Background: The prognosis of chronic kidney disease (CKD) typically requires longitudinal estimated glomerular filtration rate (eGFR) data, making risk stratification difficult at initial consultation. Furthermore, eGFR-based clinical decisions often overlook the critical factor of patient age. This study aimed to establish a simplified predictive model for progressive CKD and quantify the impact of clinical interventions. Methods: Utilizing a historical dataset (1988–2003) from the pre-renin-angiotensin system inhibitor (RASi) and pre-sodium-glucose cotransporter 2 inhibitor (SGLT2i) era, we developed heatmaps to predict the probability of reaching eGFR < 30 mL/min/1.73 m2 by age 80 years. The model also estimated the risk reduction from smoking cessation and pharmacological therapies. The predictive performance for age + eGFR was assessed using standard calibration and discrimination metrics, and clinical utility was evaluated using decision curve analysis across a range of threshold probabilities. Risk reclassification analyses compared age +eGFR-based categories with conventional eGFR-based stratification. Results: Regarding the risk of eGFR < 30 mL/min/1.73 m2 by age 80 years, simulations confirmed a correlation between age and eGFR. At age 40 years, an eGFR of ~57 mL/min/1.73 m2 indicated a 50% probability of progressing to CKD stage 4 by age 80 years. This threshold decreases to 53 and 48 mL/min/1.73 m2 at 50 and 60 years of age, respectively. Calibration and discrimination analyses demonstrated acceptable agreement between predicted and observed risks. Decision curve analysis showed that an age + eGFR threshold of approximately 115 primarily provided a net benefit at lower threshold probabilities, supporting intensified surveillance strategies, whereas an age +eGFR of 100 showed a positive net benefit across a broader range of thresholds, comparable to the conventional eGFR < 45 mL/min/1.73 m2 criterion. While proteinuria markedly increased risk, smoking cessation provided a 9.4–11.2% risk reduction. Combined RASi and SGLT2i treatment showed the greatest impact, reducing progression probability by 31.2–40.0% (e.g., reducing a 50.0% baseline risk to 32.1% in 40-year-old men). Conclusions: The age + eGFR rule represents a simple, clinically interpretable heuristic for age-adjusted risk stratification based on a single eGFR measurement and may offer potential clinical utility for guiding surveillance intensity and consideration of earlier intervention strategies. However, external validation is required before clinical application.
Enoki et al. (Tue,) studied this question.