Background: – Reports regarding the relationship between tacrolimus exposure and the risk of acute kidney allograft rejection are conflicting. This may be explained by the previous use of methodological approaches that disregarded important factors in the analysis of longitudinal measurements and time-to-event data. Therefore, in this study, joint models were used to investigate the relationship between repeated measurements of tacrolimus predose concentrations (C ₀) and time to acute biopsy-proven acute rejection (BPAR).Methods: – This was a post hoc analysis of a randomized controlled trial in which living-donor kidney transplant recipients (KTR) received either a standard, bodyweight-based or CYP3A5 genotype-based tacrolimus starting dose. Joint modeling was performed by coupling a mixed-effects model for tacrolimus C ₀ with a Cox proportional hazards model for the risk of rejection. Only the first episode of rejection was considered.Results: – A total of 229 KTRs were included, of whom the incidence of BPAR was 10.5% (n = 24 KTRs) in the first 3 months posttransplant. A total of 3069 tacrolimus measurements were available for the analysis. A joint model adjusted for recipient age and peak panel reactive antibodies demonstrated that tacrolimus C ₀ was associated with risk of rejection. A 1-unit increase in the time-normalized area under the curve for logarithmically (log)-transformed C ₀ represented a change of −2.65 in the log of the relative hazard (95% credible interval: −5.05 to −0.36, P = 0.022).Conclusions: – A negative association between the cumulative effect of tacrolimus C ₀ and BPAR was observed using joint modeling. This demonstrated that KTRs with lower tacrolimus exposure were at a higher risk of rejection.

In order to prevent long-term immunity-related complications after lung transplantation, close monitoring of immunosuppressant levels using therapeutic drug monitoring (TDM) is paramount. Novel electronic nose (eNose) technology may be a non-invasive alternative to the current invasive procedures for TDM. We investigated the diagnostic and categorization capacity of eNose breathprints for Tacrolimus trough blood plasma levels (TAC _trough) in lung transplant recipients (LTRs). We performed eNose measurements in stable LTR attending the outpatient clinic. We evaluated (1) the correlation between eNose measurements and TAC _trough, (2) the diagnostic capacity of eNose technology for TAC _trough, and (3) the accuracy of eNose technology for categorization of TAC _trough into three clinically relevant categories (low: <7 µg ml ⁻¹, medium: 7-10 µg ml ⁻¹, and high: >10 µg ml ⁻¹ ). A total of 186 measurements from 86 LTR were included. There was a weak but statistically significant correlation (r = 0.21, p = 0.004) between the eNose measurements and TAC _trough. The root mean squared error of prediction for the diagnostic capacity was 3.186 in the training and 3.131 in the validation set. The accuracy of categorization ranged between 45%-63% for the training set and 52%-69% in the validation set. There is a weak correlation between eNose breathprints and TAC _trough in LTR. However, the diagnostic as well as categorization capacity for TAC _trough using eNose breathprints is too inaccurate to be applicable in TDM.