Models for the red blood cell lifespan.

Area of Science:

• Hematology
• Biostatistics
• Mathematical Biology

Background:

• Red blood cell (RBC) lifespan is crucial for clinical interpretations, but fundamental survival terms are often confused.
• Existing literature lacks clear definitions and consistent quantification methods for RBC survival parameters.

Purpose of the Study:

• To establish precise definitions for RBC lifespan parameters, including residual lifespan, current age, and excess lifespan.
• To derive and apply statistical models for accurately quantifying these RBC survival parameters.
• To address existing ambiguities in the literature regarding RBC survival.

Main Methods:

• Developed a compartmental model for RBC populations with an arbitrary lifespan distribution.
• Defined and derived distributions for residual lifespan, current age, and excess lifespan.
• Fitted Weibull, gamma, and lognormal distribution models to biotin-labeled RBC residual survival data using nonlinear mixed effects and parametric bootstrapping.

Main Results:

• All three models (Weibull, gamma, lognormal) demonstrated excellent goodness-of-fit and reliable estimation of RBC survival parameters.
• Computed mean full lifespans around 116 days and 95th percentiles (maximum lifespan surrogate) around 154-160 days.
• Estimated mean current ages and residual half-lives, providing physiologically plausible values.

Conclusions:

• The proposed modeling framework and defined parameters offer a robust method for RBC survival analysis.
• The Weibull, gamma, and lognormal models provide consistent and reliable estimates for RBC lifespan and survival metrics.
• This work clarifies fundamental concepts, improving the accuracy and interpretability of RBC survival studies in clinical and research settings.