, and eGFR in all models.

Of the 27 823 participants (97 731 patient-years at risk; mean age = 76 years, ±13), 19% developed kidney failure and 51% died. The decline in the hazard of kidney failure associated with a given increase in age was not constant but became progressively larger as people aged; that is, the hazard ratio became progressively smaller (closer to 0). Assuming an eGFR of 25 mL/min/1.73 m², for every 10-year increase in age, the hazard ratio declined from 0.76 (95% confidence interval = 0.73-0.79) at age 50 years to 0.43 (95% confidence interval = 34-56) at age 80 years in people without cardiovascular disease, and from 0.75 (95% confidence interval = 0.70-0.79) at age 50 years to 0.36 (95% confidence interval = 0.29-0.45) at age 80 years in people with cardiovascular disease.

The relationship between kidney failure and age varies with age. An age-dependent effect, rather than a constant effect, needs to be specified to accurately predict risk. These findings have implications for risk prediction and advanced care planning.