Comparing Whole-Blood and Plasma Tacrolimus Intra-Patient Variability for Predicting Allograft Rejection in Kidney...

Tacrolimus is a key immunosuppressant used to prevent allograft rejection in kidney transplant recipients. Intra-patient variability (IPV) in tacrolimus trough concentrations has been recognized as a useful biomarker for predicting clinical outcomes in kidney transplantation. Tacrolimus therapeutic drug monitoring traditionally relies on whole-blood concentration measurements. However, the pharmacological effect of tacrolimus is likely directly influenced by the unbound fraction in plasma, suggesting that IPV derived from plasma concentrations might be a more accurate predictor of clinical outcomes. This study aimed to compare the predictive performance of tacrolimus IPV calculated from whole-blood versus imputed plasma concentrations for biopsy-proven kidney allograft rejection. Plasma tacrolimus concentrations were imputed from measured whole-blood levels in 1302 adult recipients using an established saturable hematocrit-binding model. Tacrolimus whole-blood and plasma IPV were calculated as time-weighted coefficients of variation. The association between IPV and biopsy-proven rejection occurring 60-730 days posttransplant was assessed using Kaplan-Meier analysis and Cox proportional hazards models. We found that higher tacrolimus IPV was significantly associated with increased rejection risk, irrespective of the matrix used. Model performance analysis using the concordance index (C-index) and bootstrap revealed that the plasma-derived IPV model did not outperform the whole-blood IPV model, indicating that calculating IPV from hematocrit-imputed plasma concentrations offers no significant predictive advantage over the standard whole-blood method. While our results indicate no predictive advantage of hematocrit-imputed plasma IPV over whole-blood IPV, it remains unknown whether IPV obtained from direct plasma tacrolimus measurement or more advanced plasma prediction models will outperform blood tacrolimus IPV in predicting rejection risk.