Personalized screening intervals for kidney function in patients with chronic heart failure: a modeling study.

Area of Science:

• Nephrology
• Cardiology
• Biomarker Research

Background:

• Heart failure (HF) management faces challenges in risk assessment, evidenced by high mortality and rehospitalization rates.
• Individual changes in kidney biomarkers correlate with adverse outcomes in HF patients, suggesting potential for personalized screening.
• Current risk stratification methods for HF patients require improvement for better patient outcomes.

Purpose of the Study:

• To compare personalized versus fixed scheduling for kidney biomarker measurements in chronic heart failure patients.
• To evaluate the impact of personalized scheduling on the number of measurements needed and its ability to enable timely intervention.
• To assess the prognostic performance of personalized biomarker monitoring in heart failure.

Main Methods:

• A simulation study was conducted using data from 263 chronic heart failure patients in the prospective Bio-SHiFT cohort.
• Glomerular and tubular kidney biomarkers were serially measured under a fixed trimonthly scheme.
• A joint model was developed to simulate personalized scheduling, optimizing measurement timing based on individual risk profiles and information gain.

Main Results:

• Personalized scheduling demonstrated comparable prognostication performance to fixed trimonthly scheduling.
• Personalized scheduling required a median of 0.4-2.7 fewer biomarker measurements per year compared to the fixed schedule.
• The simulation assessed the capability of personalized scheduling for timely intervention before primary endpoints.

Conclusions:

• Personalized scheduling of kidney biomarker measurements is effective for monitoring chronic heart failure patients.
• This approach may reduce patient visits and healthcare expenditures.
• Personalized monitoring offers opportunities for timely treatment adaptations in heart failure management.