Dynamic prediction based on variability of a longitudinal biomarker.

ABSTRACT:

Background

Tacrolimus is given post-kidney transplant to suppress the immune system, and the amount of drug in the body is measured frequently. Higher variability over time may be indicative of poor drug adherence, leading to more adverse events. It is important to account for the variation in Tacrolimus, not just the average change over time.

Methods

Using data from the University of Colorado, we compare methods of assessing how the variability in Tacrolimus influences the hazard of de novo Donor Specific Antibodies (dnDSA), an early warning sign of graft failure. We compare multiple joint models in terms of fit and predictive ability. We explain that the models that account for the individual-specific variability over time have the best predictive performance. These models

SUBMITTER: Campbell KR 

PROVIDER: S-EPMC8122571 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature